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carlos andino

https://en.wikipedia.org/wiki/Carlos_Andino

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16055831-2.html.csv

aggregation

carlos andino 's vale tudo fights lasted a combined total of 8 rounds .

{'scope': 'all', 'col': '6', 'type': 'sum', 'result': '8', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'round'], 'result': '8', 'ind': 0, 'tostr': 'sum { all_rows ; round }'}, '8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; round } ; 8 } = true', 'tointer': 'the sum of the round record of all rows is 8 .'}

round_eq { sum { all_rows ; round } ; 8 } = true

the sum of the round record of all rows is 8 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'round_4': 4, '8_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'round_4': 'round', '8_5': '8'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'round_4': [0], '8_5': [1]}

['result', 'record', 'opponent', 'method', 'date', 'round', 'location', 'notes']

[['win', '1 - 0 - 0', 'joa mendes', 'knockout ( strikes )', '1995', '1', 'itapeua , brazil', 'vale tudo'], ['win', '2 - 0 - 0', 'larry reynolds', 'knockout ( strikes )', '1995', '1', 'itapeua , brazil', 'vale tudo'], ['win', '3 - 0 - 0', 'héctor rodríguez', 'knockout ( strikes )', '1995', '1', 'itapeua , brazil', 'vale tudo'], ['win', '4 - 0 - 0', 'larry reynolds', 'knockout ( strikes )', '1996', '1', 'itapeua , brazil', 'vale tudo'], ['win', '5 - 0 - 0', 'luigi maiolini', 'knockout ( strikes )', '1999', '1', 'itapeua , brazil', 'vale tudo'], ['loss', '5 - 1 - 0', 'junior pitbull', 'knockout ( strikes )', '2003', '1', 'itapeua , brazil', 'vale tudo'], ['loss', '5 - 2 - 0', 'zuluzinho', 'knockout ( strikes )', '4 november 2003', '1', 'itapeua , brazil', 'vale tudo'], ['loss', '5 - 3 - 0', 'osvaldo castuera', 'submission ( armbar )', '2007', '1', 'itapeua , brazil', 'vale tudo']]

george mason patriots men 's basketball

https://en.wikipedia.org/wiki/George_Mason_Patriots_men%27s_basketball

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12661367-1.html.csv

ordinal

kenny sanders , a george mason patriots men 's basketball player , has scored the second-highest amount of points in the school 's history .

{'row': '2', 'col': '6', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'total points', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total points ; 2 }'}, 'player'], 'result': 'kenny sanders', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total points ; 2 } ; player }'}, 'kenny sanders'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total points ; 2 } ; player } ; kenny sanders } = true', 'tointer': 'select the row whose total points record of all rows is 2nd maximum . the player record of this row is kenny sanders .'}

eq { hop { nth_argmax { all_rows ; total points ; 2 } ; player } ; kenny sanders } = true

select the row whose total points record of all rows is 2nd maximum . the player record of this row is kenny sanders .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total points_5': 5, '2_6': 6, 'player_7': 7, 'kenny sanders_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', 'total points_5': 'total points', '2_6': '2', 'player_7': 'player', 'kenny sanders_8': 'kenny sanders'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total points_5': [0], '2_6': [0], 'player_7': [1], 'kenny sanders_8': [2]}

['rank', 'player', 'years', 'games', 'ppg avg', 'total points']

[['1', 'carlos yates', '1981 - 1985', '109', '22.2', '2420'], ['2', 'kenny sanders', '1985 - 1989', '107', '20.3', '2177'], ['3', 'george evans', '1997 - 2001', '116', '16.8', '1953'], ['4', 'robert dykes', '1987 - 1991', '122', '13.4', '1642'], ['5', 'ryan pearson', '2008 - 2012', '129', '12.6', '1626'], ['6', 'andre gaddy', '1977 - 1982', '98', '16.0', '1568'], ['7', 'rob rose', '1982 - 1986', '113', '13.8', '1565'], ['8', 'will thomas', '2004 - 2008', '131', '11.9', '1564'], ['9', 'folarin campbell', '2004 - 2008', '130', '11.9', '1545'], ['10', 'rudolph jones', '1971 - 1973', '59', '25.8', '1525']]

nick watney

https://en.wikipedia.org/wiki/Nick_Watney

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10856203-5.html.csv

count

the masters tournament and the pga championship were the only two tournaments that nick watney made the top ten in .

{'scope': 'all', 'criterion': 'equal', 'value': '1', 'result': '2', 'col': '3', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'top - 10', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top - 10 record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; top - 10 ; 1 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; top - 10 ; 1 } }', 'tointer': 'select the rows whose top - 10 record is equal to 1 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; top - 10 ; 1 } } ; 2 } = true', 'tointer': 'select the rows whose top - 10 record is equal to 1 . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; top - 10 ; 1 } } ; 2 } = true

select the rows whose top - 10 record is equal to 1 . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'top - 10_5': 5, '1_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'top - 10_5': 'top - 10', '1_6': '1', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'top - 10_5': [0], '1_6': [0], '2_7': [2]}

['tournament', 'wins', 'top - 10', 'top - 25', 'events', 'cuts made']

[['masters tournament', '0', '1', '4', '6', '6'], ['us open', '0', '0', '1', '7', '3'], ['the open championship', '0', '1', '2', '6', '4'], ['pga championship', '0', '0', '2', '6', '2'], ['totals', '0', '2', '9', '25', '15']]

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/2-11545282-3.html.csv

comparative

jarron collins played for the jazz for longer than dell curry did .

{'row_1': '9', 'row_2': '18', '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', 'player', 'jarron collins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to jarron collins .', 'tostr': 'filter_eq { all_rows ; player ; jarron collins }'}, 'years for jazz'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; jarron collins } ; years for jazz }', 'tointer': 'select the rows whose player record fuzzily matches to jarron collins . take the years for jazz record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'dell curry'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to dell curry .', 'tostr': 'filter_eq { all_rows ; player ; dell curry }'}, 'years for jazz'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; dell curry } ; years for jazz }', 'tointer': 'select the rows whose player record fuzzily matches to dell curry . take the years for jazz record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; jarron collins } ; years for jazz } ; hop { filter_eq { all_rows ; player ; dell curry } ; years for jazz } } = true', 'tointer': 'select the rows whose player record fuzzily matches to jarron collins . take the years for jazz record of this row . select the rows whose player record fuzzily matches to dell curry . take the years for jazz record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; player ; jarron collins } ; years for jazz } ; hop { filter_eq { all_rows ; player ; dell curry } ; years for jazz } } = true

select the rows whose player record fuzzily matches to jarron collins . take the years for jazz record of this row . select the rows whose player record fuzzily matches to dell curry . take the years for jazz 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, 'player_7': 7, 'jarron collins_8': 8, 'years for jazz_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'dell curry_12': 12, 'years for jazz_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', 'player_7': 'player', 'jarron collins_8': 'jarron collins', 'years for jazz_9': 'years for jazz', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'dell curry_12': 'dell curry', 'years for jazz_13': 'years for jazz'}

{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'jarron collins_8': [0], 'years for jazz_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'dell curry_12': [1], 'years for jazz_13': [3]}

['player', 'nationality', 'position', 'years for jazz', 'school / club team']

[['mack calvin', 'united states', 'guard', '1979 - 80', 'usc'], ['antoine carr', 'united states', 'forward - center', '1994 - 98', 'wichita state'], ['bobby cattage', 'united states', 'forward', '1981 - 82', 'auburn'], ['tom chambers', 'united states', 'forward', '1993 - 95', 'utah'], ['calbert cheaney', 'united states', 'guard - forward', '2002 - 03', 'indiana'], ['pete chilcutt', 'united states', 'forward - center', '1999 - 2000', 'north carolina'], ['keon clark', 'united states', 'forward - center', '2003 - 04', 'unlv'], ['e c coleman', 'united states', 'forward', '1974 - 77', 'houston baptist'], ['jarron collins', 'united states', 'center', '2001 - 2009', 'stanford'], ['jeff cook', 'united states', 'center', '1985 - 86', 'idaho state'], ['wayne cooper', 'united states', 'forward - center', '1980 - 81', 'new orleans'], ['tyrone corbin', 'united states', 'forward', '1991 - 94', 'depaul'], ['mel counts', 'united states', 'forward - center', '1974 - 76', 'oregon state'], ['john crotty', 'united states', 'guard', '1992 - 95 , 2000 - 02', 'virginia'], ['corey crowder', 'united states', 'guard - forward', '1991 - 92', 'kentucky wesleyan'], ['pat cummings', 'united states', 'center', '1990 - 91', 'cincinnati'], ['william cunningham', 'united states', 'center', '1997 - 98', 'temple'], ['dell curry', 'united states', 'guard', '1986 - 87', 'virginia tech']]

1969 los angeles dodgers season

https://en.wikipedia.org/wiki/1969_Los_Angeles_Dodgers_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12901325-10.html.csv

majority

the majority of these players did not sign with the los angeles dodgers .

{'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'no', 'subset': None}

{'func': 'all_str_eq', 'args': ['all_rows', 'signed', 'no'], 'result': True, 'ind': 0, 'tointer': 'for the signed records of all rows , all of them fuzzily match to no .', 'tostr': 'all_eq { all_rows ; signed ; no } = true'}

all_eq { all_rows ; signed ; no } = true

for the signed records of all rows , all of them fuzzily match to no .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'signed_3': 3, 'no_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'signed_3': 'signed', 'no_4': 'no'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'signed_3': [0], 'no_4': [0]}

['round', 'name', 'position', 'school', 'signed']

[['1', 'pat harrison', 'inf', 'university of southern california', 'no'], ['2', 'william camp', 'rhp', 'oklahoma state university', 'no cubs - 1970'], ['3', 'george pugh', 'lhp', 'mesa community college', 'no'], ['4', 'william ferguson', '1b', 'texas christian university', 'no reds - 1969 june'], ['5', 'george putz', '1b', 'springfield college', 'no cardinals - 1969 june']]

global challenge

https://en.wikipedia.org/wiki/Global_Challenge

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1227024-4.html.csv

majority

most participants scored under 90 points for the 2004 global challenge race .

{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '90', 'subset': None}

{'func': 'most_less', 'args': ['all_rows', 'points', '90'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are less than 90 .', 'tostr': 'most_less { all_rows ; points ; 90 } = true'}

most_less { all_rows ; points ; 90 } = true

for the points records of all rows , most of them are less than 90 .

1

1

{'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '90_4': 4}

{'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '90_4': '90'}

{'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '90_4': [0]}

['overall place', 'yacht name', 'skipper', 'points', 'combined elapsed time']

[['1', 'bg spirit', 'andy forbes', '90', '166d 00h 50 m 36s'], ['2', 'barclays adventurer', 'stuart jackson', '76', '168d 09h 39 m 09s'], ['3', 'bp explorer', 'david melville', '74', '167d 13h 16 m 25s'], ['4', 'spirit of sark', 'duggie gillespie', '73', '166d 19h 15 m 25s'], ['5', 'saic la jolla', 'eero lehtinen', '71', '168d 20h 09 m 51s'], ['6', 'team stelmar', 'clive cosby', '66', '184d 15h 04 m 11s'], ['7 =', 'me to you', 'james allen', '63', '170d 16h 07 m 02s'], ['7 =', 'vaio', 'amedeo sorrentino', '63', '170d 11h 31 m 10s'], ['9', 'samsung', 'matt riddell', '58', '170d 06h 13 m 10s'], ['10', 'imagine it done', 'dee caffari', '56', '168d 23h 31 m 26s'], ['11', 'pindar', 'loz marriott', '54', '174d 01h 11 m 59s'], ['12', 'save the children', 'paul kelly', '41', '176d 03h 37 m 23s']]

greg pursley

https://en.wikipedia.org/wiki/Greg_Pursley

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15544826-1.html.csv

aggregation

from 2009 - 2012 , greg pursley won a total of 11 times .

{'scope': 'all', 'col': '3', 'type': 'sum', 'result': '11', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'wins'], 'result': '11', 'ind': 0, 'tostr': 'sum { all_rows ; wins }'}, '11'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; wins } ; 11 } = true', 'tointer': 'the sum of the wins record of all rows is 11 .'}

round_eq { sum { all_rows ; wins } ; 11 } = true

the sum of the wins record of all rows is 11 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'wins_4': 4, '11_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'wins_4': 'wins', '11_5': '11'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'wins_4': [0], '11_5': [1]}

['year', 'races', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'season rank']

[['1999', '1', '0', '0', '0', '0', '16.0', '11.0', '64th'], ['2002', '10', '0', '2', '5', '0', '9.2', '10.2', '9th'], ['2007', '1', '0', '0', '0', '0', '22.0', '29.0', '69th'], ['2008', '4', '0', '0', '0', '0', '12.8', '25.2', '32nd'], ['2009', '13', '1', '8', '11', '2', '6.5', '6.3', '3rd'], ['2010', '12', '2', '4', '7', '3', '4.7', '11.6', '5th'], ['2011', '14', '6', '12', '12', '6', '3.3', '5.2', '1st'], ['2012', '9', '2', '7', '9', '3', '3.2', '3.8', '2nd']]

2010 tim hortons brier

https://en.wikipedia.org/wiki/2010_Tim_Hortons_Brier

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25381437-2.html.csv

comparative

jeff richard had one less win than serge reid .

{'row_1': '8', 'row_2': '6', 'col': '3', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'skip', 'jeff richard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose skip record fuzzily matches to jeff richard .', 'tostr': 'filter_eq { all_rows ; skip ; jeff richard }'}, 'w'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; skip ; jeff richard } ; w }', 'tointer': 'select the rows whose skip record fuzzily matches to jeff richard . take the w record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'skip', 'serge reid'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose skip record fuzzily matches to serge reid .', 'tostr': 'filter_eq { all_rows ; skip ; serge reid }'}, 'w'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; skip ; serge reid } ; w }', 'tointer': 'select the rows whose skip record fuzzily matches to serge reid . take the w record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; skip ; jeff richard } ; w } ; hop { filter_eq { all_rows ; skip ; serge reid } ; w } } = true', 'tointer': 'select the rows whose skip record fuzzily matches to jeff richard . take the w record of this row . select the rows whose skip record fuzzily matches to serge reid . take the w record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; skip ; jeff richard } ; w } ; hop { filter_eq { all_rows ; skip ; serge reid } ; w } } = true

select the rows whose skip record fuzzily matches to jeff richard . take the w record of this row . select the rows whose skip record fuzzily matches to serge reid . take the w 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, 'skip_7': 7, 'jeff richard_8': 8, 'w_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'skip_11': 11, 'serge reid_12': 12, 'w_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', 'skip_7': 'skip', 'jeff richard_8': 'jeff richard', 'w_9': 'w', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'skip_11': 'skip', 'serge reid_12': 'serge reid', 'w_13': 'w'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'skip_7': [0], 'jeff richard_8': [0], 'w_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'skip_11': [1], 'serge reid_12': [1], 'w_13': [3]}

['locale', 'skip', 'w', 'l', 'pf', 'pa', 'ends won', 'ends lost', 'blank ends', 'stolen ends', 'shot pct']

[['ontario', 'glenn howard', '11', '0', '90', '45', '50', '35', '8', '15', '88'], ['northern ontario', 'brad jacobs', '9', '2', '80', '54', '49', '39', '6', '17', '84'], ['alberta', 'kevin koe', '8', '3', '81', '62', '45', '42', '9', '11', '85'], ['newfoundland and labrador', 'brad gushue', '8', '3', '79', '53', '45', '35', '9', '11', '84'], ['manitoba', 'jeff stoughton', '7', '4', '71', '58', '45', '41', '9', '12', '83'], ['quebec', 'serge reid', '5', '6', '60', '71', '41', '42', '8', '9', '76'], ['saskatchewan', 'darrell mckee', '4', '7', '70', '79', '44', '44', '5', '7', '80'], ['british columbia', 'jeff richard', '4', '7', '68', '71', '43', '45', '9', '6', '79'], ['new brunswick', 'james grattan', '3', '8', '56', '71', '38', '47', '11', '6', '79'], ['nova scotia', 'ian fitzner - leblanc', '3', '8', '62', '90', '38', '54', '2', '5', '76'], ['prince edward island', 'rod macdonald', '3', '8', '64', '75', '44', '47', '8', '7', '80']]

iran at the 2007 asian indoor games

https://en.wikipedia.org/wiki/Iran_at_the_2007_Asian_Indoor_Games

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14350710-31.html.csv

ordinal

mostafa abdollahi participated in the second heaviest weight division for iran at the 2007 asian indoor games .

{'row': '4', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'event', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; event ; 2 }'}, 'athlete'], 'result': 'mostafa abdollahi', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; event ; 2 } ; athlete }'}, 'mostafa abdollahi'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; event ; 2 } ; athlete } ; mostafa abdollahi } = true', 'tointer': 'select the row whose event record of all rows is 2nd maximum . the athlete record of this row is mostafa abdollahi .'}

eq { hop { nth_argmax { all_rows ; event ; 2 } ; athlete } ; mostafa abdollahi } = true

select the row whose event record of all rows is 2nd maximum . the athlete record of this row is mostafa abdollahi .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'event_5': 5, '2_6': 6, 'athlete_7': 7, 'mostafa abdollahi_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', 'event_5': 'event', '2_6': '2', 'athlete_7': 'athlete', 'mostafa abdollahi_8': 'mostafa abdollahi'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'event_5': [0], '2_6': [0], 'athlete_7': [1], 'mostafa abdollahi_8': [2]}

['athlete', 'event', 'quarterfinal', 'semifinal', 'final']

[['ali ekranpour', '63.5 kg', 'did not advance', 'did not advance', 'did not advance'], ['jalal motamedi', '67 kg', 'ng ( mac ) w 5 - 0', 'kahhorov ( uzb ) l 0 - 5', 'did not advance'], ['vahid roshani', '71 kg', 'jawad ( irq ) w 5 - 0', 'shetty ( ind ) w rsch', 'kadirkulov ( uzb ) l 1 - 4'], ['mostafa abdollahi', '75 kg', 'chu ( mac ) w knockout', 'el - kaissi ( lib ) w rsch', 'shukla ( ind ) w rsch'], ['yousef soltani', '81 kg', 'matsumoto ( jpn ) l 0 - 5', 'did not advance', 'did not advance']]

houston rockets all - time roster

https://en.wikipedia.org/wiki/Houston_Rockets_all-time_roster

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11734041-3.html.csv

superlative

carroll , joe barry joe barry carroll was the tallest player at 7 feet 1 inch for the houston rockets .

{'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', 'height in ft'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; height in ft }'}, 'player'], 'result': 'carroll , joe barry joe barry carroll', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; height in ft } ; player }'}, 'carroll , joe barry joe barry carroll'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; height in ft } ; player } ; carroll , joe barry joe barry carroll } = true', 'tointer': 'select the row whose height in ft record of all rows is maximum . the player record of this row is carroll , joe barry joe barry carroll .'}

eq { hop { argmax { all_rows ; height in ft } ; player } ; carroll , joe barry joe barry carroll } = true

select the row whose height in ft record of all rows is maximum . the player record of this row is carroll , joe barry joe barry carroll .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'height in ft_5': 5, 'player_6': 6, 'carroll , joe barry joe barry carroll_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'height in ft_5': 'height in ft', 'player_6': 'player', 'carroll , joe barry joe barry carroll_7': 'carroll , joe barry joe barry carroll'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'height in ft_5': [0], 'player_6': [1], 'carroll , joe barry joe barry carroll_7': [2]}

['player', 'no ( s )', 'height in ft', 'position', 'years for rockets', 'school / club team / country']

[['caldwell , adrian adrian caldwell', '44', '6 - 8', 'forward', '1989 - 91 , 1994 - 95', 'lamar'], ['carr , antoine antoine carr', '55', '6 - 9', 'forward', '1998 - 99', 'wichita state'], ['carroll , joe barry joe barry carroll', '2', '7 - 1', 'center / forward', '1987 - 88', 'purdue'], ['cassell , sam sam cassell', '10', '6 - 3', 'guard', '1993 - 96', 'florida state'], ['cato , kelvin kelvin cato', '13', '6 - 11', 'center', '1999 - 2004', 'iowa state'], ['chievous , derrick derrick chievous', '3', '6 - 7', 'guard / forward', '1988 - 90', 'missouri'], ['chilcutt , pete pete chilcutt', '32', '6 - 10', 'forward', '1994 - 96', 'north carolina'], ['coleman , ec ec coleman', '12 , 44', '6 - 8', 'forward', '1973 - 74 , 1978 - 79', 'houston baptist'], ['collier , jason jason collier', '52', '7 - 0', 'forward / center', '2000 - 03', 'georgia tech'], ['colson , sean sean colson', '20', '6 - 0', 'guard', '2000 - 01', 'unc - charlotte'], ['conner , lester lester conner', '7', '6 - 4', 'guard', '1987 - 88', 'oregon state'], ['cook , brian brian cook', '43', '6 - 9', 'forward', '2009 - 10', 'illinois'], ['cunningham , dick dick cunningham', '34', '6 - 10', 'center', '1971 - 72', 'murray state'], ['cureton , earl earl cureton', '35', '6 - 9', 'forward / center', '1993 - 94', 'detroit , robert morris'], ['curley , bill bill curley', '15', '6 - 9', 'forward', '1999 - 2000', 'boston college']]

list of fc barcelona records and statistics

https://en.wikipedia.org/wiki/List_of_FC_Barcelona_records_and_statistics

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14707564-7.html.csv

comparative

ladislao kubala scored more total goals for fc barcelona than carles rexach scored .

{'row_1': '5', 'row_2': '9', 'col': '4', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'ladislao kubala'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to ladislao kubala .', 'tostr': 'filter_eq { all_rows ; name ; ladislao kubala }'}, 'goals'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; ladislao kubala } ; goals }', 'tointer': 'select the rows whose name record fuzzily matches to ladislao kubala . take the goals record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'carles rexach'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to carles rexach .', 'tostr': 'filter_eq { all_rows ; name ; carles rexach }'}, 'goals'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; carles rexach } ; goals }', 'tointer': 'select the rows whose name record fuzzily matches to carles rexach . take the goals record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; ladislao kubala } ; goals } ; hop { filter_eq { all_rows ; name ; carles rexach } ; goals } } = true', 'tointer': 'select the rows whose name record fuzzily matches to ladislao kubala . take the goals record of this row . select the rows whose name record fuzzily matches to carles rexach . take the goals record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; name ; ladislao kubala } ; goals } ; hop { filter_eq { all_rows ; name ; carles rexach } ; goals } } = true

select the rows whose name record fuzzily matches to ladislao kubala . take the goals record of this row . select the rows whose name record fuzzily matches to carles rexach . take the goals 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, 'ladislao kubala_8': 8, 'goals_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'carles rexach_12': 12, 'goals_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', 'ladislao kubala_8': 'ladislao kubala', 'goals_9': 'goals', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'carles rexach_12': 'carles rexach', 'goals_13': 'goals'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'ladislao kubala_8': [0], 'goals_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'carles rexach_12': [1], 'goals_13': [3]}

['ranking', 'nationality', 'name', 'goals', 'years']

[['1', 'philippines', 'paulino alcántara', '369', '1912 - 1916 , 1918 - 1927'], ['2', 'argentina', 'lionel messi', '352', '2004 -'], ['3', 'spain', 'josep samitier', '333', '1919 - 1932'], ['4', 'spain', 'césar rodríguez', '301', '1942 - 1955'], ['5', 'hungary', 'ladislao kubala', '280', '1950 - 1961'], ['6', 'spain', 'josep escolà', '223', '1934 - 1949'], ['7', 'spain', 'ángel arocha', '215', '1926 - 1933'], ['8', 'spain', 'vicenç martínez', '200', '1912 - 1923'], ['9', 'spain', 'carles rexach', '195', '1965 - 1981'], ['10', 'spain', 'mariano martín', '188', '1939 - 1946']]

1942 green bay packers season

https://en.wikipedia.org/wiki/1942_Green_Bay_Packers_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14877626-1.html.csv

majority

the majority of the players picked from minnesota were picked in round 1 through round 11 .

{'scope': 'subset', 'col': '1', 'most_or_all': 'most', 'criterion': 'less_than_eq', 'value': '11', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'minnesota'}}

{'func': 'most_less_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'minnesota'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; school / club team ; minnesota }', 'tointer': 'select the rows whose school / club team record fuzzily matches to minnesota .'}, 'round', '11'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose school / club team record fuzzily matches to minnesota . for the round records of these rows , most of them are less than or equal to 11 .', 'tostr': 'most_less_eq { filter_eq { all_rows ; school / club team ; minnesota } ; round ; 11 } = true'}

most_less_eq { filter_eq { all_rows ; school / club team ; minnesota } ; round ; 11 } = true

select the rows whose school / club team record fuzzily matches to minnesota . for the round records of these rows , most of them are less than or equal to 11 .

2

2

{'most_less_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'school / club team_4': 4, 'minnesota_5': 5, 'round_6': 6, '11_7': 7}

{'most_less_eq_1': 'most_less_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'school / club team_4': 'school / club team', 'minnesota_5': 'minnesota', 'round_6': 'round', '11_7': '11'}

{'most_less_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'school / club team_4': [0], 'minnesota_5': [0], 'round_6': [1], '11_7': [1]}

['round', 'pick', 'player', 'position', 'school / club team']

[['1', '9', 'urban odson', 'tackle', 'minnesota'], ['3', '24', 'ray frankowski', 'guard', 'washington'], ['5', '39', 'bill green', 'back', 'iowa'], ['6', '49', 'joe krivonak', 'guard', 'south carolina'], ['7', '59', 'preston johnston', 'back', 'smu'], ['8', '69', 'joe rogers', 'end', 'michigan'], ['9', '79', 'noah langdale', 'tackle', 'alabama'], ['10', '89', 'gene flick', 'center', 'minnesota'], ['11', '99', 'tom farris', 'back', 'wisconsin'], ['12', '109', 'jimmy richardson', 'back', 'marquette'], ['13', '119', 'bruce smith', 'halfback', 'minnesota'], ['14', '129', 'bill applegate', 'guard', 'south carolina'], ['15', '139', 'jim trimble', 'tackle', 'indiana'], ['16', '149', 'tom kinkade', 'back', 'ohio state'], ['17', '159', 'fred preston', 'end', 'nebraska'], ['18', '169', 'robert ingalls', 'center', 'michigan'], ['19', '179', 'george benson', 'back', 'northwestern'], ['20', '189', 'horace young', 'back', 'smu'], ['21', '194', 'henry woronicz', 'end', 'boston college'], ['22', '199', 'woody adams', 'tackle', 'tcu']]

list of stargate audiobooks

https://en.wikipedia.org/wiki/List_of_Stargate_audiobooks

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16279520-1.html.csv

majority

most of the titles had sharon gosling as the director .

{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'sharon gosling', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'director', 'sharon gosling'], 'result': True, 'ind': 0, 'tointer': 'for the director records of all rows , most of them fuzzily match to sharon gosling .', 'tostr': 'most_eq { all_rows ; director ; sharon gosling } = true'}

most_eq { all_rows ; director ; sharon gosling } = true

for the director records of all rows , most of them fuzzily match to sharon gosling .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'director_3': 3, 'sharon gosling_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'director_3': 'director', 'sharon gosling_4': 'sharon gosling'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'director_3': [0], 'sharon gosling_4': [0]}

['title', 'series', 'release', 'featuring', 'writer', 'director', 'length', 'timeline', 'release date']

[['gift of the gods', 'stargate sg - 1', '1.1', 'michael shanks john schwab', 'sally malcolm', 'sharon gosling', "70 '", 'season 3 before fair game', 'april 1 , 2008'], ['a necessary evil', 'stargate atlantis', '1.2', 'torri higginson timothy watson', 'sharon gosling', 'sharon gosling', "70 '", 'season 3 , bookended by season 4', 'may 2008'], ['shell game', 'stargate sg - 1', '1.3', 'claudia black michael shanks', 'james swallow', 'sharon gosling', "70 '", 'season 10 after the pegasus project', 'june 1 , 2008'], ['perchance to dream', 'stargate atlantis', '1.4', 'paul mcgillion sara douglas', 'sally malcolm', 'sharon gosling', "70 '", 'season 2', 'july 2008'], ['savarna', 'stargate sg - 1', '1.5', 'teryl rothery toby longworth', 'sally malcolm', 'sharon gosling', "70 '", 'season 7 between grace and heroes', 'august 2008'], ['zero point', 'stargate atlantis', '1.6', 'david nykl ursula burton', 'james swallow', 'sharon gosling', "70 '", 'early season 4', 'september 2008'], ['first prime', 'stargate sg - 1', '2.1', 'christopher judge noel clarke', 'james swallow', 'sharon gosling', "70 '", 'season 4', 'may 30 , 2009'], ['impressions', 'stargate atlantis', '2.2', 'kavan smith nicholas briggs', 'scott andrews', 'sharon gosling', "60 '", 'season 4 between lifeline and doppelganger', 'june 30 , 2009'], ['pathogen', 'stargate sg - 1', '2.3', 'teryl rothery christopher judge', 'sharon gosling', 'sharon gosling', "60 '", 'season 7 between fragile balance and heroes', 'july 31 , 2009'], ['the kindness of strangers', 'stargate atlantis', '2.4', 'paul mcgillion neil roberts', 'sharon gosling', 'sharon gosling', "60 '", 'season 2 / 3 before sunday', 'august 31 , 2009'], ['meltdown', 'stargate atlantis', '2.6', 'david nykl aiden j david', 'david a mcintee', 'sharon gosling', "60 '", "season 2 , shortly before coup d'etat", 'october 30 , 2009'], ['half - life', 'stargate sg - 1', '3.1', 'michael shanks claudia black cliff simon', 'james swallow', 'lisa bowerman & jason haigh - ellery', "60 '", "season 9 , between stronghold and arthur 's mantle", 'may 2012'], ['an eye for an eye', 'stargate sg - 1', '3.2', 'michael shanks claudia black cliff simon', 'sally malcolm', 'lisa bowerman & jason haigh - ellery', "60 '", "season 9 , between stronghold and arthur 's mantle", 'may 2012'], ['infiltration', 'stargate sg - 1', '3.3', 'michael shanks claudia black cliff simon', 'steve lyons', 'lisa bowerman & jason haigh - ellery', "60 '", "season 9 , between stronghold and arthur 's mantle", 'may 2012'], ['excision', 'stargate sg - 1', '3.4', 'michael shanks claudia black', 'peter j evans', 'lisa bowerman & jason haigh - ellery', "60 '", 'after stargate season 10', 'december 2012'], ['duplicity', 'stargate sg - 1', '3.5', 'michael shanks claudia black', 'richard dinnick', 'lisa bowerman & jason haigh - ellery', "60 '", 'after stargate season 10', 'december 2012']]

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/2-167235-8.html.csv

count

two of the albanian prime ministers have been with the democratic party of albania .

{'scope': 'all', 'criterion': 'equal', 'value': 'democratic party of albania', 'result': '2', 'col': '5', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'political party', 'democratic party of albania'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose political party record fuzzily matches to democratic party of albania .', 'tostr': 'filter_eq { all_rows ; political party ; democratic party of albania }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; political party ; democratic party of albania } }', 'tointer': 'select the rows whose political party record fuzzily matches to democratic party of albania . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; political party ; democratic party of albania } } ; 2 } = true', 'tointer': 'select the rows whose political party record fuzzily matches to democratic party of albania . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; political party ; democratic party of albania } } ; 2 } = true

select the rows whose political party record fuzzily matches to democratic party of albania . 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, 'political party_5': 5, 'democratic party of albania_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', 'political party_5': 'political party', 'democratic party of albania_6': 'democratic party of albania', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'political party_5': [0], 'democratic party of albania_6': [0], '2_7': [2]}

['name', 'born - died', 'term start', 'term end', 'political party']

[['prime ministers 1991 onwards', 'prime ministers 1991 onwards', 'prime ministers 1991 onwards', 'prime ministers 1991 onwards', 'prime ministers 1991 onwards'], ['fatos nano ( 1st time )', '1952 -', '22 february 1991', '5 june 1991', 'party of labour of albania'], ['ylli bufi', '1948 -', '5 june 1991', '10 december 1991', 'socialist party of albania'], ['vilson ahmeti', '1951 -', '10 december 1991', '13 april 1992', 'non - party'], ['aleksandër meksi', '1939 -', '13 april 1992', '11 march 1997', 'democratic party of albania'], ['bashkim fino', '1962 -', '11 march 1997', '24 july 1997', 'socialist party of albania'], ['fatos nano ( 2nd time )', '1952 -', '24 july 1997', '2 october 1998', 'socialist party of albania'], ['pandeli majko ( 1st time )', '1967 -', '2 october 1998', '29 october 1999', 'socialist party of albania'], ['ilir meta', '1969 -', '29 october 1999', '22 february 2002', 'socialist party of albania'], ['pandeli majko ( 2nd time )', '1967 -', '22 february 2002', '31 july 2002', 'socialist party of albania'], ['fatos nano ( 3rd time )', '1952 -', '31 july 2002', '11 september 2005', 'socialist party of albania'], ['sali berisha', '1944 -', '11 september 2005', '15 september 2013', 'democratic party of albania'], ['edi rama', '1964 -', '15 september 2013', 'incumbent', 'socialist party of albania']]

national democratic congress ( ghana )

https://en.wikipedia.org/wiki/National_Democratic_Congress_%28Ghana%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1725076-2.html.csv

count

the outcome of the election was ndc opposition two different times .

{'scope': 'all', 'criterion': 'equal', 'value': 'ndc opposition', 'result': '2', 'col': '5', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'outcome of election', 'ndc opposition'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose outcome of election record fuzzily matches to ndc opposition .', 'tostr': 'filter_eq { all_rows ; outcome of election ; ndc opposition }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; outcome of election ; ndc opposition } }', 'tointer': 'select the rows whose outcome of election record fuzzily matches to ndc opposition . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; outcome of election ; ndc opposition } } ; 2 } = true', 'tointer': 'select the rows whose outcome of election record fuzzily matches to ndc opposition . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; outcome of election ; ndc opposition } } ; 2 } = true

select the rows whose outcome of election record fuzzily matches to ndc opposition . 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, 'outcome of election_5': 5, 'ndc opposition_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', 'outcome of election_5': 'outcome of election', 'ndc opposition_6': 'ndc opposition', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'outcome of election_5': [0], 'ndc opposition_6': [0], '2_7': [2]}

['election', 'candidate', 'number of votes', 'share of votes', 'outcome of election']

[['2012', 'john dramani mahama', '5574761', '50.7 %', 'mahama ndc government'], ['2008 ( 2 )', 'john atta mills', '4501466', '50.1 %', 'mills ndc government'], ['2008 ( 1 )', 'john atta mills', '4056634', '47.9 %', '2nd round election'], ['2004', 'john atta mills', '3850368', '44.6 %', 'ndc opposition'], ['2000 ( 2nd )', 'john atta mills', '2728241', '43.3 %', 'ndc opposition'], ['2000 ( 1st )', 'john atta mills', '2895575', '44.8 %', '2nd round election'], ['1996', 'jerry rawlings', 'n / a', '57.4 %', '2nd rawlings ndc government'], ['1992', 'jerry rawlings', '2327600', '58.4 %', 'rawlings ndc government']]

wru division five south west

https://en.wikipedia.org/wiki/WRU_Division_Five_South_West

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17675675-1.html.csv

comparative

glais rfc lost less of their matches than tycroes rfc lost .

{'row_1': '9', 'row_2': '10', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'glais rfc'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to glais rfc .', 'tostr': 'filter_eq { all_rows ; club ; glais rfc }'}, 'lost'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club ; glais rfc } ; lost }', 'tointer': 'select the rows whose club record fuzzily matches to glais rfc . take the lost record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'tycroes rfc'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to tycroes rfc .', 'tostr': 'filter_eq { all_rows ; club ; tycroes rfc }'}, 'lost'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; club ; tycroes rfc } ; lost }', 'tointer': 'select the rows whose club record fuzzily matches to tycroes rfc . take the lost record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; club ; glais rfc } ; lost } ; hop { filter_eq { all_rows ; club ; tycroes rfc } ; lost } } = true', 'tointer': 'select the rows whose club record fuzzily matches to glais rfc . take the lost record of this row . select the rows whose club record fuzzily matches to tycroes rfc . take the lost record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; club ; glais rfc } ; lost } ; hop { filter_eq { all_rows ; club ; tycroes rfc } ; lost } } = true

select the rows whose club record fuzzily matches to glais rfc . take the lost record of this row . select the rows whose club record fuzzily matches to tycroes rfc . take the lost 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, 'club_7': 7, 'glais rfc_8': 8, 'lost_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'club_11': 11, 'tycroes rfc_12': 12, 'lost_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', 'club_7': 'club', 'glais rfc_8': 'glais rfc', 'lost_9': 'lost', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'club_11': 'club', 'tycroes rfc_12': 'tycroes rfc', 'lost_13': 'lost'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'club_7': [0], 'glais rfc_8': [0], 'lost_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'club_11': [1], 'tycroes rfc_12': [1], 'lost_13': [3]}

['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points']

[['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['birchgrove rfc', '20', '0', '3', '538', '257', '82', '29', '13', '2', '83'], ['neath athletic rfc', '20', '0', '3', '616', '194', '89', '24', '12', '2', '82'], ['trebanos rfc', '20', '0', '3', '701', '223', '99', '27', '13', '0', '81'], ['gowerton rfc', '20', '0', '9', '439', '389', '55', '52', '5', '5', '54'], ['llandybie rfc', '20', '0', '9', '338', '374', '38', '55', '4', '3', '51'], ['alltwen rfc', '20', '1', '10', '445', '382', '50', '42', '5', '4', '47'], ['crynant rfc', '20', '0', '12', '315', '454', '43', '66', '4', '3', '39'], ['glais rfc', '20', '1', '13', '233', '444', '33', '64', '0', '1', '27'], ['tycroes rfc', '20', '0', '15', '250', '617', '32', '88', '3', '3', '26'], ['cwmtwrch rfc', '20', '2', '14', '179', '466', '25', '66', '1', '1', '22'], ['cwmgors rfc', '20', '0', '17', '206', '460', '31', '64', '3', '6', '21'], ['penlan rfc', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0']]

allsvenskan

https://en.wikipedia.org/wiki/Allsvenskan

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1096793-8.html.csv

comparative

malmö ff has won more allsvenskan titles than ifk göteborg has won .

{'row_1': '1', 'row_2': '2', 'col': '3', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'malmö ff'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to malmö ff .', 'tostr': 'filter_eq { all_rows ; club ; malmö ff }'}, 'allsvenskan titles'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club ; malmö ff } ; allsvenskan titles }', 'tointer': 'select the rows whose club record fuzzily matches to malmö ff . take the allsvenskan titles record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'ifk göteborg'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to ifk göteborg .', 'tostr': 'filter_eq { all_rows ; club ; ifk göteborg }'}, 'allsvenskan titles'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; club ; ifk göteborg } ; allsvenskan titles }', 'tointer': 'select the rows whose club record fuzzily matches to ifk göteborg . take the allsvenskan titles record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; club ; malmö ff } ; allsvenskan titles } ; hop { filter_eq { all_rows ; club ; ifk göteborg } ; allsvenskan titles } } = true', 'tointer': 'select the rows whose club record fuzzily matches to malmö ff . take the allsvenskan titles record of this row . select the rows whose club record fuzzily matches to ifk göteborg . take the allsvenskan titles record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; club ; malmö ff } ; allsvenskan titles } ; hop { filter_eq { all_rows ; club ; ifk göteborg } ; allsvenskan titles } } = true

select the rows whose club record fuzzily matches to malmö ff . take the allsvenskan titles record of this row . select the rows whose club record fuzzily matches to ifk göteborg . take the allsvenskan titles 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, 'club_7': 7, 'malmö ff_8': 8, 'allsvenskan titles_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'club_11': 11, 'ifk göteborg_12': 12, 'allsvenskan titles_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', 'club_7': 'club', 'malmö ff_8': 'malmö ff', 'allsvenskan titles_9': 'allsvenskan titles', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'club_11': 'club', 'ifk göteborg_12': 'ifk göteborg', 'allsvenskan titles_13': 'allsvenskan titles'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'club_7': [0], 'malmö ff_8': [0], 'allsvenskan titles_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'club_11': [1], 'ifk göteborg_12': [1], 'allsvenskan titles_13': [3]}

['club', 'swedish championship titles', 'allsvenskan titles', 'introduced', 'stars symbolizes']

[['malmö ff', '17', '20', '2006', 'number of allsvenskan titles'], ['ifk göteborg', '18', '13', '2006', 'number of swedish championship titles'], ['ifk norrköping', '12', '12', '2006', 'number of swedish championship titles'], ['örgryte is', '12', '2', '2006', 'number of swedish championship titles'], ['djurgårdens if', '11', '7', '2006', 'number of swedish championship titles'], ['aik', '11', '5', '2000', 'number of swedish championship titles']]

frank kratovil

https://en.wikipedia.org/wiki/Frank_Kratovil

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16353840-1.html.csv

unique

the 2010 us house , maryland 's 1st district election was the only one that andy harris won .

{'scope': 'all', 'row': '5', 'col': '4', 'col_other': '1,2', 'criterion': 'equal', 'value': 'andy harris', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'subject', 'andy harris'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose subject record fuzzily matches to andy harris .', 'tostr': 'filter_eq { all_rows ; subject ; andy harris }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; subject ; andy harris } }', 'tointer': 'select the rows whose subject record fuzzily matches to andy harris . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'subject', 'andy harris'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose subject record fuzzily matches to andy harris .', 'tostr': 'filter_eq { all_rows ; subject ; andy harris }'}, 'year'], 'result': '2010', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; subject ; andy harris } ; year }'}, '2010'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; subject ; andy harris } ; year } ; 2010 }', 'tointer': 'the year record of this unqiue row is 2010 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'subject', 'andy harris'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose subject record fuzzily matches to andy harris .', 'tostr': 'filter_eq { all_rows ; subject ; andy harris }'}, 'office'], 'result': "us house , maryland 's 1st district", 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; subject ; andy harris } ; office }'}, "us house , maryland 's 1st district"], 'result': True, 'ind': 5, 'tostr': "eq { hop { filter_eq { all_rows ; subject ; andy harris } ; office } ; us house , maryland 's 1st district }", 'tointer': "the office record of this unqiue row is us house , maryland 's 1st district ."}], 'result': True, 'ind': 6, 'tostr': "and { eq { hop { filter_eq { all_rows ; subject ; andy harris } ; year } ; 2010 } ; eq { hop { filter_eq { all_rows ; subject ; andy harris } ; office } ; us house , maryland 's 1st district } }", 'tointer': "the year record of this unqiue row is 2010 . the office record of this unqiue row is us house , maryland 's 1st district ."}], 'result': True, 'ind': 7, 'tostr': "and { only { filter_eq { all_rows ; subject ; andy harris } } ; and { eq { hop { filter_eq { all_rows ; subject ; andy harris } ; year } ; 2010 } ; eq { hop { filter_eq { all_rows ; subject ; andy harris } ; office } ; us house , maryland 's 1st district } } } = true", 'tointer': "select the rows whose subject record fuzzily matches to andy harris . there is only one such row in the table . the year record of this unqiue row is 2010 . the office record of this unqiue row is us house , maryland 's 1st district ."}

and { only { filter_eq { all_rows ; subject ; andy harris } } ; and { eq { hop { filter_eq { all_rows ; subject ; andy harris } ; year } ; 2010 } ; eq { hop { filter_eq { all_rows ; subject ; andy harris } ; office } ; us house , maryland 's 1st district } } } = true

select the rows whose subject record fuzzily matches to andy harris . there is only one such row in the table . the year record of this unqiue row is 2010 . the office record of this unqiue row is us house , maryland 's 1st district .

10

8

{'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'subject_10': 10, 'andy harris_11': 11, 'and_6': 6, 'eq_3': 3, 'num_hop_2': 2, 'year_12': 12, '2010_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'office_14': 14, "us house , maryland 's 1st district_15": 15}

{'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'subject_10': 'subject', 'andy harris_11': 'andy harris', 'and_6': 'and', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_12': 'year', '2010_13': '2010', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'office_14': 'office', "us house , maryland 's 1st district_15": "us house , maryland 's 1st district"}

{'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'subject_10': [0], 'andy harris_11': [0], 'and_6': [7], 'eq_3': [6], 'num_hop_2': [3], 'year_12': [2], '2010_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'office_14': [4], "us house , maryland 's 1st district_15": [5]}

['year', 'office', 'election', 'subject', 'party', 'votes']

[['2002', "queen anne 's county state 's attorney", 'general', 'frank kratovil', 'democratic', '9169'], ['2006', "queen anne 's county state 's attorney", 'general', 'frank kratovil', 'democratic', '13894'], ['2008', "us house , maryland 's 1st district", 'primary', 'frank kratovil', 'democratic', '28566'], ['2008', "us house , maryland 's 1st district", 'general', 'frank kratovil', 'democratic', '177065'], ['2010', "us house , maryland 's 1st district", 'general', 'andy harris', 'republican', '155118']]

2008 washington redskins season

https://en.wikipedia.org/wiki/2008_Washington_Redskins_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10966926-4.html.csv

ordinal

the october 12 game against the st louis rams was in week 6 of the 2008 washington redskins season .

{'row': '6', 'col': '1', 'order': '6', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'week', '6'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; week ; 6 }'}, 'date'], 'result': 'october 12 , 2008', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; week ; 6 } ; date }'}, 'october 12 , 2008'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; week ; 6 } ; date } ; october 12 , 2008 } = true', 'tointer': 'select the row whose week record of all rows is 6th minimum . the date record of this row is october 12 , 2008 .'}

eq { hop { nth_argmin { all_rows ; week ; 6 } ; date } ; october 12 , 2008 } = true

select the row whose week record of all rows is 6th minimum . the date record of this row is october 12 , 2008 .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'week_5': 5, '6_6': 6, 'date_7': 7, 'october 12 , 2008_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', 'week_5': 'week', '6_6': '6', 'date_7': 'date', 'october 12 , 2008_8': 'october 12 , 2008'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'week_5': [0], '6_6': [0], 'date_7': [1], 'october 12 , 2008_8': [2]}

['week', 'date', 'opponent', 'time ( et )', 'result', 'game site', 'record', 'match report']

[['1', 'september 4 , 2008', 'new york giants', '7:00', 'l 7 - 16', 'giants stadium', '0 - 1', 'recap'], ['2', 'september 14 , 2008', 'new orleans saints', '1:00', 'w 29 - 24', 'fedex field', '1 - 1', 'recap'], ['3', 'september 21 , 2008', 'arizona cardinals', '1:00', 'w 24 - 17', 'fedex field', '2 - 1', 'recap'], ['4', 'september 28 , 2008', 'dallas cowboys', '4:15', 'w 26 - 24', 'texas stadium', '3 - 1', 'recap'], ['5', 'october 5 , 2008', 'philadelphia eagles', '1:00', 'w 23 - 17', 'lincoln financial field', '4 - 1', 'recap'], ['6', 'october 12 , 2008', 'st louis rams', '1:00', 'l 17 - 19', 'fedex field', '4 - 2', 'recap'], ['7', 'october 19 , 2008', 'cleveland browns', '4:15', 'w 14 - 11', 'fedex field', '5 - 2', 'recap'], ['8', 'october 26 , 2008', 'detroit lions', '1:00', 'w 25 - 17', 'ford field', '6 - 2', 'recap'], ['9', 'november 3 , 2008', 'pittsburgh steelers', '8:30', 'l 6 - 23', 'fedex field', '6 - 3', 'recap'], ['10', '-', '-', '-', '-', '-', '-', ''], ['11', 'november 16 , 2008', 'dallas cowboys', '8:15', 'l 10 - 14', 'fedex field', '6 - 4', 'recap'], ['12', 'november 23 , 2008', 'seattle seahawks', '4:15', 'w 20 - 17', 'qwest field', '7 - 4', 'recap'], ['13', 'november 30 , 2008', 'new york giants', '1:00', 'l 7 - 23', 'fedex field', '7 - 5', 'recap'], ['14', 'december 7 , 2008', 'baltimore ravens', '8:15', 'l 10 - 24', 'm & t bank stadium', '7 - 6', 'recap'], ['15', 'december 14 , 2008', 'cincinnati bengals', '1:00', 'l 13 - 20', 'paul brown stadium', '7 - 7', 'recap'], ['16', 'december 21 , 2008', 'philadelphia eagles', '4:15', 'w 10 - 3', 'fedex field', '8 - 7', 'recap'], ['17', 'december 28 , 2008', 'san francisco 49ers', '4:15', 'l 24 - 27', 'candlestick park', '8 - 8', 'recap']]

bleeding time

https://en.wikipedia.org/wiki/Bleeding_time

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-221653-1.html.csv

unique

the only platelet count that could be either decreased or unaffected when discussing bleeding time is in bernard-soulier syndrome .

{'scope': 'all', 'row': '14', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'decreased or unaffected', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'platelet count', 'decreased or unaffected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose platelet count record fuzzily matches to decreased or unaffected .', 'tostr': 'filter_eq { all_rows ; platelet count ; decreased or unaffected }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; platelet count ; decreased or unaffected } }', 'tointer': 'select the rows whose platelet count record fuzzily matches to decreased or unaffected . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'platelet count', 'decreased or unaffected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose platelet count record fuzzily matches to decreased or unaffected .', 'tostr': 'filter_eq { all_rows ; platelet count ; decreased or unaffected }'}, 'condition'], 'result': 'bernard - soulier syndrome', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; platelet count ; decreased or unaffected } ; condition }'}, 'bernard - soulier syndrome'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; platelet count ; decreased or unaffected } ; condition } ; bernard - soulier syndrome }', 'tointer': 'the condition record of this unqiue row is bernard - soulier syndrome .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; platelet count ; decreased or unaffected } } ; eq { hop { filter_eq { all_rows ; platelet count ; decreased or unaffected } ; condition } ; bernard - soulier syndrome } } = true', 'tointer': 'select the rows whose platelet count record fuzzily matches to decreased or unaffected . there is only one such row in the table . the condition record of this unqiue row is bernard - soulier syndrome .'}

and { only { filter_eq { all_rows ; platelet count ; decreased or unaffected } } ; eq { hop { filter_eq { all_rows ; platelet count ; decreased or unaffected } ; condition } ; bernard - soulier syndrome } } = true

select the rows whose platelet count record fuzzily matches to decreased or unaffected . there is only one such row in the table . the condition record of this unqiue row is bernard - soulier syndrome .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'platelet count_7': 7, 'decreased or unaffected_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'condition_9': 9, 'bernard - soulier syndrome_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'platelet count_7': 'platelet count', 'decreased or unaffected_8': 'decreased or unaffected', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'condition_9': 'condition', 'bernard - soulier syndrome_10': 'bernard - soulier syndrome'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'platelet count_7': [0], 'decreased or unaffected_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'condition_9': [2], 'bernard - soulier syndrome_10': [3]}

['condition', 'prothrombin time', 'partial thromboplastin time', 'bleeding time', 'platelet count']

[['vitamin k deficiency or warfarin', 'prolonged', 'normal or mildly prolonged', 'unaffected', 'unaffected'], ['disseminated intravascular coagulation', 'prolonged', 'prolonged', 'prolonged', 'decreased'], ['von willebrand disease', 'unaffected', 'prolonged or unaffected', 'prolonged', 'unaffected'], ['hemophilia', 'unaffected', 'prolonged', 'unaffected', 'unaffected'], ['aspirin', 'unaffected', 'unaffected', 'prolonged', 'unaffected'], ['thrombocytopenia', 'unaffected', 'unaffected', 'prolonged', 'decreased'], ['liver failure , early', 'prolonged', 'unaffected', 'unaffected', 'unaffected'], ['liver failure , end - stage', 'prolonged', 'prolonged', 'prolonged', 'decreased'], ['uremia', 'unaffected', 'unaffected', 'prolonged', 'unaffected'], ['congenital afibrinogenemia', 'prolonged', 'prolonged', 'prolonged', 'unaffected'], ['factor v deficiency', 'prolonged', 'prolonged', 'unaffected', 'unaffected'], ['factor x deficiency as seen in amyloid purpura', 'prolonged', 'prolonged', 'unaffected', 'unaffected'], ["glanzmann 's thrombasthenia", 'unaffected', 'unaffected', 'prolonged', 'unaffected'], ['bernard - soulier syndrome', 'unaffected', 'unaffected', 'prolonged', 'decreased or unaffected'], ['factor xii deficiency', 'unaffected', 'prolonged', 'unaffected', 'unaffected']]

thomaz bellucci

https://en.wikipedia.org/wiki/Thomaz_Bellucci

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17436425-8.html.csv

ordinal

of the tournaments thomaz bellucci played in , the 2nd earliest was in ecuador .

{'row': '2', 'col': '2', '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', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 2 }'}, 'tournament'], 'result': 'cuenca , ecuador', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 2 } ; tournament }'}, 'cuenca , ecuador'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 2 } ; tournament } ; cuenca , ecuador } = true', 'tointer': 'select the row whose date record of all rows is 2nd minimum . the tournament record of this row is cuenca , ecuador .'}

eq { hop { nth_argmin { all_rows ; date ; 2 } ; tournament } ; cuenca , ecuador } = true

select the row whose date record of all rows is 2nd minimum . the tournament record of this row is cuenca , ecuador .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'tournament_7': 7, 'cuenca , ecuador_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '2_6': '2', 'tournament_7': 'tournament', 'cuenca , ecuador_8': 'cuenca , ecuador'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'tournament_7': [1], 'cuenca , ecuador_8': [2]}

['outcome', 'date', 'tournament', 'surface', 'opponent', 'score']

[['runner - up', '15 july 2007', 'bogotá , colombia', 'clay', 'carlos salamanca', '6 - 4 , 3 - 6 , 2 - 6'], ['runner - up', '22 july 2007', 'cuenca , ecuador', 'clay', 'leonardo mayer', '3 - 6 , 2 - 6'], ['winner', '2 march 2008', 'santiago , chile', 'clay', 'eduardo schwank', '6 - 4 , 7 - 6 ( 7 - 3 )'], ['winner', '14 april 2008', 'florianapolis , brazil', 'clay', 'franco ferreiro', '4 - 6 , 6 - 4 , 6 - 2'], ['winner', '4 may 2008', 'tunis , tunisia', 'clay', 'dušan vemić', '6 - 2 , 6 - 4'], ['winner', '11 may 2008', 'rabat , morocco', 'clay', 'martín vassallo argüello', '6 - 2 , 6 - 2'], ['winner', '19 july 2009', 'rimini , italy', 'clay', 'juan pablo brzezicki', '3 - 6 , 6 - 3 , 6 - 1'], ['winner', '1 november 2009', 'são paulo , brazil', 'clay', 'nicolás lapentti', '6 - 4 , 6 - 4'], ['runner - up', '30 october 2010', 'são paulo , brazil', 'clay', 'marcos daniel', '1 - 6 , 6 - 3 , 3 - 6'], ['winner', '7 july 2012', 'braunschweig , germany', 'clay', 'tobias kamke', '7 - 6 ( 7 - 4 ) , 6 - 3'], ['winner', '3 november 2013', 'montevideo , uruguay', 'clay', 'diego sebastián schwartzman', '6 - 4 , 6 - 4']]

1990 - 91 seattle supersonics season

https://en.wikipedia.org/wiki/1990%E2%80%9391_Seattle_SuperSonics_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17382360-4.html.csv

count

in the 1990-91 seattle supersonics season , when the supersonics won , on there were three games where g payton had the high assists .

{'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'g payton', 'result': '3', 'col': '7', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'w'}}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'w'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; score ; w }', 'tointer': 'select the rows whose score record fuzzily matches to w .'}, 'high assists', 'g payton'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high assists record fuzzily matches to g payton .', 'tostr': 'filter_eq { filter_eq { all_rows ; score ; w } ; high assists ; g payton }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; score ; w } ; high assists ; g payton } }', 'tointer': 'select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high assists record fuzzily matches to g payton . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; score ; w } ; high assists ; g payton } } ; 3 } = true', 'tointer': 'select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high assists record fuzzily matches to g payton . the number of such rows is 3 .'}

eq { count { filter_eq { filter_eq { all_rows ; score ; w } ; high assists ; g payton } } ; 3 } = true

select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high assists record fuzzily matches to g payton . the number of such rows is 3 .

4

4

{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'score_6': 6, 'w_7': 7, 'high assists_8': 8, 'g payton_9': 9, '3_10': 10}

{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'score_6': 'score', 'w_7': 'w', 'high assists_8': 'high assists', 'g payton_9': 'g payton', '3_10': '3'}

{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'score_6': [0], 'w_7': [0], 'high assists_8': [1], 'g payton_9': [1], '3_10': [3]}

['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']

[['1', 'november 3', 'houston rockets', 'w 118 - 106', 'x mcdaniel ( 24 )', 's kemp ( 10 )', 'x mcdaniel , s threatt ( 7 )', 'seattle center coliseum 13922', '1 - 0'], ['2', 'november 6', 'detroit pistons', 'w 100 - 92', 'x mcdaniel ( 24 )', 's kemp ( 13 )', 'g payton ( 6 )', 'seattle center coliseum 13078', '2 - 0'], ['3', 'november 9', 'denver nuggets', 'w 135 - 129', 'x mcdaniel ( 27 )', 'd mckey ( 14 )', 'g payton ( 10 )', 'mcnichols sports arena 10571', '3 - 0'], ['4', 'november 10', 'golden state warriors', 'l 100 - 117', 'x mcdaniel ( 26 )', 'x mcdaniel , d mckey ( 9 )', 'g payton ( 9 )', 'tacoma dome 13130', '3 - 1'], ['5', 'november 13', 'new york knicks', 'l 100 - 116 ( ot )', 's threatt ( 24 )', 'x mcdaniel ( 10 )', 'g payton ( 7 )', 'seattle center coliseum 12352', '3 - 2'], ['6', 'november 17', 'chicago bulls', 'l 95 - 116', 'x mcdaniel ( 17 )', 'm cage ( 7 )', 'g payton ( 5 )', 'seattle center coliseum 14692', '3 - 3'], ['7', 'november 18', 'los angeles clippers', 'l 65 - 78', 's kemp ( 11 )', 'm cage ( 10 )', 'g payton ( 5 )', 'los angeles memorial sports arena 10980', '3 - 4'], ['8', 'november 20', 'new jersey nets', 'w 105 - 88', 'x mcdaniel ( 35 )', 's kemp ( 8 )', 'g payton ( 9 )', 'seattle center coliseum 10466', '4 - 4'], ['9', 'november 23', 'utah jazz', 'l 96 - 97', 'x mcdaniel ( 33 )', 'd mckey ( 11 )', 's threatt ( 12 )', 'salt palace 12616', '4 - 5'], ['10', 'november 27', 'san antonio spurs', 'l 111 - 124', 'q dailey ( 29 )', 'm cage ( 8 )', 'g payton ( 8 )', 'seattle center coliseum 13293', '4 - 6'], ['11', 'november 29', 'phoenix', 'l 110 - 128', 'd mckey ( 26 )', 's kemp ( 11 )', 'g payton ( 6 )', 'arizona veterans memorial coliseum 14487', '4 - 7']]

euroleague 2007 - 08 individual statistics

https://en.wikipedia.org/wiki/Euroleague_2007%E2%80%9308_Individual_Statistics

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16050349-4.html.csv

count

two of the top scoring players in euroleague 2007 - 08 were on the team lietuvos rytas vilnius .

{'scope': 'all', 'criterion': 'equal', 'value': 'lietuvos rytas vilnius', 'result': '2', 'col': '3', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'lietuvos rytas vilnius'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to lietuvos rytas vilnius .', 'tostr': 'filter_eq { all_rows ; team ; lietuvos rytas vilnius }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; team ; lietuvos rytas vilnius } }', 'tointer': 'select the rows whose team record fuzzily matches to lietuvos rytas vilnius . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; team ; lietuvos rytas vilnius } } ; 2 } = true', 'tointer': 'select the rows whose team record fuzzily matches to lietuvos rytas vilnius . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; team ; lietuvos rytas vilnius } } ; 2 } = true

select the rows whose team record fuzzily matches to lietuvos rytas vilnius . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'lietuvos rytas vilnius_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'lietuvos rytas vilnius_6': 'lietuvos rytas vilnius', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'lietuvos rytas vilnius_6': [0], '2_7': [2]}

['rank', 'name', 'team', 'games', 'points']

[['1', 'will solomon', 'fenerbahçe', '6', '123'], ['2', 'jeremiah massey', 'aris thessaloniki', '6', '120'], ['3', 'lynn greer', 'olympiacos', '6', '113'], ['4', 'hollis price', 'lietuvos rytas vilnius', '6', '101'], ['4', 'kenan bajramović', 'lietuvos rytas vilnius', '6', '101']]

zakspeed

https://en.wikipedia.org/wiki/Zakspeed

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1219581-1.html.csv

unique

1989 was the only year that the zakspeed motor racing team used a yamaha engine .

{'scope': 'all', 'row': '5', 'col': '3', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'yamaha', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine ( s )', 'yamaha'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine ( s ) record fuzzily matches to yamaha .', 'tostr': 'filter_eq { all_rows ; engine ( s ) ; yamaha }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; engine ( s ) ; yamaha } }', 'tointer': 'select the rows whose engine ( s ) record fuzzily matches to yamaha . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine ( s )', 'yamaha'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine ( s ) record fuzzily matches to yamaha .', 'tostr': 'filter_eq { all_rows ; engine ( s ) ; yamaha }'}, 'year'], 'result': '1989', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; engine ( s ) ; yamaha } ; year }'}, '1989'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; engine ( s ) ; yamaha } ; year } ; 1989 }', 'tointer': 'the year record of this unqiue row is 1989 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; engine ( s ) ; yamaha } } ; eq { hop { filter_eq { all_rows ; engine ( s ) ; yamaha } ; year } ; 1989 } } = true', 'tointer': 'select the rows whose engine ( s ) record fuzzily matches to yamaha . there is only one such row in the table . the year record of this unqiue row is 1989 .'}

and { only { filter_eq { all_rows ; engine ( s ) ; yamaha } } ; eq { hop { filter_eq { all_rows ; engine ( s ) ; yamaha } ; year } ; 1989 } } = true

select the rows whose engine ( s ) record fuzzily matches to yamaha . there is only one such row in the table . the year record of this unqiue row is 1989 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'engine (s)_7': 7, 'yamaha_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1989_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'engine (s)_7': 'engine ( s )', 'yamaha_8': 'yamaha', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1989_10': '1989'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'engine (s)_7': [0], 'yamaha_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1989_10': [3]}

['year', 'chassis', 'engine ( s )', 'tyres', 'points']

[['1985', 'zakspeed 841', 'zakspeed s4 t / c', 'g', '0'], ['1986', 'zakspeed 861', 'zakspeed s4 t / c', 'g', '0'], ['1987', 'zakspeed 861 zakspeed 871', 'zakspeed s4 t / c', 'g', '2'], ['1988', 'zakspeed 881', 'zakspeed s4 t / c', 'g', '0'], ['1989', 'zakspeed 891', 'yamaha v8', 'p', '0']]

daniel gimeno - traver

https://en.wikipedia.org/wiki/Daniel_Gimeno-Traver

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16965329-5.html.csv

majority

most of daniel gimeno - traver 's matches have been played on a clay surface .

{'scope': 'all', 'col': '3', '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]}

['date', 'tournament', 'surface', 'opponent', 'score']

[['5 september 2005', 'brasov', 'clay', 'daniel elsner', '5 - 7 , 2 - 6'], ['5 november 2007', 'guayaquil', 'clay', 'nicolás lapentti', '3 - 6 , 7 - 6 ( 6 ) , 5 - 7'], ['10 march 2008', 'tanger', 'clay', 'marcel granollers', '4 - 6 , 4 - 6'], ['15 september 2008', 'banja luka', 'clay', 'ilija bozoljac', '4 - 6 , 4 - 6'], ['12 october 2009', 'asunción', 'clay', 'ramón delgado', '6 - 7 ( 2 - 7 ) , 6 - 1 , 3 - 6'], ['5 july 2010', 'san benedetto', 'clay', 'carlos berlocq', '3 - 6 , 6 - 4 , 4 - 6'], ['2 october 2011', 'madrid', 'clay', 'jérémy chardy', '1 - 6 , 7 - 5 , 6 - 7 ( 3 - 7 )'], ['12 august 2012', 'cordenos', 'clay', 'paolo lorenzi', '6 - 7 ( 5 - 7 ) , 3 - 6']]

new year live

https://en.wikipedia.org/wiki/New_Year_Live

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24212608-1.html.csv

count

for the show new years live , jake humphrey was the bbc one presenter two times .

{'scope': 'all', 'criterion': 'equal', 'value': 'jake humphrey', 'result': '2', 'col': '3', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'bbc one presenter ( s )', 'jake humphrey'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bbc one presenter ( s ) record fuzzily matches to jake humphrey .', 'tostr': 'filter_eq { all_rows ; bbc one presenter ( s ) ; jake humphrey }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; bbc one presenter ( s ) ; jake humphrey } }', 'tointer': 'select the rows whose bbc one presenter ( s ) record fuzzily matches to jake humphrey . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; bbc one presenter ( s ) ; jake humphrey } } ; 2 } = true', 'tointer': 'select the rows whose bbc one presenter ( s ) record fuzzily matches to jake humphrey . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; bbc one presenter ( s ) ; jake humphrey } } ; 2 } = true

select the rows whose bbc one presenter ( s ) record fuzzily matches to jake humphrey . 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, 'bbc one presenter (s)_5': 5, 'jake humphrey_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', 'bbc one presenter (s)_5': 'bbc one presenter ( s )', 'jake humphrey_6': 'jake humphrey', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'bbc one presenter (s)_5': [0], 'jake humphrey_6': [0], '2_7': [2]}

['episode', 'broadcast date', 'bbc one presenter ( s )', 'starring', 'radio 1 presenter', 'viewers ( millions )']

[['1', '2005', 'clare balding', 'doug segal', 'n / a', '6.43'], ['2', '2006', 'myleene klass', 'gethin jones , natasha kaplinsky & alesha dixon', 'n / a', '6.06'], ['3', '2007', 'myleene klass', 'gethin jones , natasha kaplinsky & nick knowles', 'n / a', '5.35'], ['5', '2009', 'myleene klass', 'n / a', 'nihal', '7.65'], ['6', '2010', 'jake humphrey', 'n / a', 'nihal', '9.37'], ['7', '2011', 'jake humphrey', 'n / a', 'nihal', '10.67'], ['8', '2012', 'gabby logan', 'n / a', 'nihal', '9.73']]

paul caligiuri

https://en.wikipedia.org/wiki/Paul_Caligiuri

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1036039-1.html.csv

ordinal

of the competitions that paul caligiuri participated in , the 2nd earliest was in trinidad and tobago .

{'row': '2', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 2 }'}, 'venue'], 'result': 'port of spain , trinidad and tobago', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 2 } ; venue }'}, 'port of spain , trinidad and tobago'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 2 } ; venue } ; port of spain , trinidad and tobago } = true', 'tointer': 'select the row whose date record of all rows is 2nd minimum . the venue record of this row is port of spain , trinidad and tobago .'}

eq { hop { nth_argmin { all_rows ; date ; 2 } ; venue } ; port of spain , trinidad and tobago } = true

select the row whose date record of all rows is 2nd minimum . the venue record of this row is port of spain , trinidad and tobago .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'venue_7': 7, 'port of spain , trinidad and tobago_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '2_6': '2', 'venue_7': 'venue', 'port of spain , trinidad and tobago_8': 'port of spain , trinidad and tobago'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'venue_7': [1], 'port of spain , trinidad and tobago_8': [2]}

['date', 'venue', 'score', 'result', 'competition']

[['may 19 , 1985', 'torrance , california', '1 - 0', '1 - 0', '1986 world cup qualifying'], ['november 19 , 1989', 'port of spain , trinidad and tobago', '1 - 0', '1 - 0', '1990 world cup qualifying'], ['march 10 , 1990', 'tampa , florida', '1 - 0', '2 - 1', 'friendly'], ['june 10 , 1990', 'florence , italy', '1 - 3', '1 - 5', '1990 world cup'], ['may 28 , 1995', 'tampa , florida', '1 - 1', '1 - 2', 'friendly']]

2007 - 08 boston celtics season

https://en.wikipedia.org/wiki/2007%E2%80%9308_Boston_Celtics_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11959669-6.html.csv

count

during the 2007-08 boston celtics season , rondo had the high assists 6 times .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'rondo', 'result': '6', 'col': '7', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'rondo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high assists record fuzzily matches to rondo .', 'tostr': 'filter_eq { all_rows ; high assists ; rondo }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; high assists ; rondo } }', 'tointer': 'select the rows whose high assists record fuzzily matches to rondo . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; high assists ; rondo } } ; 6 } = true', 'tointer': 'select the rows whose high assists record fuzzily matches to rondo . the number of such rows is 6 .'}

eq { count { filter_eq { all_rows ; high assists ; rondo } } ; 6 } = true

select the rows whose high assists record fuzzily matches to rondo . the number of such rows is 6 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high assists_5': 5, 'rondo_6': 6, '6_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high assists_5': 'high assists', 'rondo_6': 'rondo', '6_7': '6'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high assists_5': [0], 'rondo_6': [0], '6_7': [2]}

['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']

[['45', 'february 5', 'cleveland', '113 - 114', 'allen ( 24 )', 'rondo ( 7 )', 'allen ( 5 )', 'quicken loans arena 20562', '36 - 9'], ['46', 'february 6', 'la clippers', '111 - 100', 'rondo ( 24 )', 'powe ( 10 )', 'rondo ( 8 )', 'td banknorth garden 18624', '37 - 9'], ['47', 'february 8', 'minnesota', '88 - 86', 'pierce ( 18 )', 'powe ( 8 )', 'pierce ( 6 )', 'target center 19511', '38 - 9'], ['48', 'february 10', 'san antonio', '98 - 90', 'pierce ( 35 )', 'rondo ( 11 )', 'rondo ( 12 )', 'td banknorth garden 18624', '39 - 9'], ['49', 'february 12', 'indiana', '104 - 97', 'pierce ( 28 )', 'pierce ( 12 )', 'rondo ( 7 )', 'conseco fieldhouse 13603', '40 - 9'], ['50', 'february 13', 'new york', '111 - 103', 'pierce ( 24 )', 'posey ( 11 )', 'pierce ( 7 )', 'td banknorth garden 18624', '41 - 9'], ['51', 'february 19', 'denver', '118 - 124', 'pierce ( 24 )', 'powe ( 11 )', 'pierce ( 7 )', 'pepsi center 19894', '41 - 10'], ['52', 'february 20', 'golden state', '117 - 119', 'allen ( 32 )', 'garnett ( 15 )', 'allen , rondo ( 6 )', 'oracle arena 20711', '41 - 11'], ['53', 'february 22', 'phoenix', '77 - 85', 'garnett ( 19 )', 'perkins , pierce ( 6 )', 'garnett ( 4 )', 'us airways center 18422', '41 - 12'], ['54', 'february 24', 'portland', '112 - 102', 'pierce ( 30 )', 'garnett , pierce ( 7 )', 'rondo ( 8 )', 'rose garden 20554', '42 - 12'], ['55', 'february 25', 'la clippers', '104 - 76', 'pierce , posey ( 17 )', 'perkins ( 9 )', 'allen ( 7 )', 'staples center 19328', '43 - 12'], ['56', 'february 27', 'cleveland', '92 - 87', 'allen ( 22 )', 'garnett ( 11 )', 'rondo ( 8 )', 'td banknorth garden 18624', '44 - 12']]

pablo andújar

https://en.wikipedia.org/wiki/Pablo_And%C3%BAjar

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16949333-3.html.csv

count

pablo andujar was the runner up in 3 of the matches in which he played .

{'scope': 'all', 'criterion': 'equal', 'value': 'runner - up', 'result': '3', 'col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'outcome', 'runner - up'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose outcome record fuzzily matches to runner - up .', 'tostr': 'filter_eq { all_rows ; outcome ; runner - up }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; outcome ; runner - up } }', 'tointer': 'select the rows whose outcome record fuzzily matches to runner - up . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; outcome ; runner - up } } ; 3 } = true', 'tointer': 'select the rows whose outcome record fuzzily matches to runner - up . the number of such rows is 3 .'}

eq { count { filter_eq { all_rows ; outcome ; runner - up } } ; 3 } = true

select the rows whose outcome record fuzzily matches to runner - up . 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, 'outcome_5': 5, 'runner - up_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', 'outcome_5': 'outcome', 'runner - up_6': 'runner - up', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'outcome_5': [0], 'runner - up_6': [0], '3_7': [2]}

['outcome', 'date', 'tournament', 'surface', 'opponent', 'score']

[['runner - up', 'september 26 , 2010', 'brd năstase ţiriac trophy , bucharest , romania', 'clay', 'juan ignacio chela', '5 - 7 , 1 - 6'], ['winner', 'april 10 , 2011', 'grand prix hassan ii , casablanca , morocco ( 1 )', 'clay', 'potito starace', '6 - 1 , 6 - 2'], ['runner - up', 'july 17 , 2011', 'mercedescup , stuttgart , germany', 'clay', 'juan carlos ferrero', '4 - 6 , 0 - 6'], ['runner - up', 'september 25 , 2011', 'brd năstase ţiriac trophy , bucharest , romania', 'clay', 'florian mayer', '3 - 6 , 1 - 6'], ['winner', 'april 15 , 2012', 'grand prix hassan ii , casablanca , morocco ( 2 )', 'clay', 'albert ramos', '6 - 1 , 7 - 6 ( 7 - 5 )']]

naval campaign of the war of the pacific

https://en.wikipedia.org/wiki/Naval_Campaign_of_the_War_of_the_Pacific

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23614702-1.html.csv

comparative

the warship blanco encalada had more horse power than the warship cochrane .

{'row_1': '1', 'row_2': '2', 'col': '3', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'warship', 'cochrane'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose warship record fuzzily matches to cochrane .', 'tostr': 'filter_eq { all_rows ; warship ; cochrane }'}, 'horse - power'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; warship ; cochrane } ; horse - power }', 'tointer': 'select the rows whose warship record fuzzily matches to cochrane . take the horse - power record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'warship', 'blanco encalada'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose warship record fuzzily matches to blanco encalada .', 'tostr': 'filter_eq { all_rows ; warship ; blanco encalada }'}, 'horse - power'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; warship ; blanco encalada } ; horse - power }', 'tointer': 'select the rows whose warship record fuzzily matches to blanco encalada . take the horse - power record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; warship ; cochrane } ; horse - power } ; hop { filter_eq { all_rows ; warship ; blanco encalada } ; horse - power } } = true', 'tointer': 'select the rows whose warship record fuzzily matches to cochrane . take the horse - power record of this row . select the rows whose warship record fuzzily matches to blanco encalada . take the horse - power record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; warship ; cochrane } ; horse - power } ; hop { filter_eq { all_rows ; warship ; blanco encalada } ; horse - power } } = true

select the rows whose warship record fuzzily matches to cochrane . take the horse - power record of this row . select the rows whose warship record fuzzily matches to blanco encalada . take the horse - power 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, 'warship_7': 7, 'cochrane_8': 8, 'horse - power_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'warship_11': 11, 'blanco encalada_12': 12, 'horse - power_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', 'warship_7': 'warship', 'cochrane_8': 'cochrane', 'horse - power_9': 'horse - power', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'warship_11': 'warship', 'blanco encalada_12': 'blanco encalada', 'horse - power_13': 'horse - power'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'warship_7': [0], 'cochrane_8': [0], 'horse - power_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'warship_11': [1], 'blanco encalada_12': [1], 'horse - power_13': [3]}

['warship', 'tons ( lton )', 'horse - power', 'speed ( knots )', 'armour ( inch )', 'main artillery', 'built year']

[['cochrane', '3560', '2000', '9 - 12 , 8', 'up to 9', '6x9 inch', '1874'], ['blanco encalada', '3560', '3000', '9 - 12 , 8', 'up to 9', '6x9 inch', '1874'], ['huascar', '1130', '1200', '10 - 11', '4 ½', '2x300 - pounders', '1865'], ['independencia', '2004', '1500', '12 - 13', '4 ½', '2x150 - pounders', '1865'], ['manco cápac', '1034', '320', '6', '10', '2x500 - pounders', '1864']]

johnny thomson

https://en.wikipedia.org/wiki/Johnny_Thomson

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1236178-1.html.csv

aggregation

the average qual time for driver johnny thomson was 141.562 .

{'scope': 'all', 'col': '3', 'type': 'average', 'result': '141.562', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'qual'], 'result': '141.562', 'ind': 0, 'tostr': 'avg { all_rows ; qual }'}, '141.562'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; qual } ; 141.562 } = true', 'tointer': 'the average of the qual record of all rows is 141.562 .'}

round_eq { avg { all_rows ; qual } ; 141.562 } = true

the average of the qual record of all rows is 141.562 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'qual_4': 4, '141.562_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'qual_4': 'qual', '141.562_5': '141.562'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'qual_4': [0], '141.562_5': [1]}

['year', 'start', 'qual', 'rank', 'finish', 'laps']

[['1953', '33', '135.262', '33', '32', '6'], ['1954', '4', '138.787', '12', '24', '165'], ['1955', '33', '134.113', '33', '4', '200'], ['1956', '18', '145.549', '2', '32', '22'], ['1957', '11', '143.529', '4', '12', '199'], ['1958', '22', '142.908', '20', '23', '52'], ['1959', '1', '145.908', '1', '3', '200'], ['1960', '17', '146.443', '3', '5', '200']]

washington redskins draft history

https://en.wikipedia.org/wiki/Washington_Redskins_draft_history

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17100961-32.html.csv

unique

carl palazzo is the only player that the washington redskins drafted from adams state college .

{'scope': 'all', 'row': '9', 'col': '6', 'col_other': '4', 'criterion': 'equal', 'value': 'adams state', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'adams state'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to adams state .', 'tostr': 'filter_eq { all_rows ; college ; adams state }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; college ; adams state } }', 'tointer': 'select the rows whose college record fuzzily matches to adams state . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'adams state'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to adams state .', 'tostr': 'filter_eq { all_rows ; college ; adams state }'}, 'name'], 'result': 'carl palazzo', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; college ; adams state } ; name }'}, 'carl palazzo'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; college ; adams state } ; name } ; carl palazzo }', 'tointer': 'the name record of this unqiue row is carl palazzo .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; college ; adams state } } ; eq { hop { filter_eq { all_rows ; college ; adams state } ; name } ; carl palazzo } } = true', 'tointer': 'select the rows whose college record fuzzily matches to adams state . there is only one such row in the table . the name record of this unqiue row is carl palazzo .'}

and { only { filter_eq { all_rows ; college ; adams state } } ; eq { hop { filter_eq { all_rows ; college ; adams state } ; name } ; carl palazzo } } = true

select the rows whose college record fuzzily matches to adams state . there is only one such row in the table . the name record of this unqiue row is carl palazzo .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'college_7': 7, 'adams state_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'carl palazzo_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'college_7': 'college', 'adams state_8': 'adams state', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'carl palazzo_10': 'carl palazzo'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'college_7': [0], 'adams state_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'carl palazzo_10': [3]}

['round', 'pick', 'overall', 'name', 'position', 'college']

[['1', '1', '1', 'ernie davis', 'rb', 'syracuse'], ['2', '1', '15', 'joe hernandez', 'wr', 'arizona'], ['3', '1', '29', 'bob mitinger', 'lb', 'penn state'], ['4', '1', '43', 'billy neighbors', 'g', 'alabama'], ['7', '1', '85', 'bert coan', 'hb', 'kansas'], ['8', '1', '99', 'ron hatcher', 'fb', 'michigan state'], ['9', '1', '113', 'dave viti', 'e', 'boston university'], ['10', '1', '127', 'john childress', 'g', 'arkansas'], ['11', '1', '141', 'carl palazzo', 'ot', 'adams state'], ['12', '1', '155', 'terry terrebonne', 'hb', 'tulane'], ['13', '1', '169', 'bill whisler', 'e', 'iowa'], ['14', '1', '183', 'jim costen', 'hb', 'south carolina'], ['15', '1', '197', 'len velia', 'ot', 'georgia'], ['16', '1', '211', 'tommy brooker', 'e', 'alabama'], ['17', '1', '225', 'allen miller', 'lb', 'ohio'], ['18', '1', '239', 'carl charon', 'db', 'michigan state'], ['19', '1', '253', 'claude crabb', 'db', 'colorado'], ['20', '1', '267', 'ed trancygier', 'qb', 'florida state']]

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/2-15186990-3.html.csv

count

in the chronology of fred astaire 's performances , the music by george gershwin was used 4 times .

{'scope': 'all', 'criterion': 'equal', 'value': 'george gershwin', 'result': '4', 'col': '8', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'music', 'george gershwin'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose music record fuzzily matches to george gershwin .', 'tostr': 'filter_eq { all_rows ; music ; george gershwin }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; music ; george gershwin } }', 'tointer': 'select the rows whose music record fuzzily matches to george gershwin . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; music ; george gershwin } } ; 4 } = true', 'tointer': 'select the rows whose music record fuzzily matches to george gershwin . the number of such rows is 4 .'}

eq { count { filter_eq { all_rows ; music ; george gershwin } } ; 4 } = true

select the rows whose music record fuzzily matches to george gershwin . 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, 'music_5': 5, 'george gershwin_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', 'music_5': 'music', 'george gershwin_6': 'george gershwin', '4_7': '4'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'music_5': [0], 'george gershwin_6': [0], '4_7': [2]}

['title', 'date', 'theatre', 'role', 'dance partner', 'director', 'lyrics', 'music']

[['the love letter', 'oct 4 1921', 'globe', 'richard kolner', 'adele astaire', 'edward royce', 'william lebaron', 'victor jacobi'], ['for goodness sake', 'feb 20 1922', 'lyric', 'teddy lawrence', 'adele astaire', 'priestley morrison', 'arthur jackson', 'william daly paul lannin'], ['the bunch and judy', 'nov 28 1922', 'globe', 'gerald lane', 'adele astaire', 'fred latham', 'anne caldwell', 'jerome kern'], ['stop flirting ( ( for goodness sake ) )', 'may 30 , 1923', 'shaftsbury queens strand', 'teddy lawrence', 'adele astaire', 'felix edwardes', 'arthur jackson', 'william daly paul lannin'], ['lady , be good', 'dec 1 1924', 'liberty', 'dick trevor', 'adele astaire', 'felix edwardes', 'ira gershwin', 'george gershwin'], ['lady , be good', 'apr 14 1926', 'empire', 'dick trevor', 'adele astaire', 'felix edwardes', 'ira gershwin', 'george gershwin'], ['funny face', 'nov 22 1927', 'alvin', 'jimmie reeves', 'adele astaire', 'edward macgregor', 'ira gershwin', 'george gershwin'], ['funny face', 'nov 8 1928', "prince 's theatre", 'jimmie reeves', 'adele astaire', 'felix edwardes', 'ira gershwin', 'george gershwin'], ['smiles', 'nov 18 1930', 'ziegfeld', 'bob hastings', 'adele astaire marilyn miller', 'william anthony mcguire', 'clifford grey harold adamson ring lardner', 'vincent youmans']]

galatasaray s.k. ( women 's volleyball )

https://en.wikipedia.org/wiki/Galatasaray_S.K._%28women%27s_volleyball%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18729577-2.html.csv

majority

most of the players from the galatasaray s.k. women 's volleyball team have a height under 190 .

{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '190', 'subset': None}

{'func': 'most_less', 'args': ['all_rows', 'height', '190'], 'result': True, 'ind': 0, 'tointer': 'for the height records of all rows , most of them are less than 190 .', 'tostr': 'most_less { all_rows ; height ; 190 } = true'}

most_less { all_rows ; height ; 190 } = true

for the height records of all rows , most of them are less than 190 .

1

1

{'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'height_3': 3, '190_4': 4}

{'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'height_3': 'height', '190_4': '190'}

{'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'height_3': [0], '190_4': [0]}

['shirt no', 'nationality', 'player', 'birth date', 'height', 'position']

[['1', 'turkey', 'ergül avcı', 'june 24 , 1987 ( age26 )', '190', 'middle blocker'], ['2', 'turkey', 'sinem barut', 'april 12 , 1986 ( age27 )', '186', 'middle blocker'], ['5', 'bulgaria', 'dobriana rabadzhieva', 'june 14 , 1991 ( age22 )', '190', 'outside hitter'], ['7', 'colombia', 'madelaynne montaño', 'january 6 , 1983 ( age31 )', '185', 'opposite hitter'], ['8', 'turkey', 'aslı kalaç', 'december 13 , 1995 ( age18 )', '183', 'middle blocker'], ['9', 'serbia', 'stefana veljković', 'january 9 , 1990 ( age24 )', '190', 'middle blocker'], ['10', 'japan', 'saori kimura', 'august 19 , 1986 ( age27 )', '185', 'wing - spiker'], ['11', 'turkey', 'gamze alikaya', 'june 27 , 1993 ( age20 )', '179', 'setter'], ['12', 'turkey', 'bihter dumanoğlu', 'december 13 , 1995 ( age18 )', '175', 'libero'], ['13', 'turkey', 'neriman özsoy', 'july 7 , 1988 ( age25 )', '188', 'outside hitter'], ['14', 'italy', 'eleonora lo bianco', 'december 22 , 1979 ( age34 )', '172', 'setter'], ['17', 'turkey', 'nursevil aydınlar', 'december 13 , 1995 ( age18 )', '190', 'setter'], ['18', 'turkey', 'ezgi arslan', 'march 23 , 1992 ( age21 )', '186', 'outside hitter'], ['19', 'turkey', 'nihan yeldan', 'february 7 , 1982 ( age31 )', '172', 'libero']]

1991 - 92 in argentine football

https://en.wikipedia.org/wiki/1991%E2%80%9392_in_Argentine_football

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14390413-1.html.csv

majority

most of the teams which participated in the 1991 - 92 argentine football season games each played 114 matches .

{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': '114', 'subset': None}

{'func': 'most_eq', 'args': ['all_rows', 'played', '114'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , most of them are equal to 114 .', 'tostr': 'most_eq { all_rows ; played ; 114 } = true'}

most_eq { all_rows ; played ; 114 } = true

for the played records of all rows , most of them are equal to 114 .

1

1

{'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '114_4': 4}

{'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '114_4': '114'}

{'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '114_4': [0]}

['team', 'average', 'points', 'played', '1989 - 90', '1990 - 91', '1991 - 1992']

[['river plate', '1.342', '153', '114', '53', '45', '55'], ['boca juniors', '1.263', '144', '114', '43', '51', '50'], ['vélez sársfield', '1.184', '135', '114', '42', '45', '48'], ["newell 's old boys", '1.123', '128', '114', '36', '48', '44'], ['independiente', '1.070', '122', '114', '46', '40', '36'], ['racing club', '1.035', '118', '114', '39', '40', '39'], ['huracán', '1.026', '78', '76', 'n / a', '40', '38'], ['rosario central', '1.018', '116', '114', '43', '39', '34'], ['ferro carril oeste', '1.000', '114', '114', '39', '38', '37'], ['san lorenzo', '1.000', '114', '114', '35', '45', '34'], ['gimnasia de la plata', '0.991', '113', '114', '39', '33', '41'], ['platense', '0.991', '113', '114', '36', '35', '42'], ['argentinos juniors', '0.956', '109', '114', '38', '36', '35'], ['deportivo mandiyú', '0.939', '107', '114', '36', '38', '33'], ['belgrano de córdoba', '0.921', '35', '38', 'n / a', 'n / a', '35'], ['deportivo español', '0.912', '104', '114', '31', '28', '45'], ['estudiantes de la plata', '0.895', '102', '114', '34', '39', '29'], ['talleres de córdoba', '0.895', '102', '114', '36', '29', '37'], ['unión de santa fe', '0.825', '94', '114', '36', '31', '27']]

euroleague 2007 - 08 individual statistics

https://en.wikipedia.org/wiki/Euroleague_2007%E2%80%9308_Individual_Statistics

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16050349-2.html.csv

majority

all of the top players in euroleague 2007 - 08 had 100 or more rebounds .

{'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': '100', 'subset': None}

{'func': 'all_greater_eq', 'args': ['all_rows', 'rebounds', '100'], 'result': True, 'ind': 0, 'tointer': 'for the rebounds records of all rows , all of them are greater than or equal to 100 .', 'tostr': 'all_greater_eq { all_rows ; rebounds ; 100 } = true'}

all_greater_eq { all_rows ; rebounds ; 100 } = true

for the rebounds records of all rows , all of them are greater than or equal to 100 .

1

1

{'all_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'rebounds_3': 3, '100_4': 4}

{'all_greater_eq_0': 'all_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'rebounds_3': 'rebounds', '100_4': '100'}

{'all_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'rebounds_3': [0], '100_4': [0]}

['rank', 'name', 'team', 'games', 'rebounds']

[['1', 'travis watson', 'armani jeans milano', '14', '136'], ['2', 'mirsad türkcan', 'fenerbahçe', '11', '102'], ['3', 'jeremiah massey', 'aris thessaloniki', '14', '113'], ['4', 'nikola peković', 'partizan belgrade', '14', '112'], ['5', 'felipe reyes', 'real madrid', '13', '100']]

geography of the european union

https://en.wikipedia.org/wiki/Geography_of_the_European_Union

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1653499-1.html.csv

comparative

barcelona , spain has a higher population in the metro area than athens , greece .

{'row_1': '6', 'row_2': '10', 'col': '7', 'col_other': '7', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'population metro area in millions', '5.3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose population metro area in millions record fuzzily matches to 5.3 .', 'tostr': 'filter_eq { all_rows ; population metro area in millions ; 5.3 }'}, 'population metro area in millions'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; population metro area in millions ; 5.3 } ; population metro area in millions }', 'tointer': 'select the rows whose population metro area in millions record fuzzily matches to 5.3 . take the population metro area in millions record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'population metro area in millions', '3.9'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose population metro area in millions record fuzzily matches to 3.9 .', 'tostr': 'filter_eq { all_rows ; population metro area in millions ; 3.9 }'}, 'population metro area in millions'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; population metro area in millions ; 3.9 } ; population metro area in millions }', 'tointer': 'select the rows whose population metro area in millions record fuzzily matches to 3.9 . take the population metro area in millions record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; population metro area in millions ; 5.3 } ; population metro area in millions } ; hop { filter_eq { all_rows ; population metro area in millions ; 3.9 } ; population metro area in millions } } = true', 'tointer': 'select the rows whose population metro area in millions record fuzzily matches to 5.3 . take the population metro area in millions record of this row . select the rows whose population metro area in millions record fuzzily matches to 3.9 . take the population metro area in millions record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; population metro area in millions ; 5.3 } ; population metro area in millions } ; hop { filter_eq { all_rows ; population metro area in millions ; 3.9 } ; population metro area in millions } } = true

select the rows whose population metro area in millions record fuzzily matches to 5.3 . take the population metro area in millions record of this row . select the rows whose population metro area in millions record fuzzily matches to 3.9 . take the population metro area in millions 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, 'population metro area in millions_7': 7, '5.3_8': 8, 'population metro area in millions_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'population metro area in millions_11': 11, '3.9_12': 12, 'population metro area in millions_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', 'population metro area in millions_7': 'population metro area in millions', '5.3_8': '5.3', 'population metro area in millions_9': 'population metro area in millions', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'population metro area in millions_11': 'population metro area in millions', '3.9_12': '3.9', 'population metro area in millions_13': 'population metro area in millions'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'population metro area in millions_7': [0], '5.3_8': [0], 'population metro area in millions_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'population metro area in millions_11': [1], '3.9_12': [1], 'population metro area in millions_13': [3]}

['city proper', 'population city limits in millions', 'density per km square', 'urban area', 'population urban area in millions', 'metro area', 'population metro area in millions']

[['london , uk', '7.5', '4761', 'paris , france', '10.1', 'london , uk', '12 - 14'], ['berlin , germany', '3.4', '3815', 'london , uk', '8.5', 'paris , france', '11.7'], ['madrid , spain', '3.1', '1985', 'madrid , spain', '5.5', 'rhine - ruhr , germany', '10.2'], ['rome , italy', '2.7', '5198', 'ruhr , germany', '5.3', 'randstad , netherlands', '7.0'], ['paris , france', '2.2', '24672', 'barcelona , spain', '4.5', 'madrid , spain', '5.8'], ['bucharest , romania', '1.9', '9131', 'milan , italy', '3.8', 'barcelona , spain', '5.3'], ['hamburg , germany', '1.8', '2310', 'berlin , germany', '3.7', 'milan , italy', '4.3'], ['warsaw , poland', '1.7', '3258', 'rotterdam - the hague , netherlands', '3.3', 'berlin , germany', '4.3'], ['budapest , hungary', '1 , 7', '3570', 'athens , greece', '3.2', 'frankfurt rhine - main , germany', '4.1'], ['vienna , austria', '1.7', '3931', 'naples , italy', '2.9', 'athens , greece', '3.9']]

claudio suárez

https://en.wikipedia.org/wiki/Claudio_Su%C3%A1rez

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1007636-2.html.csv

majority

most of claudio suárez ' competitions were in the category of friendly competitions .

{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'friendly', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': True, 'ind': 0, 'tointer': 'for the competition records of all rows , most of them fuzzily match to friendly .', 'tostr': 'most_eq { all_rows ; competition ; friendly } = true'}

most_eq { all_rows ; competition ; friendly } = true

for the competition records of all rows , most of them fuzzily match to friendly .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, 'friendly_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', 'friendly_4': 'friendly'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], 'friendly_4': [0]}

['goal', 'date', 'score', 'result', 'competition']

[['1', 'november 8 , 1992', '2 - 0', '4 - 0', '1994 fifa world cup qualification'], ['2', 'november 22 , 1992', '2 - 0', '4 - 0', '1994 fifa world cup qualification'], ['3', 'december 14 , 1994', '3 - 1', '5 - 1', 'friendly'], ['4', 'october 11 , 1995', '1 - 1', '2 - 1', 'friendly'], ['5', 'january 31 , 2001', '1 - 0', '2 - 3', 'friendly'], ['6', 'may 1 , 2001', '1 - 0', '3 - 3', 'friendly']]

list of royal pains episodes

https://en.wikipedia.org/wiki/List_of_Royal_Pains_episodes

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23117208-3.html.csv

unique

only one episode of royal pains had less than 4 million viewers .

{'scope': 'all', 'row': '14', 'col': '8', 'col_other': 'n/a', 'criterion': 'less_than', 'value': '4 million', 'subset': None}

{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'viewers ( millions )', '4 million'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose viewers ( millions ) record is less than 4 million .', 'tostr': 'filter_less { all_rows ; viewers ( millions ) ; 4 million }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; viewers ( millions ) ; 4 million } } = true', 'tointer': 'select the rows whose viewers ( millions ) record is less than 4 million . there is only one such row in the table .'}

only { filter_less { all_rows ; viewers ( millions ) ; 4 million } } = true

select the rows whose viewers ( millions ) record is less than 4 million . there is only one such row in the table .

2

2

{'only_1': 1, 'result_2': 2, 'filter_less_0': 0, 'all_rows_3': 3, 'viewers (millions)_4': 4, '4 million_5': 5}

{'only_1': 'only', 'result_2': 'true', 'filter_less_0': 'filter_less', 'all_rows_3': 'all_rows', 'viewers (millions)_4': 'viewers ( millions )', '4 million_5': '4 million'}

{'only_1': [2], 'result_2': [], 'filter_less_0': [1], 'all_rows_3': [0], 'viewers (millions)_4': [0], '4 million_5': [0]}

['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'prod code', 'viewers ( millions )']

[['13', '1', 'spasticity', 'constantine makris', 'andrew lenchewski', 'june 3 , 2010', 'rp201', '5.84'], ['14', '2', 'lovesick', 'allison liddi - brown', 'michael rauch', 'june 10 , 2010', 'rp202', '5.60'], ['15', '3', 'keeping the faith', 'dennis smith', 'jack bernstein & michael rauch', 'june 17 , 2010', 'rp203', '5.51'], ['16', '4', 'medusa', 'matthew penn', 'andrew lenchewski & constance m burge', 'june 24 , 2010', 'rp204', '5.30'], ['17', '5', 'mano a mano', 'matthew penn', 'carol flint & jon sherman', 'july 1 , 2010', 'rp205', '5.32'], ['18', '6', 'in vino veritas', 'michael w watkins', 'jessica ball', 'july 15 , 2010', 'rp206', '5.20'], ['19', '7', "comfort 's overrated", 'ed fraiman', 'constance m burge', 'july 22 , 2010', 'rp207', '5.28'], ['20', '8', 'the hankover', 'jay chandrasekhar', 'carol flint & jon sherman', 'july 29 , 2010', 'rp208', '5.01'], ['21', '9', 'frenemies', 'wendey stanzler', 'jack bernstein', 'august 5 , 2010', 'rp209', '5.53'], ['22', '10', 'whole lotto love', 'tawnia mckiernan', 'michael rauch & jessica ball', 'august 12 , 2010', 'rp210', '5.39'], ['23', '11', 'big whoop', 'michael w watkins', 'michael rauch & contance m burge', 'august 19 , 2010', 'rp211', '5.27'], ['24', '12', 'open up your yenta mouth and say ah', 'ken whittingham', 'andrew lenchewski', 'august 26 , 2010', 'rp212', '6.08'], ['25', '13', 'mulligan', 'michael rauch', 'michael rauch & jon sherman', 'january 20 , 2011', 'rp213', '4.43'], ['28', '16', 'astraphobia', 'ed fraiman', 'andrew lenchewski & stuart feldman', 'february 10 , 2011', 'rp216', '3.86']]

list of public sector undertakings in india

https://en.wikipedia.org/wiki/List_of_public_sector_undertakings_in_India

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15221362-8.html.csv

ordinal

the second public sector in india to be incorporated was the airline allied services ltd .

{'row': '4', 'col': '3', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'incorporated', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; incorporated ; 2 }'}, 'company'], 'result': 'airline allied services ltd', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; incorporated ; 2 } ; company }'}, 'airline allied services ltd'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; incorporated ; 2 } ; company } ; airline allied services ltd } = true', 'tointer': 'select the row whose incorporated record of all rows is 2nd minimum . the company record of this row is airline allied services ltd .'}

eq { hop { nth_argmin { all_rows ; incorporated ; 2 } ; company } ; airline allied services ltd } = true

select the row whose incorporated record of all rows is 2nd minimum . the company record of this row is airline allied services ltd .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'incorporated_5': 5, '2_6': 6, 'company_7': 7, 'airline allied services ltd_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', 'incorporated_5': 'incorporated', '2_6': '2', 'company_7': 'company', 'airline allied services ltd_8': 'airline allied services ltd'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'incorporated_5': [0], '2_6': [0], 'company_7': [1], 'airline allied services ltd_8': [2]}

['sno', 'company', 'incorporated', 'ministry', 'sector']

[['1', 'air india air transport services ltd', '2003', 'ministry of civil aviation', 'services'], ['2', 'air india charters', '1972', 'ministry of civil aviation', 'services'], ['3', 'air india engineering services ltd', '2006', 'ministry of civil aviation', 'enterprises under construction'], ['4', 'airline allied services ltd', '1983', 'ministry of civil aviation', 'services'], ['5', 'airports authority of india ltd', '1996', 'ministry of civil aviation', 'services']]

toronto raptors all - time roster

https://en.wikipedia.org/wiki/Toronto_Raptors_all-time_roster

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10015132-7.html.csv

count

three of the players on the toronto raptors are in the position of forward , at least part of the time .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'forward', 'result': '3', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'forward'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to forward .', 'tostr': 'filter_eq { all_rows ; position ; forward }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; forward } }', 'tointer': 'select the rows whose position record fuzzily matches to forward . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; forward } } ; 3 } = true', 'tointer': 'select the rows whose position record fuzzily matches to forward . the number of such rows is 3 .'}

eq { count { filter_eq { all_rows ; position ; forward } } ; 3 } = true

select the rows whose position record fuzzily matches to forward . 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, 'position_5': 5, 'forward_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', 'position_5': 'position', 'forward_6': 'forward', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'forward_6': [0], '3_7': [2]}

['player', 'no', 'nationality', 'position', 'years in toronto', 'school / club team']

[['sundiata gaines', '2', 'united states', 'guard', '2011', 'georgia'], ['jorge garbajosa', '15', 'spain', 'forward', '2006 - 08', 'cb mã ¡ laga ( spain )'], ['chris garner', '0', 'united states', 'guard', '1997 - 98', 'memphis'], ['rudy gay', '22', 'united states', 'forward', '2013 - present', 'connecticut'], ['dion glover', '22', 'united states', 'guard', '2004', 'georgia tech'], ['joey graham', '14', 'united states', 'guard - forward', '2005 - 09', 'oklahoma state']]

2002 senior pga tour

https://en.wikipedia.org/wiki/2002_Senior_PGA_Tour

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11603116-4.html.csv

aggregation

the players in the 2002 senior pga tour had average earnings of 11647073 .

{'scope': 'all', 'col': '4', 'type': 'average', 'result': '11647073', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'earnings'], 'result': '11647073', 'ind': 0, 'tostr': 'avg { all_rows ; earnings }'}, '11647073'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; earnings } ; 11647073 } = true', 'tointer': 'the average of the earnings record of all rows is 11647073 .'}

round_eq { avg { all_rows ; earnings } ; 11647073 } = true

the average of the earnings record of all rows is 11647073 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'earnings_4': 4, '11647073_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'earnings_4': 'earnings', '11647073_5': '11647073'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'earnings_4': [0], '11647073_5': [1]}

['rank', 'player', 'country', 'earnings', 'wins']

[['1', 'hale irwin', 'united states', '16950178', '36'], ['2', 'gil morgan', 'united states', '11092593', '21'], ['3', 'jim colbert', 'united states', '10840374', '20'], ['4', 'dave stockton', 'united states', '9735814', '14'], ['5', 'lee trevino', 'united states', '9616404', '29']]

2005 - 06 toronto raptors season

https://en.wikipedia.org/wiki/2005%E2%80%9306_Toronto_Raptors_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15873014-7.html.csv

comparative

in march of the 2005 - 06 season , the toronto raptors scored more points against new york than they did against detroit .

{'row_1': '11', 'row_2': '9', 'col': '4', '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', 'team', 'new york'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to new york .', 'tostr': 'filter_eq { all_rows ; team ; new york }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; new york } ; score }', 'tointer': 'select the rows whose team record fuzzily matches to new york . take the score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'detroit'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to detroit .', 'tostr': 'filter_eq { all_rows ; team ; detroit }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; detroit } ; score }', 'tointer': 'select the rows whose team record fuzzily matches to detroit . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; team ; new york } ; score } ; hop { filter_eq { all_rows ; team ; detroit } ; score } } = true', 'tointer': 'select the rows whose team record fuzzily matches to new york . take the score record of this row . select the rows whose team record fuzzily matches to detroit . take the score record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; team ; new york } ; score } ; hop { filter_eq { all_rows ; team ; detroit } ; score } } = true

select the rows whose team record fuzzily matches to new york . take the score record of this row . select the rows whose team record fuzzily matches to detroit . take the score record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team_7': 7, 'new york_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'detroit_12': 12, 'score_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team_7': 'team', 'new york_8': 'new york', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'detroit_12': 'detroit', 'score_13': 'score'}

{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'new york_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'detroit_12': [1], 'score_13': [3]}

['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']

[['57', 'march 1', 'atlanta', 'l 111 - 113 ( ot )', 'chris bosh ( 27 )', 'charlie villanueva ( 11 )', 'chris bosh ( 5 )', 'air canada centre 15137', '20 - 37'], ['58', 'march 4', 'new jersey', 'l 100 - 105 ( ot )', 'morris peterson ( 25 )', 'chris bosh , charlie villanueva ( 11 )', 'mike james ( 7 )', 'continental airlines arena 16215', '20 - 38'], ['59', 'march 5', 'boston', 'w 111 - 105 ( ot )', 'morris peterson ( 27 )', 'chris bosh ( 10 )', 'mike james ( 6 )', 'air canada centre 16623', '21 - 38'], ['60', 'march 7', 'cleveland', 'l 99 - 106 ( ot )', 'mike james ( 31 )', 'charlie villanueva ( 11 )', 'mike james ( 8 )', 'quicken loans arena 18077', '21 - 39'], ['61', 'march 8', 'cleveland', 'l 97 - 98 ( ot )', 'morris peterson ( 31 )', 'chris bosh ( 14 )', 'mike james ( 7 )', 'air canada centre 19800', '21 - 40'], ['62', 'march 10', 'denver', 'l 97 - 108 ( ot )', 'mike james ( 26 )', 'chris bosh ( 15 )', 'josé calderón ( 5 )', 'air canada centre 17806', '21 - 41'], ['63', 'march 12', 'indiana', 'w 93 - 89 ( ot )', 'morris peterson ( 25 )', 'chris bosh ( 8 )', 'mike james ( 4 )', 'air canada centre 17573', '22 - 41'], ['64', 'march 14', 'philadelphia', 'w 111 - 97 ( ot )', 'chris bosh ( 31 )', 'charlie villanueva ( 10 )', 'darrick martin ( 12 )', 'wachovia center 14917', '23 - 41'], ['65', 'march 15', 'detroit', 'l 98 - 105 ( ot )', 'mike james ( 24 )', 'chris bosh ( 11 )', 'mike james ( 11 )', 'air canada centre 19800', '23 - 42'], ['66', 'march 17', 'milwaukee', 'w 97 - 96 ( ot )', 'chris bosh ( 27 )', 'chris bosh ( 10 )', 'mike james ( 6 )', 'air canada centre 17273', '24 - 42'], ['67', 'march 21', 'new york', 'w 114 - 109 ( ot )', 'mike james ( 37 )', 'mike james , charlie villanueva ( 8 )', 'mike james ( 5 )', 'madison square garden 18131', '25 - 42'], ['68', 'march 22', 'boston', 'l 96 - 110 ( ot )', 'mike james ( 31 )', 'chris bosh ( 11 )', 'chris bosh ( 8 )', 'td banknorth garden 18624', '25 - 43'], ['69', 'march 24', 'minnesota', 'w 97 - 77 ( ot )', 'morris peterson ( 21 )', 'chris bosh ( 15 )', 'mike james ( 5 )', 'air canada centre 17493', '26 - 43'], ['70', 'march 26', 'milwaukee', 'l 116 - 125 ( ot )', 'charlie villanueva ( 48 )', 'charlie villanueva ( 9 )', 'mike james ( 10 )', 'bradley center 16317', '26 - 44'], ['71', 'march 29', 'miami', 'l 94 - 98 ( ot )', 'morris peterson ( 28 )', 'charlie villanueva ( 13 )', 'mike james ( 12 )', 'air canada centre 19973', '26 - 45'], ['72', 'march 31', 'phoenix', 'l 126 - 140 ( ot )', 'morris peterson ( 38 )', 'pape sow ( 15 )', 'mike james ( 10 )', 'air canada centre 19800', '26 - 46']]

lauryn williams

https://en.wikipedia.org/wiki/Lauryn_Williams

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1027162-1.html.csv

aggregation

the lauryn williams competitions have an aggregate position of about 100 m.

{'scope': 'all', 'col': '4', 'type': 'average', 'result': '100', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'position'], 'result': '100', 'ind': 0, 'tostr': 'avg { all_rows ; position }'}, '100'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; position } ; 100 } = true', 'tointer': 'the average of the position record of all rows is 100 .'}

round_eq { avg { all_rows ; position } ; 100 } = true

the average of the position record of all rows is 100 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'position_4': 4, '100_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'position_4': 'position', '100_5': '100'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'position_4': [0], '100_5': [1]}

['year', 'competition', 'venue', 'position', 'event', 'notes']

[['2002', 'world junior championships', 'kingston , jamaica', '100 m', '1st', '11.33 secs'], ['2003', 'pan american games', 'santo domingo , dominican republic', '100 m', '1st', '11.12 secs'], ['2004', 'olympic games', 'athens , greece', '100 m', '2nd', '10.96 secs'], ['2004', 'world athletics final', 'monaco , monaco', '100 m', '3rd', '11.21 secs'], ['2005', 'world championships', 'helsinki , finland', '100 m', '1st', '10.93 secs'], ['2005', 'world athletics final', 'monaco , monaco', '100 m', '3rd', '11.04 secs'], ['2006', 'world indoor championships', 'moscow , russia', '60 m', '2nd', '7.01 secs'], ['2007', 'world championships', 'osaka , japan', '100 m', '2nd', '11.01 secs']]

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

aggregation

leonardo de souza had an average of 14.4 races per season .

{'scope': 'all', 'col': '4', 'type': 'average', 'result': '14.4', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'races'], 'result': '14.4', 'ind': 0, 'tostr': 'avg { all_rows ; races }'}, '14.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; races } ; 14.4 } = true', 'tointer': 'the average of the races record of all rows is 14.4 .'}

round_eq { avg { all_rows ; races } ; 14.4 } = true

the average of the races record of all rows is 14.4 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'races_4': 4, '14.4_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'races_4': 'races', '14.4_5': '14.4'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'races_4': [0], '14.4_5': [1]}

['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', 'kemba racing', '14', '0', '1', '2', '0', '33', '9th'], ['2010', 'formula three sudamericana', 'kemba racing', '20', '0', '1', '4', '1', '171', '5th']]

1979 masters tournament

https://en.wikipedia.org/wiki/1979_Masters_Tournament

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16458346-2.html.csv

ordinal

seve ballesteros placed highest in the 1979 masters tournament of players not from the united states .

{'scope': 'subset', 'row': '8', 'col': '1', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'not_equal', 'value': 'united states'}}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_not_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record does not match to united states .'}, 'place', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_not_eq { all_rows ; country ; united states } ; place ; 1 }'}, 'player'], 'result': 'seve ballesteros', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_not_eq { all_rows ; country ; united states } ; place ; 1 } ; player }'}, 'seve ballesteros'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_not_eq { all_rows ; country ; united states } ; place ; 1 } ; player } ; seve ballesteros } = true', 'tointer': 'select the rows whose country record does not match to united states . select the row whose place record of these rows is 1st minimum . the player record of this row is seve ballesteros .'}

eq { hop { nth_argmin { filter_not_eq { all_rows ; country ; united states } ; place ; 1 } ; player } ; seve ballesteros } = true

select the rows whose country record does not match to united states . select the row whose place record of these rows is 1st minimum . the player record of this row is seve ballesteros .

4

4

{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_5': 5, 'country_6': 6, 'united states_7': 7, 'place_8': 8, '1_9': 9, 'player_10': 10, 'seve ballesteros_11': 11}

{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_5': 'all_rows', 'country_6': 'country', 'united states_7': 'united states', 'place_8': 'place', '1_9': '1', 'player_10': 'player', 'seve ballesteros_11': 'seve ballesteros'}

{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_5': [0], 'country_6': [0], 'united states_7': [0], 'place_8': [1], '1_9': [1], 'player_10': [2], 'seve ballesteros_11': [3]}

['place', 'player', 'country', 'score', 'to par']

[['t1', 'ed sneed', 'united states', '68 + 67 = 135', '- 9'], ['t1', 'craig stadler', 'united states', '69 + 66 = 135', '- 9'], ['t3', 'raymond floyd', 'united states', '70 + 68 = 138', '- 6'], ['t3', 'leonard thompson', 'united states', '68 + 70 = 138', '- 6'], ['t5', 'miller barber', 'united states', '75 + 64 = 139', '- 5'], ['t5', 'tom watson', 'united states', '68 + 71 = 139', '- 5'], ['t5', 'joe inman', 'united states', '68 + 71 = 139', '- 5'], ['t8', 'seve ballesteros', 'spain', '72 + 68 = 140', '- 4'], ['t8', 'jack nicklaus', 'united states', '69 + 71 = 140', '- 4'], ['t8', 'lou graham', 'united states', '69 + 71 = 140', '- 4']]

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

comparative

in the 1991 san diego chargers season , mike heldt was selected one round before joachim weinberg .

{'row_1': '13', 'row_2': '14', 'col': '1', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'yes', 'diff_result': {'diff_value': '1', 'bigger': 'row2'}}

{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'mike heldt'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to mike heldt .', 'tostr': 'filter_eq { all_rows ; player ; mike heldt }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; mike heldt } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to mike heldt . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'joachim weinberg'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to joachim weinberg .', 'tostr': 'filter_eq { all_rows ; player ; joachim weinberg }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; joachim weinberg } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to joachim weinberg . take the round record of this row .'}], 'result': '-1', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; player ; mike heldt } ; round } ; hop { filter_eq { all_rows ; player ; joachim weinberg } ; round } }'}, '-1'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; player ; mike heldt } ; round } ; hop { filter_eq { all_rows ; player ; joachim weinberg } ; round } } ; -1 }', 'tointer': 'select the rows whose player record fuzzily matches to mike heldt . take the round record of this row . select the rows whose player record fuzzily matches to joachim weinberg . take the round record of this row . the second record is 1 larger than the first record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'mike heldt'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to mike heldt .', 'tostr': 'filter_eq { all_rows ; player ; mike heldt }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; mike heldt } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to mike heldt . take the round record of this row .'}, '10'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; player ; mike heldt } ; round } ; 10 }', 'tointer': 'the round record of the first row is 10 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'joachim weinberg'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to joachim weinberg .', 'tostr': 'filter_eq { all_rows ; player ; joachim weinberg }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; joachim weinberg } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to joachim weinberg . take the round record of this row .'}, '11'], 'result': True, 'ind': 7, 'tostr': 'eq { hop { filter_eq { all_rows ; player ; joachim weinberg } ; round } ; 11 }', 'tointer': 'the round record of the second row is 11 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; player ; mike heldt } ; round } ; 10 } ; eq { hop { filter_eq { all_rows ; player ; joachim weinberg } ; round } ; 11 } }', 'tointer': 'the round record of the first row is 10 . the round record of the second row is 11 .'}], 'result': True, 'ind': 9, 'tostr': 'and { eq { diff { hop { filter_eq { all_rows ; player ; mike heldt } ; round } ; hop { filter_eq { all_rows ; player ; joachim weinberg } ; round } } ; -1 } ; and { eq { hop { filter_eq { all_rows ; player ; mike heldt } ; round } ; 10 } ; eq { hop { filter_eq { all_rows ; player ; joachim weinberg } ; round } ; 11 } } } = true', 'tointer': 'select the rows whose player record fuzzily matches to mike heldt . take the round record of this row . select the rows whose player record fuzzily matches to joachim weinberg . take the round record of this row . the second record is 1 larger than the first record . the round record of the first row is 10 . the round record of the second row is 11 .'}

and { eq { diff { hop { filter_eq { all_rows ; player ; mike heldt } ; round } ; hop { filter_eq { all_rows ; player ; joachim weinberg } ; round } } ; -1 } ; and { eq { hop { filter_eq { all_rows ; player ; mike heldt } ; round } ; 10 } ; eq { hop { filter_eq { all_rows ; player ; joachim weinberg } ; round } ; 11 } } } = true

select the rows whose player record fuzzily matches to mike heldt . take the round record of this row . select the rows whose player record fuzzily matches to joachim weinberg . take the round record of this row . the second record is 1 larger than the first record . the round record of the first row is 10 . the round record of the second row is 11 .

14

10

{'and_9': 9, 'result_10': 10, 'eq_5': 5, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_11': 11, 'player_12': 12, 'mike heldt_13': 13, 'round_14': 14, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_15': 15, 'player_16': 16, 'joachim weinberg_17': 17, 'round_18': 18, '-1_19': 19, 'and_8': 8, 'eq_6': 6, '10_20': 20, 'eq_7': 7, '11_21': 21}

{'and_9': 'and', 'result_10': 'true', 'eq_5': 'eq', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player', 'mike heldt_13': 'mike heldt', 'round_14': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_15': 'all_rows', 'player_16': 'player', 'joachim weinberg_17': 'joachim weinberg', 'round_18': 'round', '-1_19': '-1', 'and_8': 'and', 'eq_6': 'eq', '10_20': '10', 'eq_7': 'eq', '11_21': '11'}

{'and_9': [10], 'result_10': [], 'eq_5': [9], 'diff_4': [5], 'num_hop_2': [4, 6], 'filter_str_eq_0': [2], 'all_rows_11': [0], 'player_12': [0], 'mike heldt_13': [0], 'round_14': [2], 'num_hop_3': [4, 7], 'filter_str_eq_1': [3], 'all_rows_15': [1], 'player_16': [1], 'joachim weinberg_17': [1], 'round_18': [3], '-1_19': [5], 'and_8': [9], 'eq_6': [8], '10_20': [6], 'eq_7': [8], '11_21': [7]}

['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', 'duane young', 'tight end', 'michigan state'], ['5', '127', 'floyd fields', 'defensive back', 'arizona state'], ['6', '150', 'jimmy laister', 'offensive tackle', 'oregon tech'], ['7', '177', 'david jones', 'tight end', 'delaware state'], ['7', '192', 'terry beauford', 'guard', 'florida a & m'], ['9', '230', 'andy katoa', 'linebacker', 'southern oregon'], ['10', '254', 'ronald poles', 'running back', 'tennessee'], ['10', '257', 'mike heldt', 'center', 'tennessee'], ['11', '290', 'joachim weinberg', 'wide receiver', 'johnson c smith u'], ['12', '317', 'chris samuels', 'running back', 'texas']]

nickelodeon movies

https://en.wikipedia.org/wiki/Nickelodeon_Movies

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1305286-7.html.csv

majority

most of the results for nickelodeon movies were nominations .

{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'nominated', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'result', 'nominated'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to nominated .', 'tostr': 'most_eq { all_rows ; result ; nominated } = true'}

most_eq { all_rows ; result ; nominated } = true

for the result records of all rows , most of them fuzzily match to nominated .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'nominated_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'nominated_4': 'nominated'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'nominated_4': [0]}

['year', 'category', 'film', 'winner / nominee ( s )', 'result']

[['1997', 'favorite movie actress', 'harriet the spy', "rosie o'donnell", 'nominated'], ['1999', 'favorite movie', 'the rugrats movie', 'n / a', 'won'], ['2001', 'favorite voice from an animated movie', 'rugrats in paris : the movie', 'susan sarandon', 'won'], ['2004', 'favorite voice from an animated movie', 'rugrats go wild', 'bruce willis', 'nominated'], ['2005', 'favorite movie actor', "lemony snicket 's a series of unfortunate events", 'jim carrey', 'nominated'], ['2007', 'favorite movie actor', 'nacho libre', 'jack black', 'nominated'], ['2007', 'favorite movie actress', "charlotte 's web", 'dakota fanning', 'won'], ['2012', 'favorite voice from an animated movie', 'rango', 'johnny depp', 'nominated']]

1922 in brazilian football

https://en.wikipedia.org/wiki/1922_in_Brazilian_football

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15389424-1.html.csv

aggregation

all of the 1922 brazilian football clubs scored a total number of 167 points .

{'scope': 'all', 'col': '3', 'type': 'sum', 'result': '167', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '167', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '167'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 167 } = true', 'tointer': 'the sum of the points record of all rows is 167 .'}

round_eq { sum { all_rows ; points } ; 167 } = true

the sum of the points record of all rows is 167 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '167_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '167_5': '167'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '167_5': [1]}

['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference']

[['1', 'corinthians', '30', '18', '2', '2', '19', '53'], ['2', 'palestra itália - sp', '29', '18', '1', '3', '24', '24'], ['3', 'sírio', '26', '18', '4', '3', '27', '17'], ['4', 'paulistano', '22', '18', '2', '6', '34', '17'], ['5', 'aa das palmeiras', '18', '18', '4', '7', '29', '8'], ['6', 'ypiranga - sp', '15', '18', '5', '8', '34', '- 2'], ['7', 'minas gerais', '14', '18', '2', '10', '54', '- 29'], ['8', 'aa são bento', '13', '18', '1', '11', '32', '- 7']]

list of career achievements by jack nicklaus

https://en.wikipedia.org/wiki/List_of_career_achievements_by_Jack_Nicklaus

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13026799-7.html.csv

count

jack nicklaus had to participate in a playoff two times .

{'scope': 'all', 'criterion': 'equal', 'value': 'playoff', 'result': '2', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'margin of victory', 'playoff'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose margin of victory record fuzzily matches to playoff .', 'tostr': 'filter_eq { all_rows ; margin of victory ; playoff }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; margin of victory ; playoff } }', 'tointer': 'select the rows whose margin of victory record fuzzily matches to playoff . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; margin of victory ; playoff } } ; 2 } = true', 'tointer': 'select the rows whose margin of victory record fuzzily matches to playoff . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; margin of victory ; playoff } } ; 2 } = true

select the rows whose margin of victory record fuzzily matches to playoff . 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, 'margin of victory_5': 5, 'playoff_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', 'margin of victory_5': 'margin of victory', 'playoff_6': 'playoff', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'margin of victory_5': [0], 'playoff_6': [0], '2_7': [2]}

['date', 'tournament', 'winning score', 'margin of victory', 'runner ( s ) - up']

[['apr 1 , 1990', 'the tradition at desert mountain', '- 10 ( 71 + 67 + 68 = 206 )', '4 strokes', 'gary player'], ['jun 10 , 1990', 'mazda senior tournament players championship', '- 27 ( 65 + 68 + 64 + 64 = 261 )', '6 strokes', 'lee trevino'], ['apr 7 , 1991', 'the tradition at desert mountain', '- 11 ( 71 + 73 + 66 + 67 = 277 )', '1 stroke', 'jim colbert , jim dent , phil rodgers'], ['apr 21 , 1991', "pga seniors ' championship", '- 17 ( 66 + 66 + 69 + 70 = 271 )', '6 strokes', 'bruce crampton'], ['jul 29 , 1991', 'us senior open', '+ 2 ( 72 + 69 + 70 + 71 = 282 )', 'playoff', 'chi - chi rodriguez'], ['jul 11 , 1993', 'us senior open', '- 6 ( 68 + 73 + 67 + 70 = 278 )', '1 stroke', 'tom weiskopf'], ['jan 9 , 1994', 'mercedes championships', '- 9 ( 73 + 69 + 69 + 68 = 279 )', '1 stroke', 'bob murphy'], ['apr 2 , 1995', 'the tradition', '- 12 ( 69 + 71 + 69 + 67 = 276 )', 'playoff', 'isao aoki'], ['feb 18 , 1996', 'gte suncoast classic', '- 2 ( 76 + 68 + 67 = 211 )', '1 stroke', 'j c snead'], ['apr 7 , 1996', 'the tradition', '- 16 ( 68 + 74 + 65 + 65 = 272 )', '3 strokes', 'hale irwin']]

2007 - 08 charlotte bobcats season

https://en.wikipedia.org/wiki/2007%E2%80%9308_Charlotte_Bobcats_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11907963-7.html.csv

aggregation

during the 2007 - 08 charlotte bobcats season the average points scored by jason richardson in games where he was high point scorer was 31 .

{'scope': 'subset', 'col': '5', 'type': 'average', 'result': '31', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': 'jason richardson'}}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high points', 'jason richardson'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high points ; jason richardson }', 'tointer': 'select the rows whose high points record fuzzily matches to jason richardson .'}, 'high points'], 'result': '31', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; high points ; jason richardson } ; high points }'}, '31'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; high points ; jason richardson } ; high points } ; 31 } = true', 'tointer': 'select the rows whose high points record fuzzily matches to jason richardson . the average of the high points record of these rows is 31 .'}

round_eq { avg { filter_eq { all_rows ; high points ; jason richardson } ; high points } ; 31 } = true

select the rows whose high points record fuzzily matches to jason richardson . the average of the high points record of these rows is 31 .

3

3

{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high points_5': 5, 'jason richardson_6': 6, 'high points_7': 7, '31_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high points_5': 'high points', 'jason richardson_6': 'jason richardson', 'high points_7': 'high points', '31_8': '31'}

{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high points_5': [0], 'jason richardson_6': [0], 'high points_7': [1], '31_8': [2]}

['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record']

[['59', 'march 2', 'toronto', '110 - 98', 'jason richardson ( 30 )', 'raymond felton ( 8 )', 'time warner cable arena 12083', '20 - 39'], ['60', 'march 4', 'minnesota', '109 - 89', 'jason richardson ( 25 )', 'raymond felton ( 10 )', 'target center 10019', '21 - 39'], ['61', 'march 5', 'golden state', '118 - 109', 'jason richardson ( 42 )', 'raymond felton ( 6 )', 'time warner cable arena 13747', '22 - 39'], ['62', 'march 7', 'atlanta', '108 - 93', 'raymond felton ( 23 )', 'raymond felton ( 11 )', 'time warner cable arena 15203', '23 - 39'], ['63', 'march 8', 'wizards', '100 - 97', 'jason richardson ( 34 )', 'raymond felton ( 12 )', 'verizon center 20173', '24 - 39'], ['64', 'march 12', 'dallas', '93 - 118', 'raymond felton ( 21 )', 'raymond felton ( 6 )', 'american airlines center 20279', '24 - 40'], ['65', 'march 14', 'houston', '80 - 89', 'jason richardson ( 28 )', 'jason richardson ( 5 )', 'toyota center 18265', '24 - 41'], ['66', 'march 16', 'cleveland', '91 - 98', 'jason richardson ( 33 )', 'raymond felton ( 9 )', 'quicken loans arena 20562', '24 - 42'], ['67', 'march 17', 'memphis', '80 - 98', 'derek anderson ( 17 )', 'earl boykins ( 5 )', 'fedex forum 10971', '24 - 43'], ['68', 'march 19', 'indiana', '95 - 102', 'jason richardson ( 20 )', 'jason richardson ( 8 )', 'conseco fieldhouse 10813', '24 - 44'], ['69', 'march 22', 'miami', '94 - 82', 'gerald wallace ( 26 )', 'raymond felton ( 10 )', 'time warner cable arena 17522', '25 - 44'], ['70', 'march 25', 'utah', '106 - 128', 'jason richardson ( 26 )', 'raymond felton ( 6 )', 'energysolutions arena 19911', '25 - 45'], ['71', 'march 26', 'la lakers', '108 - 95', 'jason richardson ( 34 )', 'raymond felton ( 10 )', 'staples center 18997', '26 - 45'], ['72', 'march 28', 'seattle', '96 - 93', 'jason richardson ( 27 )', 'raymond felton ( 6 )', 'keyarena 13592', '27 - 45'], ['73', 'march 29', 'portland', '93 - 85', 'emeka okafor ( 21 )', 'raymond felton ( 9 )', 'rose garden 19980', '28 - 45'], ['74', 'march 31', 'toronto', '100 - 104', 'jason richardson ( 26 )', 'raymond felton ( 10 )', 'time warner cable arena 12188', '28 - 46']]

list of hungarian records in swimming

https://en.wikipedia.org/wiki/List_of_Hungarian_records_in_swimming

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18473886-1.html.csv

aggregation

the average record time for hungarian swimming contenders in 50 m events is 24.41 .

{'scope': 'subset', 'col': '2', 'type': 'average', 'result': '24.41', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': '50 m'}}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', '50 m'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; event ; 50 m }', 'tointer': 'select the rows whose event record fuzzily matches to 50 m .'}, 'time'], 'result': '24.41', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; event ; 50 m } ; time }'}, '24.41'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; event ; 50 m } ; time } ; 24.41 } = true', 'tointer': 'select the rows whose event record fuzzily matches to 50 m . the average of the time record of these rows is 24.41 .'}

round_eq { avg { filter_eq { all_rows ; event ; 50 m } ; time } ; 24.41 } = true

select the rows whose event record fuzzily matches to 50 m . the average of the time record of these rows is 24.41 .

3

3

{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'event_5': 5, '50 m_6': 6, 'time_7': 7, '24.41_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'event_5': 'event', '50 m_6': '50 m', 'time_7': 'time', '24.41_8': '24.41'}

{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'event_5': [0], '50 m_6': [0], 'time_7': [1], '24.41_8': [2]}

['event', 'time', 'date', 'meet', 'location']

[['50 m freestyle', '21.42', '31 july 2009', 'world championships', 'rome , italy'], ['100 m freestyle', '49.13', '27 july 2001', 'world championships', 'fukuoka , japan'], ['200 m freestyle', '1:45.78', '31 july 2009', 'world championships', 'rome , italy'], ['400 m freestyle', '3:45.68', '26 july 2009', 'world championships', 'rome , italy'], ['800 m freestyle', '7:44.94', '27 july 2011', 'world championships', 'shanghai , china'], ['1500 m freestyle', '14:45.66', '31 july 2011', 'world championships', 'shanghai , china'], ['50 m backstroke', '25.14', '24 may 2012', 'european championships', 'debrecen , hungary'], ['100 m backstroke', '53.40', '4 august 2012', 'olympic games', 'london , united kingdom'], ['200 m backstroke', '1:55.88', '26 may 2012', 'european championships', 'debrecen , hungary'], ['50 m breaststroke', '27.51', '2 august 2002', 'european championships', 'berlin , germany'], ['100 m breaststroke', '59.53', '29 july 2012', 'olympic games', 'london , united kingdom'], ['200 m breaststroke', '2:07.23', '2 august 2013', '2013 world championships', 'barcelona , spain'], ['50 m butterfly', '23.57', '28 june 2009', 'hungarian championships', 'eger , hungary'], ['100 m butterfly', '51.45', '3 august 2013', '2013 world championships', 'barcelona , spain'], ['200 m butterfly', '1:52.70', '13 august 2008', 'olympic games', 'beijing , china'], ['200 m individual medley', '1:55.18', '29 july 2009', 'world championships', 'rome , italy'], ['400 m individual medley', '4:06.18', '10 august 2008', 'olympic games', 'beijing , china'], ['4100 m freestyle relay', '3:17.23', '21 may 2012', 'european championships', 'debrecen , hungary'], ['4200 m freestyle relay', '7:08.24', '31 july 2009', 'world championships', 'rome , italy'], ['4100 m medley relay', '3:33.02', '4 august 2012', 'olympic games', 'london , united kingdom']]

list of manly - warringah sea eagles honours

https://en.wikipedia.org/wiki/List_of_Manly-Warringah_Sea_Eagles_honours

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12573519-8.html.csv

superlative

the manly - warringah sea eagles ' game against the melbourne storm recorded the most attendance .

{'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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'opponent'], 'result': 'melbourne storm', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; opponent }'}, 'melbourne storm'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; opponent } ; melbourne storm } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the opponent record of this row is melbourne storm .'}

eq { hop { argmax { all_rows ; attendance } ; opponent } ; melbourne storm } = true

select the row whose attendance record of all rows is maximum . the opponent record of this row is melbourne storm .

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, 'melbourne storm_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', 'melbourne storm_7': 'melbourne storm'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'melbourne storm_7': [2]}

['year', 'opponent', 'competition', 'score', 'venue', 'attendance']

[['1951', 'south sydney rabbitohs', 'nswrfl', '14 - 42', 'sydney sports ground', '28505'], ['1957', 'st george dragons', 'nswrfl', '9 - 31', 'sydney cricket ground', '54399'], ['1959', 'st george dragons', 'nswrfl', '0 - 20', 'sydney cricket ground', '49457'], ['1968', 'south sydney rabbitohs', 'nswrfl', '9 - 13', 'sydney cricket ground', '54255'], ['1970', 'south sydney rabbitohs', 'nswrfl', '12 - 23', 'sydney cricket ground', '53241'], ['1982', 'parramatta eels', 'nswrfl', '8 - 21', 'sydney cricket ground', '52186'], ['1983', 'parramatta eels', 'nswrfl', '6 - 18', 'sydney cricket ground', '40285'], ['1995', 'sydney bulldogs', 'arl', '4 - 17', 'sydney football stadium', '41127'], ['1997', 'newcastle knights', 'arl', '16 - 22', 'sydney football stadium', '42482'], ['2007', 'melbourne storm', 'nrl', '8 - 34', 'anz stadium', '81392']]

anthony kim

https://en.wikipedia.org/wiki/Anthony_Kim

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11106562-3.html.csv

comparative

of the tournaments that anthony kim participated in , he had 1 more top 5 at the masters tournament than at the us open .

{'row_1': '1', 'row_2': '2', 'col': '3', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'masters tournament'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to masters tournament .', 'tostr': 'filter_eq { all_rows ; tournament ; masters tournament }'}, 'top - 5'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; masters tournament } ; top - 5 }', 'tointer': 'select the rows whose tournament record fuzzily matches to masters tournament . take the top - 5 record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'us open'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to us open .', 'tostr': 'filter_eq { all_rows ; tournament ; us open }'}, 'top - 5'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; us open } ; top - 5 }', 'tointer': 'select the rows whose tournament record fuzzily matches to us open . take the top - 5 record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; tournament ; masters tournament } ; top - 5 } ; hop { filter_eq { all_rows ; tournament ; us open } ; top - 5 } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to masters tournament . take the top - 5 record of this row . select the rows whose tournament record fuzzily matches to us open . take the top - 5 record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; tournament ; masters tournament } ; top - 5 } ; hop { filter_eq { all_rows ; tournament ; us open } ; top - 5 } } = true

select the rows whose tournament record fuzzily matches to masters tournament . take the top - 5 record of this row . select the rows whose tournament record fuzzily matches to us open . take the top - 5 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, 'tournament_7': 7, 'masters tournament_8': 8, 'top - 5_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'tournament_11': 11, 'us open_12': 12, 'top - 5_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', 'tournament_7': 'tournament', 'masters tournament_8': 'masters tournament', 'top - 5_9': 'top - 5', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tournament', 'us open_12': 'us open', 'top - 5_13': 'top - 5'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'tournament_7': [0], 'masters tournament_8': [0], 'top - 5_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'tournament_11': [1], 'us open_12': [1], 'top - 5_13': [3]}

['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made']

[['masters tournament', '0', '1', '1', '2', '3', '2'], ['us open', '0', '0', '0', '2', '4', '4'], ['the open championship', '0', '1', '2', '2', '3', '2'], ['pga championship', '0', '0', '0', '0', '5', '3'], ['totals', '0', '2', '3', '6', '15', '11']]

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

unique

the fiat albea with the 1.2 8v sohc engine is the only one with 1242 cc displacement that has 2500 rpm of torque .

{'scope': 'subset', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'at2500 rpm', 'subset': {'col': '3', 'criterion': 'equal', 'value': '1242 cc'}}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'displacement', '1242 cc'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; displacement ; 1242 cc }', 'tointer': 'select the rows whose displacement record fuzzily matches to 1242 cc .'}, 'torque', 'at2500 rpm'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose displacement record fuzzily matches to 1242 cc . among these rows , select the rows whose torque record fuzzily matches to at2500 rpm .', 'tostr': 'filter_eq { filter_eq { all_rows ; displacement ; 1242 cc } ; torque ; at2500 rpm }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; displacement ; 1242 cc } ; torque ; at2500 rpm } }', 'tointer': 'select the rows whose displacement record fuzzily matches to 1242 cc . among these rows , select the rows whose torque record fuzzily matches to at2500 rpm . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'displacement', '1242 cc'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; displacement ; 1242 cc }', 'tointer': 'select the rows whose displacement record fuzzily matches to 1242 cc .'}, 'torque', 'at2500 rpm'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose displacement record fuzzily matches to 1242 cc . among these rows , select the rows whose torque record fuzzily matches to at2500 rpm .', 'tostr': 'filter_eq { filter_eq { all_rows ; displacement ; 1242 cc } ; torque ; at2500 rpm }'}, 'engine'], 'result': '1.2 8v sohc', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; displacement ; 1242 cc } ; torque ; at2500 rpm } ; engine }'}, '1.2 8v sohc'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; displacement ; 1242 cc } ; torque ; at2500 rpm } ; engine } ; 1.2 8v sohc }', 'tointer': 'the engine record of this unqiue row is 1.2 8v sohc .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; displacement ; 1242 cc } ; torque ; at2500 rpm } } ; eq { hop { filter_eq { filter_eq { all_rows ; displacement ; 1242 cc } ; torque ; at2500 rpm } ; engine } ; 1.2 8v sohc } } = true', 'tointer': 'select the rows whose displacement record fuzzily matches to 1242 cc . among these rows , select the rows whose torque record fuzzily matches to at2500 rpm . there is only one such row in the table . the engine record of this unqiue row is 1.2 8v sohc .'}

and { only { filter_eq { filter_eq { all_rows ; displacement ; 1242 cc } ; torque ; at2500 rpm } } ; eq { hop { filter_eq { filter_eq { all_rows ; displacement ; 1242 cc } ; torque ; at2500 rpm } ; engine } ; 1.2 8v sohc } } = true

select the rows whose displacement record fuzzily matches to 1242 cc . among these rows , select the rows whose torque record fuzzily matches to at2500 rpm . there is only one such row in the table . the engine record of this unqiue row is 1.2 8v sohc .

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, 'displacement_8': 8, '1242 cc_9': 9, 'torque_10': 10, 'at2500 rpm_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'engine_12': 12, '1.2 8v sohc_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', 'displacement_8': 'displacement', '1242 cc_9': '1242 cc', 'torque_10': 'torque', 'at2500 rpm_11': 'at2500 rpm', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'engine_12': 'engine', '1.2 8v sohc_13': '1.2 8v sohc'}

{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'displacement_8': [0], '1242 cc_9': [0], 'torque_10': [1], 'at2500 rpm_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'engine_12': [3], '1.2 8v sohc_13': [4]}

['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']]

green party of british columbia

https://en.wikipedia.org/wiki/Green_Party_of_British_Columbia

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-168482-1.html.csv

superlative

the green party of british columbia achieved their highest percentage of the popular vote in 2001 .

{'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', '% of popular vote'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; % of popular vote }'}, 'election'], 'result': '2001', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; % of popular vote } ; election }'}, '2001'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; % of popular vote } ; election } ; 2001 } = true', 'tointer': 'select the row whose % of popular vote record of all rows is maximum . the election record of this row is 2001 .'}

eq { hop { argmax { all_rows ; % of popular vote } ; election } ; 2001 } = true

select the row whose % of popular vote record of all rows is maximum . the election record of this row is 2001 .

3

3

{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, '% of popular vote_5': 5, 'election_6': 6, '2001_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', '% of popular vote_5': '% of popular vote', 'election_6': 'election', '2001_7': '2001'}

{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], '% of popular vote_5': [0], 'election_6': [1], '2001_7': [2]}

['election', 'candidates fielded', 'of seats won', 'total votes', '% of popular vote', 'place']

[['1983', '4', '0', '3078', '0.19 %', '7th'], ['1986', '9', '0', '4660', '0.24 %', '5th'], ['1991', '42', '0', '12650', '0.86 %', '4th'], ['1996', '71', '0', '31511', '1.99 %', '5th'], ['2001', '72', '0', '197231', '12.39 %', '3rd'], ['2005', '79', '0', '161842', '9.17 %', '3rd'], ['2009', '85', '0', '134570', '8.21 %', '3rd'], ['2013', '61', '1', '146607', '8.13 %', '3rd']]

2004 centrix financial grand prix of denver

https://en.wikipedia.org/wiki/2004_Centrix_Financial_Grand_Prix_of_Denver

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16789804-1.html.csv

count

18 players participated in the 2004 centrix financial grand prix of denver .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '18', 'col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'name'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record is arbitrary .', 'tostr': 'filter_all { all_rows ; name }'}], 'result': '18', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; name } }', 'tointer': 'select the rows whose name record is arbitrary . the number of such rows is 18 .'}, '18'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; name } } ; 18 } = true', 'tointer': 'select the rows whose name record is arbitrary . the number of such rows is 18 .'}

eq { count { filter_all { all_rows ; name } } ; 18 } = true

select the rows whose name record is arbitrary . the number of such rows is 18 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'name_5': 5, '18_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'name_5': 'name', '18_6': '18'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'name_5': [0], '18_6': [2]}

['name', 'team', 'qual 1', 'qual 2', 'best']

[['sébastien bourdais', 'newman / haas racing', '1:00.413', '59.942', '59.942'], ['bruno junqueira', 'newman / haas racing', '1:01.203', '1:00.525', '1:00.525'], ['paul tracy', 'forsythe racing', '1:00.885', '1:00.588', '1:00.588'], ['patrick carpentier', 'forsythe racing', '1:01.416', '1:00.595', '1:00.595'], ['mario domínguez', 'herdez competition', '1:00.721', '-', '1:00.721'], ['oriol servià', 'dale coyne racing', '1:02.046', '1:00.813', '1:00.813'], ['a j allmendinger', 'rusport', '-', '1:00.907', '1:00.907'], ['ryan hunter - reay', 'herdez competition', '1:01.545', '1:01.072', '1:01.072'], ['mario haberfeld', 'walker racing', '1:01.198', '1:01.285', '1:01.198'], ['justin wilson', 'mi - jack conquest racing', '1:01.782', '1:01.265', '1:01.265'], ['alex tagliani', 'rocketsports racing', '1:01.757', '1:01.266', '1:01.266'], ['jimmy vasser', 'pkv racing', '1:01.334', '1:02.090', '1:01.334'], ['michel jourdain , jr', 'rusport', '1:01.447', '1:01.345', '1:01.345'], ['nelson philippe', 'mi - jack conquest racing', '1:02.354', '1:01.522', '1:01.522'], ['rodolfo lavín', 'forsythe racing', '1:02.130', '1:01.794', '1:01.794'], ['guy smith', 'rocketsports racing', '1:02.113', '1:02.137', '1:02.113'], ['gastón mazzacane', 'dale coyne racing', '1:02.412', '-', '1:02.412'], ['roberto gonzález', 'pkv racing', '1:02.604', '1:02.507', '1:02.507']]

list of post - secondary institutions in malaysia

https://en.wikipedia.org/wiki/List_of_post-secondary_institutions_in_Malaysia

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18144241-2.html.csv

unique

sultan abdul halim mu'adzam shah is the only post-secondary institution in malaysia to have the acronym polimas .

{'scope': 'all', 'row': '11', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'polimas', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'acronym', 'polimas'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose acronym record fuzzily matches to polimas .', 'tostr': 'filter_eq { all_rows ; acronym ; polimas }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; acronym ; polimas } }', 'tointer': 'select the rows whose acronym record fuzzily matches to polimas . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'acronym', 'polimas'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose acronym record fuzzily matches to polimas .', 'tostr': 'filter_eq { all_rows ; acronym ; polimas }'}, 'name in english'], 'result': "sultan abdul halim mu'adzam shah", 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; acronym ; polimas } ; name in english }'}, "sultan abdul halim mu'adzam shah"], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; acronym ; polimas } ; name in english } ; sultan abdul halim mu'adzam shah }", 'tointer': "the name in english record of this unqiue row is sultan abdul halim mu'adzam shah ."}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; acronym ; polimas } } ; eq { hop { filter_eq { all_rows ; acronym ; polimas } ; name in english } ; sultan abdul halim mu'adzam shah } } = true", 'tointer': "select the rows whose acronym record fuzzily matches to polimas . there is only one such row in the table . the name in english record of this unqiue row is sultan abdul halim mu'adzam shah ."}

and { only { filter_eq { all_rows ; acronym ; polimas } } ; eq { hop { filter_eq { all_rows ; acronym ; polimas } ; name in english } ; sultan abdul halim mu'adzam shah } } = true

select the rows whose acronym record fuzzily matches to polimas . there is only one such row in the table . the name in english record of this unqiue row is sultan abdul halim mu'adzam shah .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'acronym_7': 7, 'polimas_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name in english_9': 9, "sultan abdul halim mu'adzam shah_10": 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'acronym_7': 'acronym', 'polimas_8': 'polimas', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name in english_9': 'name in english', "sultan abdul halim mu'adzam shah_10": "sultan abdul halim mu'adzam shah"}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'acronym_7': [0], 'polimas_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name in english_9': [2], "sultan abdul halim mu'adzam shah_10": [3]}

['name in english', 'name in malay', 'acronym', 'foundation', 'location']

[['alor setar professional institute', 'institut profesional alor setar', '-', '-', 'alor setar'], ['a n s technological institute , alor setar', 'institut teknologi a n s alor setar', '-', '-', 'alor setar'], ['bandar darulaman community college', 'kolej komuniti bandar darulaman', '-', '-', 'jitra'], ['daya ilmu technological institute , sungai petani', 'institut teknologi daya ilmu sungai petani', '-', '-', 'sungai petani'], ['hasani institute', 'institut hasani', '-', '-', 'sungai petani'], ['informatics institute , sungai petani', 'institut informatics , sungai petani', '-', '-', 'sungai petani'], ['international northern higher education institute', 'institut pengajian tinggi utara antarabangsa', '-', 'petua', 'alor setar'], ['kulim community college', 'kolej komuniti kulim', '-', '-', 'kulim'], ['kulim polytechnic', 'politeknik kulim', 'pku', '-', 'kulim'], ['northern management and technological institute', 'institut pengurusan dan teknologi utara', '-', 'iptura', 'alor setar'], ["sultan abdul halim mu'adzam shah", "politeknik sultan abdul halim mu'adzam shah", 'polimas', '1984', 'jitra'], ['sungai petani community college', 'kolej komuniti sungai petani', '2002', 'kkspe', 'sungai petani']]

swimming at the 2008 summer olympics - women 's 50 metre freestyle

https://en.wikipedia.org/wiki/Swimming_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_50_metre_freestyle

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18625234-4.html.csv

comparative

kara lynn joyce had a faster swimming time than aliaksandra herasimenia .

{'row_1': '5', 'row_2': '6', 'col': '5', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'kara lynn joyce'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to kara lynn joyce .', 'tostr': 'filter_eq { all_rows ; name ; kara lynn joyce }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; kara lynn joyce } ; time }', 'tointer': 'select the rows whose name record fuzzily matches to kara lynn joyce . take the time record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'aliaksandra herasimenia'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to aliaksandra herasimenia .', 'tostr': 'filter_eq { all_rows ; name ; aliaksandra herasimenia }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; aliaksandra herasimenia } ; time }', 'tointer': 'select the rows whose name record fuzzily matches to aliaksandra herasimenia . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; kara lynn joyce } ; time } ; hop { filter_eq { all_rows ; name ; aliaksandra herasimenia } ; time } } = true', 'tointer': 'select the rows whose name record fuzzily matches to kara lynn joyce . take the time record of this row . select the rows whose name record fuzzily matches to aliaksandra herasimenia . take the time record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; name ; kara lynn joyce } ; time } ; hop { filter_eq { all_rows ; name ; aliaksandra herasimenia } ; time } } = true

select the rows whose name record fuzzily matches to kara lynn joyce . take the time record of this row . select the rows whose name record fuzzily matches to aliaksandra herasimenia . take the time 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, 'name_7': 7, 'kara lynn joyce_8': 8, 'time_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'aliaksandra herasimenia_12': 12, 'time_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', 'name_7': 'name', 'kara lynn joyce_8': 'kara lynn joyce', 'time_9': 'time', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'aliaksandra herasimenia_12': 'aliaksandra herasimenia', 'time_13': 'time'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'kara lynn joyce_8': [0], 'time_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'aliaksandra herasimenia_12': [1], 'time_13': [3]}

['rank', 'lane', 'name', 'nationality', 'time']

[['1', '3', 'britta steffen', 'germany', '24.43'], ['2', '4', 'marleen veldhuis', 'netherlands', '24.46'], ['3', '5', 'lisbeth trickett', 'australia', '24.47'], ['4', '7', 'hinkelien schreuder', 'netherlands', '24.52'], ['5', '1', 'kara lynn joyce', 'united states', '24.63'], ['6', '8', 'aliaksandra herasimenia', 'belarus', '24.72'], ['7', '6', 'francesca halsall', 'great britain', '24.80'], ['8', '2', 'malia metella', 'france', '24.89']]

bill vukovich

https://en.wikipedia.org/wiki/Bill_Vukovich

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1251950-1.html.csv

count

of the times bill vukovich used an offenhauser engine , he only used a trevis chassis once .

{'scope': 'subset', 'criterion': 'equal', 'value': 'trevis', 'result': '1', 'col': '3', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'offenhauser l4'}}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'offenhauser l4'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; engine ; offenhauser l4 }', 'tointer': 'select the rows whose engine record fuzzily matches to offenhauser l4 .'}, 'chassis', 'trevis'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose engine record fuzzily matches to offenhauser l4 . among these rows , select the rows whose chassis record fuzzily matches to trevis .', 'tostr': 'filter_eq { filter_eq { all_rows ; engine ; offenhauser l4 } ; chassis ; trevis }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; engine ; offenhauser l4 } ; chassis ; trevis } }', 'tointer': 'select the rows whose engine record fuzzily matches to offenhauser l4 . among these rows , select the rows whose chassis record fuzzily matches to trevis . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; engine ; offenhauser l4 } ; chassis ; trevis } } ; 1 } = true', 'tointer': 'select the rows whose engine record fuzzily matches to offenhauser l4 . among these rows , select the rows whose chassis record fuzzily matches to trevis . the number of such rows is 1 .'}

eq { count { filter_eq { filter_eq { all_rows ; engine ; offenhauser l4 } ; chassis ; trevis } } ; 1 } = true

select the rows whose engine record fuzzily matches to offenhauser l4 . among these rows , select the rows whose chassis record fuzzily matches to trevis . the number of such rows is 1 .

4

4

{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'engine_6': 6, 'offenhauser l4_7': 7, 'chassis_8': 8, 'trevis_9': 9, '1_10': 10}

{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'engine_6': 'engine', 'offenhauser l4_7': 'offenhauser l4', 'chassis_8': 'chassis', 'trevis_9': 'trevis', '1_10': '1'}

{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'engine_6': [0], 'offenhauser l4_7': [0], 'chassis_8': [1], 'trevis_9': [1], '1_10': [3]}

['year', 'entrant', 'chassis', 'engine', 'points']

[['1950', 'i r c', 'maserati', 'maserati l4', '0'], ['1951', 'central excavating', 'trevis', 'offenhauser l4', '0'], ['1952', 'fuel injection', 'kurtis kraft kk500a', 'offenhauser l4', '1'], ['1953', 'fuel injection', 'kurtis kraft kk500a', 'offenhauser l4', '9'], ['1954', 'fuel injection', 'kurtis kraft kk500a', 'offenhauser l4', '8'], ['1955', 'hopkins', 'kurtis kraft kk500c', 'offenhauser l4', '1']]

1996 pga championship

https://en.wikipedia.org/wiki/1996_PGA_Championship

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18096431-2.html.csv

majority

most of the players from the united states at the 1996 pga championship had previously won in the 1980 's .

{'scope': 'subset', 'col': '3', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '198', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'united states'}}

{'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'year ( s ) won', '198'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . for the year ( s ) won records of these rows , most of them fuzzily match to 198 .', 'tostr': 'most_eq { filter_eq { all_rows ; country ; united states } ; year ( s ) won ; 198 } = true'}

most_eq { filter_eq { all_rows ; country ; united states } ; year ( s ) won ; 198 } = true

select the rows whose country record fuzzily matches to united states . for the year ( s ) won records of these rows , most of them fuzzily match to 198 .

2

2

{'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'country_4': 4, 'united states_5': 5, 'year (s) won_6': 6, '198_7': 7}

{'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'country_4': 'country', 'united states_5': 'united states', 'year (s) won_6': 'year ( s ) won', '198_7': '198'}

{'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'country_4': [0], 'united states_5': [0], 'year (s) won_6': [1], '198_7': [1]}

['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish']

[['steve elkington', 'australia', '1995', '278', '- 10', 't3'], ['nick price', 'zimbabwe', '1992 , 1994', '280', '- 8', 't13'], ['paul azinger', 'united states', '1993', '285', '- 3', 't29'], ['jeff sluman', 'united states', '1988', '287', '- 1', 't41'], ['wayne grady', 'australia', '1990', '291', '+ 3', 't65'], ['payne stewart', 'united states', '1989', '292', '+ 4', 't69'], ['larry nelson', 'united states', '1981 , 1987', '295', '+ 15', 't71']]

orlando magic all - time roster

https://en.wikipedia.org/wiki/Orlando_Magic_all-time_roster

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15621965-2.html.csv

majority

all of the players have a nationality that is the united states .

{'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None}

{'func': 'all_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; nationality ; united states } = true'}

all_eq { all_rows ; nationality ; united states } = true

for the nationality records of all rows , all of them fuzzily match to united states .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]}

['player', 'no', 'nationality', 'position', 'years in orlando', 'school / club team']

[['matt barnes', '22', 'united states', 'guard - forward', '2009 - 2010', 'ucla'], ['andre barrett', '11', 'united states', 'guard', '2005', 'seton hall'], ['brandon bass', '30', 'united states', 'forward', '2009 - 2011', 'louisiana state'], ['tony battie', '4', 'united states', 'forward - center', '2004 - 2009', 'texas tech'], ['david benoit', '2', 'united states', 'forward', '1998', 'alabama'], ['keith bogans', '3', 'united states', 'guard', '2003 - 2004', 'kentucky'], ['keith bogans', '10', 'united states', 'guard', '2006 - 2009', 'kentucky'], ['anthony bonner', '24', 'united states', 'forward', '1995 - 1996', 'st louis'], ['anthony bowie', '14', 'united states', 'guard', '1991 - 1996', 'oklahoma'], ['earl boykins', '11', 'united states', 'guard', '1999', 'eastern michigan'], ['michael bradley', '7', 'united states', 'forward', '2004 - 2005', 'villanova'], ['dee brown', '7', 'united states', 'guard', '2000 - 2002', 'jacksonville'], ['jud buechler', '30', 'united states', 'guard - forward', '2001 - 2002', 'arizona']]

1997 tennessee oilers season

https://en.wikipedia.org/wiki/1997_Tennessee_Oilers_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15986484-2.html.csv

aggregation

in october 1997 , total attendance at tennessee oilers games was 142,040 .

{'scope': 'subset', 'col': '7', 'type': 'sum', 'result': '142040', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'october'}}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'attendance'], 'result': '142040', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; date ; october } ; attendance }'}, '142040'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; date ; october } ; attendance } ; 142040 } = true', 'tointer': 'select the rows whose date record fuzzily matches to october . the sum of the attendance record of these rows is 142040 .'}

round_eq { sum { filter_eq { all_rows ; date ; october } ; attendance } ; 142040 } = true

select the rows whose date record fuzzily matches to october . the sum of the attendance record of these rows is 142040 .

3

3

{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'october_6': 6, 'attendance_7': 7, '142040_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'october_6': 'october', 'attendance_7': 'attendance', '142040_8': '142040'}

{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'october_6': [0], 'attendance_7': [1], '142040_8': [2]}

['week', 'date', 'opponent', 'result', 'record', 'location', 'attendance']

[['1', 'august 31 , 1997', 'oakland raiders', 'w 24 - 21', '1 - 0', 'liberty bowl memorial stadium', '30171'], ['2', 'september 7 , 1997', 'miami dolphins', 'l 16 - 13', '1 - 1', 'pro player stadium', '64439'], ['3', '-', '-', '-', '-', '-', ''], ['4', 'september 21 , 1997', 'baltimore ravens', 'l 36 - 10', '1 - 2', 'liberty bowl memorial stadium', '17737'], ['5', 'september 28 , 1997', 'pittsburgh steelers', 'l 37 - 24', '1 - 3', 'three rivers stadium', '57507'], ['6', 'october 5 , 1997', 'seattle seahawks', 'l 16 - 13', '1 - 4', 'kingdome', '49897'], ['7', 'october 12 , 1997', 'cincinnati bengals', 'w 30 - 7', '2 - 4', 'liberty bowl memorial stadium', '17071'], ['8', 'october 19 , 1997', 'washington redskins', 'w 28 - 14', '3 - 4', 'liberty bowl memorial stadium', '31042'], ['9', 'october 26 , 1997', 'arizona cardinals', 'w 41 - 14', '4 - 4', 'sun devil stadium', '44030'], ['10', 'november 2 , 1997', 'jacksonville jaguars', 'l 30 - 24', '4 - 5', 'liberty bowl memorial stadium', '27208'], ['11', 'november 9 , 1997', 'new york giants', 'w 10 - 6', '5 - 5', 'liberty bowl memorial stadium', '26744'], ['12', 'november 16 , 1997', 'jacksonville jaguars', 'l 17 - 9', '5 - 6', 'alltel stadium', '70070'], ['13', 'november 23 , 1997', 'buffalo bills', 'w 31 - 14', '6 - 6', 'liberty bowl memorial stadium', '23571'], ['14', 'november 27 , 1997', 'dallas cowboys', 'w 27 - 14', '7 - 6', 'texas stadium', '63421'], ['15', 'december 4 , 1997', 'cincinnati bengals', 'l 41 - 14', '7 - 7', 'cinergy field', '49086'], ['16', 'december 14 , 1997', 'baltimore ravens', 'l 21 - 19', '7 - 8', 'memorial stadium', '60558'], ['17', 'december 21 , 1997', 'pittsburgh steelers', 'w 16 - 6', '8 - 8', 'liberty bowl memorial stadium', '50677']]

sandro rosell

https://en.wikipedia.org/wiki/Sandro_Rosell

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18409089-1.html.csv

majority

the majority of sandro rosell 's signings cost more than 26 million euros .

{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '26', 'subset': None}

{'func': 'most_greater', 'args': ['all_rows', 'transfer fee ( millions )', '26'], 'result': True, 'ind': 0, 'tointer': 'for the transfer fee ( millions ) records of all rows , most of them are greater than 26 .', 'tostr': 'most_greater { all_rows ; transfer fee ( millions ) ; 26 } = true'}

most_greater { all_rows ; transfer fee ( millions ) ; 26 } = true

for the transfer fee ( millions ) records of all rows , most of them are greater than 26 .

1

1

{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'transfer fee ( millions)_3': 3, '26_4': 4}

{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'transfer fee ( millions)_3': 'transfer fee ( millions )', '26_4': '26'}

{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'transfer fee ( millions)_3': [0], '26_4': [0]}

['rank', 'player', 'from', 'transfer fee ( millions )', 'year']

[['1', 'neymar', 'santos fc', '57.0', '2013'], ['2', 'cesc fàbregas', 'arsenal', '29 + 5 ( variables )', '2011'], ['3', 'alexis sánchez', 'udinese', '26 + 11 ( add ons )', '2011'], ['4', 'javier mascherano', 'liverpool', '26.8', '2010'], ['5', 'alex song', 'arsenal', '19.0', '2012'], ['6', 'jordi alba', 'valencia', '14.0', '2012'], ['7', 'adriano', 'sevilla', '13.5', '2010']]

yorkshire county cricket club in 2008

https://en.wikipedia.org/wiki/Yorkshire_County_Cricket_Club_in_2008

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15893020-2.html.csv

ordinal

of the players in the yorkshire county cricket club in 2008 , tim bresnan had the second highest number of wickets .

{'row': '4', 'col': '6', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'wickets', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; wickets ; 2 }'}, 'player'], 'result': 'tim bresnan', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; wickets ; 2 } ; player }'}, 'tim bresnan'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; wickets ; 2 } ; player } ; tim bresnan } = true', 'tointer': 'select the row whose wickets record of all rows is 2nd maximum . the player record of this row is tim bresnan .'}

eq { hop { nth_argmax { all_rows ; wickets ; 2 } ; player } ; tim bresnan } = true

select the row whose wickets record of all rows is 2nd maximum . the player record of this row is tim bresnan .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'wickets_5': 5, '2_6': 6, 'player_7': 7, 'tim bresnan_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', 'wickets_5': 'wickets', '2_6': '2', 'player_7': 'player', 'tim bresnan_8': 'tim bresnan'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'wickets_5': [0], '2_6': [0], 'player_7': [1], 'tim bresnan_8': [2]}

['player', 'matches', 'overs', 'maidens', 'runs', 'wickets', 'average', 'economy', '5w', '10w', 'best bowling']

[['ajmal shahzad', '1', '24.0', '6', '64', '3', '21.33', '2.67', '0', '0', '2 / 43'], ['steven patterson', '4', '99.1', '23', '280', '12', '23.33', '2.82', '0', '0', '3 / 19'], ['matthew hoggard', '13', '342.5', '66', '1037', '42', '24.69', '3.02', '1', '0', '6 / 57'], ['tim bresnan', '14', '419.0', '726', '1267', '44', '28.80', '3.02', '1', '0', '5 / 94'], ['adil rashid', '16', '590.1', '64', '1886', '62', '30.42', '3.20', '4', '0', '7 / 107'], ['david wainwright', '4', '85.1', '18', '246', '8', '30.75', '2.89', '0', '0', '3 / 9'], ['anthony mcgrath', '14', '99.1', '16', '282', '9', '31.33', '2.84', '0', '0', '2 / 27'], ['mornã morkel', '1', '15.2', '4', '33', '1', '33.00', '2.15', '0', '0', '1 / 33'], ['rana naved - ul - hasan', '7', '153.1', '21', '604', '16', '37.75', '3.94', '0', '0', '4 / 86'], ['deon kruis', '10', '295.3', '68', '903', '22', '41.05', '3.06', '1', '0', '5 / 47'], ['darren gough', '8', '149.0', '25', '528', '9', '58.67', '3.54', '0', '0', '2 / 34'], ['jacques rudolph', '16', '21.2', '2', '74', '1', '74.00', '3.47', '0', '0', '1 / 13'], ['adam lyth', '14', '30.1', '5', '105', '1', '105.00', '3.48', '0', '0', '1 / 20'], ['oliver hannon - dalby', '1', '29.0', '5', '114', '1', '114.00', '3.93', '0', '0', '1 / 58'], ['ben sanderson', '2', '37.0', '7', '140', '1', '140.00', '3.78', '0', '0', '1 / 87'], ['richard pyrah', '5', '56.0', '11', '201', '1', '201.00', '3.59', '0', '0', '1 / 14'], ['andrew gale', '15', '1.0', '0', '3', '0', 'n / a', '3.00', '0', '0', '0 / 3'], ['michael vaughan', '6', '6.0', '0', '47', '0', 'n / a', '7.83', '0', '0', '0 / 47']]

2007 - 08 crewe alexandra f.c. season

https://en.wikipedia.org/wiki/2007%E2%80%9308_Crewe_Alexandra_F.C._season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12964478-4.html.csv

count

all but one of the awards were given to a club in england .

{'scope': 'all', 'criterion': 'equal', 'value': 'eng', 'result': '11', 'col': '2', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'eng'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to eng .', 'tostr': 'filter_eq { all_rows ; country ; eng }'}], 'result': '11', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; eng } }', 'tointer': 'select the rows whose country record fuzzily matches to eng . the number of such rows is 11 .'}, '11'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; eng } } ; 11 } = true', 'tointer': 'select the rows whose country record fuzzily matches to eng . the number of such rows is 11 .'}

eq { count { filter_eq { all_rows ; country ; eng } } ; 11 } = true

select the rows whose country record fuzzily matches to eng . the number of such rows is 11 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'eng_6': 6, '11_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'eng_6': 'eng', '11_7': '11'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'eng_6': [0], '11_7': [2]}

['date', 'country', 'name', 'award', 'notes']

[['13 aug 2007', 'eng', 'g s roberts', 'team of the week', 'source'], ['20 aug 2007', 'eng', 'woodards', 'team of the week', 'source'], ['10 sep 2007', 'ger', 'bopp', 'team of the week', 'source'], ['24 sep 2007', 'eng', 'williams', 'team of the week', 'source'], ['1 oct 2007', 'eng', 'jones', 'team of the week', 'source'], ['22 oct 2007', 'eng', 'lowe', 'team of the week', 'source'], ['5 nov 2007', 'eng', 'moore', 'team of the week', 'source'], ['19 nov 2007', 'eng', 'woodards', 'team of the week ( 2 )', 'source'], ['10 dec 2007', 'eng', 'woodards', 'team of the week ( 3 )', 'source'], ['28 jan 2008', 'eng', 'williams', 'team of the week ( 2 )', 'source'], ['3 mar 2008', 'eng', 'williams', 'team of the week ( 3 )', 'source'], ['17 mar 2008', 'eng', "o'connor", 'team of the week', 'source']]

list of the tudors episodes

https://en.wikipedia.org/wiki/List_of_The_Tudors_episodes

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10413597-5.html.csv

count

dearbhla walsh directed a total of three episodes of the tudors .

{'scope': 'all', 'criterion': 'equal', 'value': 'dearbhla walsh', 'result': '3', 'col': '5', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'dearbhla walsh'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to dearbhla walsh .', 'tostr': 'filter_eq { all_rows ; directed by ; dearbhla walsh }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; directed by ; dearbhla walsh } }', 'tointer': 'select the rows whose directed by record fuzzily matches to dearbhla walsh . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; directed by ; dearbhla walsh } } ; 3 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to dearbhla walsh . the number of such rows is 3 .'}

eq { count { filter_eq { all_rows ; directed by ; dearbhla walsh } } ; 3 } = true

select the rows whose directed by record fuzzily matches to dearbhla walsh . the number of such rows is 3 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'directed by_5': 5, 'dearbhla walsh_6': 6, '3_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'directed by_5': 'directed by', 'dearbhla walsh_6': 'dearbhla walsh', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'directed by_5': [0], 'dearbhla walsh_6': [0], '3_7': [2]}

['no in series', 'no in season', 'title', 'setting', 'directed by', 'written by', 'us viewers ( million )', 'original air date']

[['29', '1', 'moment of nostalgia', 'summer 1540', 'dearbhla walsh', 'michael hirst', '0.88', 'april 11 , 2010'], ['30', '2', 'sister', 'winter 1540', 'dearbhla walsh', 'michael hirst', 'n / a', 'april 18 , 2010'], ['31', '3', 'something for you', 'spring 1541', 'dearbhla walsh', 'michael hirst', 'n / a', 'april 25 , 2010'], ['32', '4', 'natural ally', 'summer / autumn 1541', 'ciarán donnelly', 'michael hirst', '0.90', 'may 2 , 2010'], ['33', '5', 'bottom of the pot', 'winter 1541 / february 13 , 1542', 'ciarán donnelly', 'michael hirst', '0.93', 'may 9 , 2010'], ['34', '6', 'you have my permission', '1542', 'ciarán donnelly', 'michael hirst', 'n / a', 'may 16 , 2010'], ['35', '7', 'sixth and the final wife', '1543', 'jeremy podeswa', 'michael hirst', '0.95', 'may 23 , 2010'], ['36', '8', 'as it should be', '1544', 'jeremy podeswa', 'michael hirst', '0.99', 'june 6 , 2010'], ['37', '9', 'secrets of the heart', '1544 - 1546', 'ciarán donnelly', 'michael hirst', '0.72', 'june 13 , 2010']]

2008 - 09 football league one

https://en.wikipedia.org/wiki/2008%E2%80%9309_Football_League_One

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18788823-5.html.csv

unique

paul ince is the only manager whose manner of departure was signed by blackburn rovers ( mutual consent ) .

{'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'signed by blackburn rovers ( mutual consent )', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'signed by blackburn rovers ( mutual consent )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to signed by blackburn rovers ( mutual consent ) .', 'tostr': 'filter_eq { all_rows ; manner of departure ; signed by blackburn rovers ( mutual consent ) }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; manner of departure ; signed by blackburn rovers ( mutual consent ) } }', 'tointer': 'select the rows whose manner of departure record fuzzily matches to signed by blackburn rovers ( mutual consent ) . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'signed by blackburn rovers ( mutual consent )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to signed by blackburn rovers ( mutual consent ) .', 'tostr': 'filter_eq { all_rows ; manner of departure ; signed by blackburn rovers ( mutual consent ) }'}, 'outgoing manager'], 'result': 'paul ince', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; manner of departure ; signed by blackburn rovers ( mutual consent ) } ; outgoing manager }'}, 'paul ince'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; manner of departure ; signed by blackburn rovers ( mutual consent ) } ; outgoing manager } ; paul ince }', 'tointer': 'the outgoing manager record of this unqiue row is paul ince .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; manner of departure ; signed by blackburn rovers ( mutual consent ) } } ; eq { hop { filter_eq { all_rows ; manner of departure ; signed by blackburn rovers ( mutual consent ) } ; outgoing manager } ; paul ince } } = true', 'tointer': 'select the rows whose manner of departure record fuzzily matches to signed by blackburn rovers ( mutual consent ) . there is only one such row in the table . the outgoing manager record of this unqiue row is paul ince .'}

and { only { filter_eq { all_rows ; manner of departure ; signed by blackburn rovers ( mutual consent ) } } ; eq { hop { filter_eq { all_rows ; manner of departure ; signed by blackburn rovers ( mutual consent ) } ; outgoing manager } ; paul ince } } = true

select the rows whose manner of departure record fuzzily matches to signed by blackburn rovers ( mutual consent ) . there is only one such row in the table . the outgoing manager record of this unqiue row is paul ince .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'manner of departure_7': 7, 'signed by blackburn rovers (mutual consent)_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'outgoing manager_9': 9, 'paul ince_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'manner of departure_7': 'manner of departure', 'signed by blackburn rovers (mutual consent)_8': 'signed by blackburn rovers ( mutual consent )', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'outgoing manager_9': 'outgoing manager', 'paul ince_10': 'paul ince'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'manner of departure_7': [0], 'signed by blackburn rovers (mutual consent)_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'outgoing manager_9': [2], 'paul ince_10': [3]}

['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment', 'position in table']

[['milton keynes dons', 'paul ince', 'signed by blackburn rovers ( mutual consent )', '22 june 2008', 'roberto di matteo', '2 july 2008', 'pre - season'], ['cheltenham town', 'keith downing', 'mutual consent', '13 september 2008', 'martin allen', '15 september 2008', '24th'], ['colchester united', 'geraint williams', 'mutual consent', '22 september 2008', 'paul lambert', '24 september 2008', '23rd'], ['carlisle united', 'john ward', 'mutual consent', '3 november 2008', 'greg abbott', '5 december 2008', '20th'], ['huddersfield town', 'stan ternent', 'mutual consent', '4 november 2008', 'lee clark', '11 december 2008', '16th'], ['swindon town', 'maurice malpas', 'mutual consent', '14 november 2008', 'danny wilson', '26 december 2008', '16th'], ['crewe alexandra', 'steve holland', 'contract terminated', '18 november 2008', 'guðjón þórðarson', '24 december 2008', '24th'], ['hartlepool united', 'danny wilson', 'contract terminated', '15 december 2008', 'chris turner', '15 december 2008', '13th'], ['leeds united', 'gary mcallister', 'contract terminated', '21 december 2008', 'simon grayson', '23 december 2008', '9th'], ['walsall', 'jimmy mullen', 'contract terminated', '10 january 2009', 'chris hutchings', '20 january 2009', '12th'], ['leyton orient', 'martin ling', 'mutual consent', '18 january 2009', 'geraint williams', '5 february 2009', '21st'], ['yeovil town', 'russell slade', 'contract terminated', '16 february 2009', 'terry skiverton', '18 february 2009', '16th'], ['brighton & hove albion', 'micky adams', 'contract terminated', '21 february 2009', 'russell slade', '6 march 2009', '21st']]

remittance

https://en.wikipedia.org/wiki/Remittance

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2941963-1.html.csv

unique

in terms of remittances , of the countries who had remittances over 10 in 2011 , the only time the remittance was over 50 in 2010 was when the country was india .

{'scope': 'subset', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'greater_than', 'value': '50', 'subset': {'col': '5', 'criterion': 'greater_than', 'value': '10'}}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'remittances 2011', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; remittances 2011 ; 10 }', 'tointer': 'select the rows whose remittances 2011 record is greater than 10 .'}, 'remittances 2010', '50'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose remittances 2011 record is greater than 10 . among these rows , select the rows whose remittances 2010 record is greater than 50 .', 'tostr': 'filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } }', 'tointer': 'select the rows whose remittances 2011 record is greater than 10 . among these rows , select the rows whose remittances 2010 record is greater than 50 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'remittances 2011', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; remittances 2011 ; 10 }', 'tointer': 'select the rows whose remittances 2011 record is greater than 10 .'}, 'remittances 2010', '50'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose remittances 2011 record is greater than 10 . among these rows , select the rows whose remittances 2010 record is greater than 50 .', 'tostr': 'filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 }'}, 'country'], 'result': 'india', 'ind': 3, 'tostr': 'hop { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } ; country }'}, 'india'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } ; country } ; india }', 'tointer': 'the country record of this unqiue row is india .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } } ; eq { hop { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } ; country } ; india } } = true', 'tointer': 'select the rows whose remittances 2011 record is greater than 10 . among these rows , select the rows whose remittances 2010 record is greater than 50 . there is only one such row in the table . the country record of this unqiue row is india .'}

and { only { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } } ; eq { hop { filter_greater { filter_greater { all_rows ; remittances 2011 ; 10 } ; remittances 2010 ; 50 } ; country } ; india } } = true

select the rows whose remittances 2011 record is greater than 10 . among these rows , select the rows whose remittances 2010 record is greater than 50 . there is only one such row in the table . the country record of this unqiue row is india .

8

6

{'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_7': 7, 'remittances 2011_8': 8, '10_9': 9, 'remittances 2010_10': 10, '50_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'country_12': 12, 'india_13': 13}

{'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_7': 'all_rows', 'remittances 2011_8': 'remittances 2011', '10_9': '10', 'remittances 2010_10': 'remittances 2010', '50_11': '50', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'country_12': 'country', 'india_13': 'india'}

{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_greater_0': [1], 'all_rows_7': [0], 'remittances 2011_8': [0], '10_9': [0], 'remittances 2010_10': [1], '50_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'country_12': [3], 'india_13': [4]}

['country', 'remittances 2008', 'remittances 2009', 'remittances 2010', 'remittances 2011']

[['india', '49.98', '49.20', '53.48', '63.82'], ['china', '22.69', '22.90', '33.44', '40.48'], ['mexico', '26.04', '22.08', '22.08', '23.59'], ['philippines', '18.63', '19.73', '21.37', '22.97'], ['nigeria', '19.21', '18.37', '19.82', '20.62'], ['france', '16.28', '16.06', '16.71', '19.31'], ['egypt', '8.69', '7.15', '12.45', '14.32'], ['germany', '10.97', '11.30', '11.73', '13.16'], ['pakistan', '7.04', '8.72', '9.69', '12.26'], ['bangladesh', '8.93', '10.52', '10.85', '12.07'], ['belgium', '10.42', '10.44', '10.30', '10.91'], ['spain', '10.15', '8.95', '9.11', '9.91'], ['vietnam', '6.81', '6.02', '8.26', '8.60'], ['south korea', '9.07', '7.28', '7.06', '8.49']]

bojana jovanovski

https://en.wikipedia.org/wiki/Bojana_Jovanovski

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18183850-8.html.csv

count

bojana jovanovski was the winner of four of the matches she played in .

{'scope': 'all', 'criterion': 'equal', 'value': 'winner', 'result': '4', 'col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'outcome', 'winner'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose outcome record fuzzily matches to winner .', 'tostr': 'filter_eq { all_rows ; outcome ; winner }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; outcome ; winner } }', 'tointer': 'select the rows whose outcome record fuzzily matches to winner . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; outcome ; winner } } ; 4 } = true', 'tointer': 'select the rows whose outcome record fuzzily matches to winner . the number of such rows is 4 .'}

eq { count { filter_eq { all_rows ; outcome ; winner } } ; 4 } = true

select the rows whose outcome record fuzzily matches to winner . 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, 'outcome_5': 5, 'winner_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', 'outcome_5': 'outcome', 'winner_6': 'winner', '4_7': '4'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'outcome_5': [0], 'winner_6': [0], '4_7': [2]}

['outcome', 'date', 'tournament', 'surface', 'opponent', 'score']

[['winner', '7 july 2008', 'prokuplje , serbia', 'clay', 'karin morgošová', '6 - 0 , 6 - 1'], ['winner', '18 august 2008', 'vinkovci , croatia', 'clay', 'zorica petrov', '6 - 1 , 6 - 3'], ['winner', '1 september 2008', 'brčko , bosnia and herzegovina', 'clay', 'gracia radovanović', '6 - 4 , 3 - 6 , 6 - 2'], ['runner - up', '27 december 2008', 'delhi , india', 'hard', 'sandra záhlavová', '4 - 6 , 3 - 6'], ['runner - up', '16 november 2009', 'pune , india', 'hard', 'rika fujiwara', '7 - 5 , 4 - 6 , 3 - 6'], ['runner - up', '23 november 2009', 'toyota , japan', 'carpet ( i )', 'kimiko date - krumm', '5 - 7 , 2 - 6'], ['runner - up', '13 december 2010', 'dubai , united arab emirates', 'clay', 'sania mirza', '6 - 4 , 3 - 6 , 0 - 6'], ['winner', '20 december 2010', 'pune , india', 'hard', 'nina bratchikova', '6 - 4 , 6 - 4']]

tri - eastern conference ( ihsaa )

https://en.wikipedia.org/wiki/Tri-Eastern_Conference_%28IHSAA%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18973139-1.html.csv

aggregation

the average size for schools in the tri-eastern conference was 408.4 .

{'scope': 'all', 'col': '4', 'type': 'average', 'result': '408.4', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'size'], 'result': '408.4', 'ind': 0, 'tostr': 'avg { all_rows ; size }'}, '408.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; size } ; 408.4 } = true', 'tointer': 'the average of the size record of all rows is 408.4 .'}

round_eq { avg { all_rows ; size } ; 408.4 } = true

the average of the size record of all rows is 408.4 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'size_4': 4, '408.4_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'size_4': 'size', '408.4_5': '408.4'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'size_4': [0], '408.4_5': [1]}

['school', 'location', 'mascot', 'size', 'ihsaa class', 'county', 'year joined', 'previous conference']

[['cambridge city lincoln', 'cambridge city', 'golden eagles', '367', 'aa', '89 wayne', '1965', 'none ( new school )'], ['centerville', 'centerville', 'bulldogs', '530', 'aa', '89 wayne', '1962', 'east central'], ['hagerstown', 'hagerstown', 'tigers', '401', 'aa', '89 wayne', '1966', 'mississinewa valley'], ['northeastern', 'fountain city', 'knights', '379', 'aa', '89 wayne', '1974', 'mid - eastern'], ['tri', 'straughn', 'titans', '274', 'a', '33 henry', '1989', 'big blue river'], ['union city community', 'union city', 'indians', '287', 'a', '68 randolph', '1962', 'east central'], ['union county', 'liberty', 'patriots', '535', 'aa', '81 union', '1973', 'none ( new school )'], ['winchester community', 'winchester', 'golden falcons', '494', 'aa', '68 randolph', '1972', 'mississinewa valley']]

atlantic coast collegiate hockey league

https://en.wikipedia.org/wiki/Atlantic_Coast_Collegiate_Hockey_League

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16403890-1.html.csv

majority

the majority of the members of the atlantic coast collegiate hockey league are private institutions .

{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'private', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'affiliation', 'private'], 'result': True, 'ind': 0, 'tointer': 'for the affiliation records of all rows , most of them fuzzily match to private .', 'tostr': 'most_eq { all_rows ; affiliation ; private } = true'}

most_eq { all_rows ; affiliation ; private } = true

for the affiliation records of all rows , most of them fuzzily match to private .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'affiliation_3': 3, 'private_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'affiliation_3': 'affiliation', 'private_4': 'private'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'affiliation_3': [0], 'private_4': [0]}

['institution', 'location', 'founded', 'affiliation', 'enrollment', 'team nickname', 'primary conference', 'home rink']

[['duke university', 'durham , nc', '1838', 'private / non - sectarian', '6496', 'blue devils', 'atlantic coast conference ( d - i )', 'triangle sports plex'], ['elon university', 'elon , nc', '1889', 'private', '5225', 'phoenix', 'southern conference ( d - i )', 'triangle sports plex / greensboro ice house'], ['georgetown university', 'washington , dc', '1789', 'private / catholic', '13612', 'hoyas', 'big east conference ( d - i )', 'kettler capitals iceplex'], ['george washington university', 'washington , dc', '1821', 'private', '6655', 'colonials', 'atlantic 10 conference ( d - i )', 'fort dupont ice arena / kettler capitals iceplex'], ['university of north carolina', 'chapel hill , nc', '1789', 'public', '17895', 'tar heels', 'atlantic coast conference ( d - i )', 'triangle sports plex'], ['north carolina state university', 'raleigh , nc', '1887', 'public', '24741', 'wolfpack', 'atlantic coast conference ( d - i )', 'raleigh center ice']]

1994 arizona cardinals season

https://en.wikipedia.org/wiki/1994_Arizona_Cardinals_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16714815-1.html.csv

superlative

the highest attendance during the 1994 season was when the arizona cardinals played against the new york giants .

{'scope': 'all', 'col_superlative': '5', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'november 13 , 1994', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'november 13 , 1994'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; november 13 , 1994 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is november 13 , 1994 .'}

eq { hop { argmax { all_rows ; attendance } ; date } ; november 13 , 1994 } = true

select the row whose attendance record of all rows is maximum . the date record of this row is november 13 , 1994 .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, 'november 13 , 1994_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'date_6': 'date', 'november 13 , 1994_7': 'november 13 , 1994'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'november 13 , 1994_7': [2]}

['week', 'date', 'opponent', 'result', 'attendance']

[['1', 'september 4 , 1994', 'los angeles rams', 'l 14 - 12', '32969'], ['2', 'september 11 , 1994', 'new york giants', 'l 20 - 17', '60066'], ['3', 'september 18 , 1994', 'cleveland browns', 'l 32 - 0', '62818'], ['5', 'october 2 , 1994', 'minnesota vikings', 'w 17 - 7', '67950'], ['6', 'october 9 , 1994', 'dallas cowboys', 'l 38 - 3', '64518'], ['7', 'october 16 , 1994', 'washington redskins', 'w 19 - 16', '50019'], ['8', 'october 23 , 1994', 'dallas cowboys', 'l 28 - 21', '71023'], ['9', 'october 30 , 1994', 'pittsburgh steelers', 'w 20 - 17', '65690'], ['10', 'november 6 , 1994', 'philadelphia eagles', 'l 17 - 7', '64952'], ['11', 'november 13 , 1994', 'new york giants', 'w 10 - 9', '71719'], ['12', 'november 20 , 1994', 'philadelphia eagles', 'w 12 - 6', '62779'], ['13', 'november 27 , 1994', 'chicago bears', 'l 19 - 16', '65922'], ['14', 'december 4 , 1994', 'houston oilers', 'w 30 - 12', '39821'], ['15', 'december 11 , 1994', 'washington redskins', 'w 17 - 15', '53790'], ['16', 'december 18 , 1994', 'cincinnati bengals', 'w 28 - 7', '50110'], ['17', 'december 24 , 1994', 'atlanta falcons', 'l 10 - 6', '35311']]

1991 - 92 seattle supersonics season

https://en.wikipedia.org/wiki/1991%E2%80%9392_Seattle_SuperSonics_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27902171-5.html.csv

unique

the seattle supersonics game on december 26 was the only one with an overtime ( ot ) .

{'scope': 'all', 'row': '12', 'col': '4', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'ot', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'ot'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to ot .', 'tostr': 'filter_eq { all_rows ; score ; ot }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; score ; ot } }', 'tointer': 'select the rows whose score record fuzzily matches to ot . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'ot'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to ot .', 'tostr': 'filter_eq { all_rows ; score ; ot }'}, 'date'], 'result': 'december 26', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score ; ot } ; date }'}, 'december 26'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; score ; ot } ; date } ; december 26 }', 'tointer': 'the date record of this unqiue row is december 26 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; score ; ot } } ; eq { hop { filter_eq { all_rows ; score ; ot } ; date } ; december 26 } } = true', 'tointer': 'select the rows whose score record fuzzily matches to ot . there is only one such row in the table . the date record of this unqiue row is december 26 .'}

and { only { filter_eq { all_rows ; score ; ot } } ; eq { hop { filter_eq { all_rows ; score ; ot } ; date } ; december 26 } } = true

select the rows whose score record fuzzily matches to ot . there is only one such row in the table . the date record of this unqiue row is december 26 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score_7': 7, 'ot_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'december 26_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score_7': 'score', 'ot_8': 'ot', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'december 26_10': 'december 26'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], 'ot_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'december 26_10': [3]}

['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']

[['16', 'december 3', 'washington bullets', 'w 91 - 90', 'r pierce ( 26 )', 's kemp ( 12 )', 'g payton ( 5 )', 'seattle center coliseum 10957', '9 - 7'], ['17', 'december 6', 'minnesota timberwolves', 'w 96 - 94', 'r pierce ( 29 )', 'm cage ( 23 )', 'g payton , r pierce ( 5 )', 'seattle center coliseum 9796', '10 - 7'], ['18', 'december 7', 'dallas mavericks', 'w 104 - 101', 'r pierce ( 27 )', 'm cage ( 14 )', 'n mcmillan ( 6 )', 'seattle center coliseum 12313', '11 - 7'], ['19', 'december 10', 'chicago bulls', 'l 103 - 108', 'r pierce ( 30 )', 'm cage ( 13 )', 's kemp , g payton ( 5 )', 'chicago stadium 18061', '11 - 8'], ['20', 'december 11', 'new york knicks', 'l 87 - 96', 'r pierce ( 25 )', 'b benjamin , s kemp ( 9 )', 'r pierce ( 7 )', 'madison square garden 14934', '11 - 9'], ['21', 'december 13', 'boston celtics', 'l 97 - 117', 'r pierce ( 21 )', 'b benjamin ( 8 )', 'n mcmillan ( 8 )', 'boston garden 14890', '11 - 10'], ['22', 'december 14', 'philadelphia 76ers', 'l 95 - 104', 'b benjamin ( 23 )', 'b benjamin ( 9 )', 'n mcmillan ( 8 )', 'the spectrum 12395', '11 - 11'], ['23', 'december 17', 'los angeles clippers', 'w 116 - 99', 'b benjamin ( 20 )', 'm cage ( 13 )', 'n mcmillan ( 6 )', 'seattle center coliseum 10357', '12 - 11'], ['24', 'december 19', 'denver nuggets', 'w 119 - 106', 'r pierce ( 29 )', 'm cage ( 15 )', 'd mckey , n mcmillan , g payton ( 4 )', 'seattle center coliseum 10663', '13 - 11'], ['25', 'december 21', 'golden state warriors', 'w 120 - 112', 'r pierce ( 34 )', 'g payton ( 11 )', 'g payton ( 12 )', 'seattle center coliseum 14180', '14 - 11'], ['26', 'december 22', 'portland trail blazers', 'l 87 - 96', 'b benjamin ( 18 )', 'm cage ( 9 )', 'b kofoed , g payton ( 5 )', 'memorial coliseum 12888', '14 - 12'], ['27', 'december 26', 'sacramento kings', 'w 115 - 106 ( ot )', 'r pierce ( 27 )', 'b benjamin ( 13 )', 'g payton ( 5 )', 'arco arena 17014', '15 - 12']]

list of supernanny episodes

https://en.wikipedia.org/wiki/List_of_Supernanny_episodes

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19897294-8.html.csv

majority

most of the supernanny episodes in the series originally aired in february .

{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'february', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'original air date', 'february'], 'result': True, 'ind': 0, 'tointer': 'for the original air date records of all rows , most of them fuzzily match to february .', 'tostr': 'most_eq { all_rows ; original air date ; february } = true'}

most_eq { all_rows ; original air date ; february } = true

for the original air date records of all rows , most of them fuzzily match to february .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'original air date_3': 3, 'february_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'original air date_3': 'original air date', 'february_4': 'february'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'original air date_3': [0], 'february_4': [0]}

['no overall', 'no in series', 'family / families', 'location ( s )', 'original air date']

[['uk30', '1', 'the hussain family and the philip family', 'leeds & dorset', '9 february 2010'], ['uk31', '2', 'the ward family and the wren family', 'blackpool & glasgow', '16 february 2010'], ['uk32', '3', 'the coughlan family and the dumbleton family', 'west london & manchester', '23 february 2010'], ['uk33', '4', 'the mccloud family and the griffin family', 'nottingham & birmingham', '2 march 2010'], ['uk34', '5', 'the simmons family', 'north london', '9 march 2010']]

1926 vfl season

https://en.wikipedia.org/wiki/1926_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746808-5.html.csv

ordinal

the match between essendon and st. kilda had the third biggest crowd of any match .

{'row': '2', 'col': '6', 'order': '3', 'col_other': '2,3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 3 }'}, 'home team score'], 'result': '13.7 ( 85 )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 3 } ; home team score }'}, '13.7 ( 85 )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 3 } ; home team score } ; 13.7 ( 85 ) }', 'tointer': 'select the row whose crowd record of all rows is 3rd maximum . the home team score record of this row is 13.7 ( 85 ) .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 3 }'}, 'away team'], 'result': 'st kilda', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 3 } ; away team }'}, 'st kilda'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 3 } ; away team } ; st kilda }', 'tointer': 'the away team record of this row is st kilda .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { nth_argmax { all_rows ; crowd ; 3 } ; home team score } ; 13.7 ( 85 ) } ; eq { hop { nth_argmax { all_rows ; crowd ; 3 } ; away team } ; st kilda } } = true', 'tointer': 'select the row whose crowd record of all rows is 3rd maximum . the home team score record of this row is 13.7 ( 85 ) . the away team record of this row is st kilda .'}

and { eq { hop { nth_argmax { all_rows ; crowd ; 3 } ; home team score } ; 13.7 ( 85 ) } ; eq { hop { nth_argmax { all_rows ; crowd ; 3 } ; away team } ; st kilda } } = true

select the row whose crowd record of all rows is 3rd maximum . the home team score record of this row is 13.7 ( 85 ) . the away team record of this row is st kilda .

7

6

{'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_7': 7, 'crowd_8': 8, '3_9': 9, 'home team score_10': 10, '13.7 (85)_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'away team_12': 12, 'st kilda_13': 13}

{'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_7': 'all_rows', 'crowd_8': 'crowd', '3_9': '3', 'home team score_10': 'home team score', '13.7 (85)_11': '13.7 ( 85 )', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'away team_12': 'away team', 'st kilda_13': 'st kilda'}

{'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'nth_argmax_0': [1, 3], 'all_rows_7': [0], 'crowd_8': [0], '3_9': [0], 'home team score_10': [1], '13.7 (85)_11': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'away team_12': [3], 'st kilda_13': [4]}

['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']

[['melbourne', '19.8 ( 122 )', 'richmond', '12.17 ( 89 )', 'mcg', '28628', '29 may 1926'], ['essendon', '13.7 ( 85 )', 'st kilda', '5.8 ( 38 )', 'windy hill', '20000', '29 may 1926'], ['south melbourne', '10.15 ( 75 )', 'north melbourne', '11.7 ( 73 )', 'lake oval', '15000', '29 may 1926'], ['hawthorn', '9.13 ( 67 )', 'footscray', '14.16 ( 100 )', 'glenferrie oval', '10000', '29 may 1926'], ['geelong', '9.14 ( 68 )', 'collingwood', '10.15 ( 75 )', 'corio oval', '19500', '29 may 1926'], ['fitzroy', '7.16 ( 58 )', 'carlton', '7.6 ( 48 )', 'brunswick street oval', '25000', '29 may 1926']]

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

unique

superstars is the only programme whose original channel was bbc one .

{'scope': 'all', 'row': '4', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'bbc one', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original channel', 'bbc one'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original channel record fuzzily matches to bbc one .', 'tostr': 'filter_eq { all_rows ; original channel ; bbc one }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; original channel ; bbc one } }', 'tointer': 'select the rows whose original channel record fuzzily matches to bbc one . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original channel', 'bbc one'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original channel record fuzzily matches to bbc one .', 'tostr': 'filter_eq { all_rows ; original channel ; bbc one }'}, 'programme'], 'result': 'superstars', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; original channel ; bbc one } ; programme }'}, 'superstars'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; original channel ; bbc one } ; programme } ; superstars }', 'tointer': 'the programme record of this unqiue row is superstars .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; original channel ; bbc one } } ; eq { hop { filter_eq { all_rows ; original channel ; bbc one } ; programme } ; superstars } } = true', 'tointer': 'select the rows whose original channel record fuzzily matches to bbc one . there is only one such row in the table . the programme record of this unqiue row is superstars .'}

and { only { filter_eq { all_rows ; original channel ; bbc one } } ; eq { hop { filter_eq { all_rows ; original channel ; bbc one } ; programme } ; superstars } } = true

select the rows whose original channel record fuzzily matches to bbc one . there is only one such row in the table . the programme record of this unqiue row is superstars .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'original channel_7': 7, 'bbc one_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'programme_9': 9, 'superstars_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'original channel_7': 'original channel', 'bbc one_8': 'bbc one', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'programme_9': 'programme', 'superstars_10': 'superstars'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'original channel_7': [0], 'bbc one_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'programme_9': [2], 'superstars_10': [3]}

['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', '2005', 'bbc one', 'july 2008', 'five'], ["it 'll be alright on the night", '18 march 2006', 'itv', '20 september 2008', 'n / a ( same channel as original )']]

list of how it 's made episodes

https://en.wikipedia.org/wiki/List_of_How_It%27s_Made_episodes

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15187735-19.html.csv

superlative

episode 235 was the first of these episodes to have aired .

{'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None}

{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'series ep'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; series ep }'}, 'episode'], 'result': '235', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; series ep } ; episode }'}, '235'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; series ep } ; episode } ; 235 } = true', 'tointer': 'select the row whose series ep record of all rows is minimum . the episode record of this row is 235 .'}

eq { hop { argmin { all_rows ; series ep } ; episode } ; 235 } = true

select the row whose series ep record of all rows is minimum . the episode record of this row is 235 .

3

3

{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'series ep_5': 5, 'episode_6': 6, '235_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'series ep_5': 'series ep', 'episode_6': 'episode', '235_7': '235'}

{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'series ep_5': [0], 'episode_6': [1], '235_7': [2]}

['series ep', 'episode', 'segment a', 'segment b', 'segment c', 'segment d']

[['19 - 01', '235', 'garden forks', 'english toffee', 'paint chip cards', 'bundt s pan'], ['19 - 02', '236', 'pewter flasks', 'potato salad', 'hydrogen s fuel cell', 'engineered wood siding'], ['19 - 03', '237', 'canvas wall s tent', 's peace pipe', 'shredded wheat cereal', 's cannon'], ['19 - 04', '238', 'ic robot ing hunt s decoy', 'canned tomatoes', 's scoreboard', 's lasso'], ['19 - 05', '239', 'turf grass', 'beef jerky', 'wood chippers', 'bowling pins'], ['19 - 06', '240', 's multi - tool', 'jojoba oil', 's marionette ( part 1 )', 's marionette ( part 2 )'], ['19 - 07', '241', 'fish decoys', 'film digitization', 'cylinder stoves', 'concrete light poles'], ['19 - 08', '242', 'bamboo bicycles', 'chainsaw art', 'breath mints', 'manual motorcycle transmissions'], ['19 - 09', '243', 'dinnerware', 'air brake tanks', 'frosted cereal', 's fossil'], ['19 - 10', '244', 'clay', 'pitted prunes', 's spur', 'polyurethane tires'], ['19 - 11', '245', 's taser', 'canned soup', 'jaw harps & mouth bows', 's diving board'], ['19 - 12', '246', 'navajo rugs', 'crude oil', 's kaleidoscope', 'titanium dental implants']]

vietnam open ( badminton )

https://en.wikipedia.org/wiki/Vietnam_Open_%28badminton%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14194250-1.html.csv

unique

2006 was the only year that the men 's singles of the vietnam open was won by andrew smith .

{'scope': 'all', 'row': '4', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'andrew smith', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', "men 's singles", 'andrew smith'], 'result': None, 'ind': 0, 'tointer': "select the rows whose men 's singles record fuzzily matches to andrew smith .", 'tostr': "filter_eq { all_rows ; men 's singles ; andrew smith }"}], 'result': True, 'ind': 1, 'tostr': "only { filter_eq { all_rows ; men 's singles ; andrew smith } }", 'tointer': "select the rows whose men 's singles record fuzzily matches to andrew smith . there is only one such row in the table ."}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', "men 's singles", 'andrew smith'], 'result': None, 'ind': 0, 'tointer': "select the rows whose men 's singles record fuzzily matches to andrew smith .", 'tostr': "filter_eq { all_rows ; men 's singles ; andrew smith }"}, 'year'], 'result': '2006', 'ind': 2, 'tostr': "hop { filter_eq { all_rows ; men 's singles ; andrew smith } ; year }"}, '2006'], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; men 's singles ; andrew smith } ; year } ; 2006 }", 'tointer': 'the year record of this unqiue row is 2006 .'}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; men 's singles ; andrew smith } } ; eq { hop { filter_eq { all_rows ; men 's singles ; andrew smith } ; year } ; 2006 } } = true", 'tointer': "select the rows whose men 's singles record fuzzily matches to andrew smith . there is only one such row in the table . the year record of this unqiue row is 2006 ."}

and { only { filter_eq { all_rows ; men 's singles ; andrew smith } } ; eq { hop { filter_eq { all_rows ; men 's singles ; andrew smith } ; year } ; 2006 } } = true

select the rows whose men 's singles record fuzzily matches to andrew smith . there is only one such row in the table . the year record of this unqiue row is 2006 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, "men 's singles_7": 7, 'andrew smith_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'year_9': 9, '2006_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', "men 's singles_7": "men 's singles", 'andrew smith_8': 'andrew smith', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'year_9': 'year', '2006_10': '2006'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], "men 's singles_7": [0], 'andrew smith_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'year_9': [2], '2006_10': [3]}

['year', "men 's singles", "women 's singles", "men 's doubles", "women 's doubles", 'mixed doubles']

[['1996', 'nunung subandoro', 'zheng yaqiong', 'choong tan fook lee wan wah', 'peng xingyong zhang jin', 'liu yong zhang jin'], ['1997', 'chen gang', 'susi susanti', 'ricky subagja rexy mainaky', 'eliza nathanael zelin resiana', 'bambang supriyanto riseu rosalina'], ['1998 2005', 'no competition', 'no competition', 'no competition', 'no competition', 'no competition'], ['2006', 'andrew smith', 'bae seung - hee', 'yoo yeon - seong jeon jun - bum', 'kim jin - ock lee jung - mi', 'yoo yeon - seong lee jung - mi'], ['2007', 'roslin hashim', 'zhu jingjing', 'kwon yi - goo ko sung - hyun', 'natalia poluakan yulianti', 'tontowi ahmad yulianti'], ['2008', 'nguyen tien minh', 'zhang beiwen', 'choong tan fook lee wan wah', 'shendy puspa irawati meiliana jauhari', 'tontowi ahmad shendy puspa irawati'], ['2009', 'nguyen tien minh', 'fransisca ratnasari', 'luluk hadiyanto joko riyadi', 'anneke feinya agustin annisa wahyuni', 'flandy limpele cheng wen - hsing'], ['2010', 'chen yuekun', 'ratchanok inthanon', 'mohammad ahsan bona septano', 'ma jin zhong qianxin', 'he hanbin ma jin'], ['2011', 'nguyen tien minh', 'fu mingtian', 'angga pratama ryan agung saputra', 'anneke feinya agustin nitya krishinda maheswari', 'vitaliy durkin nina vislova'], ['2012', 'nguyen tien minh', 'porntip buranaprasertsuk', 'bodin issara maneepong jongjit', 'pia zebadiah rizki amelia pradipta', 'markis kido pia zebadiah']]

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/2-17231232-5.html.csv

aggregation

all the players of the 1986 u.s. open ( golf ) tournament had an average score of around 143 .

{'scope': 'all', 'col': '4', 'type': 'average', 'result': '143', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '143', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '143'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 143 } = true', 'tointer': 'the average of the score record of all rows is 143 .'}

round_eq { avg { all_rows ; score } ; 143 } = true

the average of the score record of all rows is 143 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '143_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '143_5': '143'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '143_5': [1]}

['place', 'player', 'country', 'score', 'to par']

[['1', 'greg norman', 'australia', '71 + 68 = 139', '1'], ['t2', 'lee trevino', 'united states', '74 + 68 = 142', '+ 2'], ['t2', 'denis watson', 'zimbabwe', '72 + 70 = 142', '+ 2'], ['t4', 'raymond floyd', 'united states', '75 + 68 = 143', '+ 3'], ['t4', 'bob tway', 'united states', '70 + 73 = 143', '+ 3'], ['t4', 'tom watson', 'united states', '72 + 71 = 143', '+ 3'], ['t7', 'david frost', 'south africa', '72 + 72 = 144', '+ 4'], ['t7', 'bernhard langer', 'west germany', '74 + 70 = 144', '+ 4'], ['t7', 'tsuneyuki nakajima', 'japan', '72 + 72 = 144', '+ 4'], ['t7', "mac o'grady", 'united states', '75 + 69 = 144', '+ 4'], ['t7', 'payne stewart', 'united states', '76 + 68 = 144', '+ 4'], ['t7', 'bobby wadkins', 'united states', '75 + 69 = 144', '+ 4'], ['t7', 'lanny wadkins', 'united states', '74 + 70 = 144', '+ 4']]

peruvian segunda división

https://en.wikipedia.org/wiki/Peruvian_Segunda_Divisi%C3%B3n

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12335018-1.html.csv

majority

the majority of the stadiums have a capacity of over 10,000 .

{'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10,000', 'subset': None}

{'func': 'most_greater', 'args': ['all_rows', 'capacity', '10,000'], 'result': True, 'ind': 0, 'tointer': 'for the capacity records of all rows , most of them are greater than 10,000 .', 'tostr': 'most_greater { all_rows ; capacity ; 10,000 } = true'}

most_greater { all_rows ; capacity ; 10,000 } = true

for the capacity 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, 'capacity_3': 3, '10,000_4': 4}

{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'capacity_3': 'capacity', '10,000_4': '10,000'}

{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'capacity_3': [0], '10,000_4': [0]}

['team', 'city', 'founded', 'first season in segunda división', 'first season of current spell in segunda división', 'stadium', 'capacity', 'field', 'top division titles', 'last top division title']

[['alfonso ugarte', 'puno', '1928', '2006', '2013', 'enrique torres belón', '20000', 'grass', '0', '-'], ['alianza universidad', 'huánuco', '1939', '2012', '2012', 'heraclio tapia', '15000', 'grass', '0', '-'], ['atlético minero', 'matucana', '1997', '2006', '2009', 'municipal de matucana', '5000', 'grass', '0', '-'], ['atlético torino', 'talara', '1946', '2009', '2009', 'campeonísimo', '8000', 'grass', '0', '-'], ['defensor san alejandro', 'aguaytía', '1969', '2013', '2013', 'aliardo soria pérez', '13000', 'grass', '0', '-'], ['deportivo coopsol', 'chancay', '1964', '1999', '1999', 'rómulo shaw cisneros', '13000', 'grass', '1', '2000'], ['deportivo municipal', 'lima', '1935', '1968', '2013', 'miguel grau', '15000', 'grass', '2', '2006'], ['sport boys', 'callao', '1927', '1988', '2013', 'miguel grau', '15000', 'grass', '2', '2009'], ['sport victoria', 'ica', '1919', '2013', '2013', 'max augustín', '24576', 'grass', '0', '-'], ['sportivo huracán', 'arequipa', '1927', '2013', '2013', 'mariano melgar', '20000', 'grass', '0', '-'], ['walter ormeño', 'cañete', '1950', '1988', '2013', 'oscar ramos cabieses', '8000', 'grass', '0', '-']]

1995 wta tour

https://en.wikipedia.org/wiki/1995_WTA_Tour

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15866312-10.html.csv

count

the 1995 wta tour featured four matches on 2 october , 1995 .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2 october', 'result': '4', 'col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'week of', '2 october'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose week of record fuzzily matches to 2 october .', 'tostr': 'filter_eq { all_rows ; week of ; 2 october }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; week of ; 2 october } }', 'tointer': 'select the rows whose week of record fuzzily matches to 2 october . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; week of ; 2 october } } ; 4 } = true', 'tointer': 'select the rows whose week of record fuzzily matches to 2 october . the number of such rows is 4 .'}

eq { count { filter_eq { all_rows ; week of ; 2 october } } ; 4 } = true

select the rows whose week of record fuzzily matches to 2 october . 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, 'week of_5': 5, '2 october_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', 'week of_5': 'week of', '2 october_6': '2 october', '4_7': '4'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'week of_5': [0], '2 october_6': [0], '4_7': [2]}

['week of', 'tier', 'winner', 'runner - up', 'semi finalists']

[['2 october', 'tier iv', 'shi - ting wang 6 - 1 , 6 - 1', 'jing - qian yi', 'tina križan annabel ellwood'], ['2 october', 'tier iv', 'petra kamstra tina križan 2 - 6 , 6 - 4 , 6 - 1', 'nana miyagi stephanie reece', 'tina križan annabel ellwood'], ['2 october', 'tier i', 'iva majoli 6 - 4 , 6 - 4', 'mary pierce', 'chanda rubin mariaan de swardt'], ['2 october', 'tier i', 'nicole arendt manon bollegraf 6 - 4 , 6 - 7 , 6 - 4', 'chanda rubin caroline vis', 'chanda rubin mariaan de swardt'], ['9 october', 'tier ii', 'iva majoli 6 - 4 , 7 - 6', 'gabriela sabatini', 'anke huber chanda rubin'], ['9 october', 'tier ii', 'gigi fernández natalia zvereva 5 - 7 , 6 - 1 , 6 - 4', 'meredith mcgrath larisa savchenko', 'anke huber chanda rubin'], ['17 october', 'tier ii', 'mary joe fernández 6 - 4 , 7 - 5', 'amanda coetzer', 'kristie boogert magdalena maleeva'], ['17 october', 'tier ii', 'meredith mcgrath larisa savchenko 7 - 5 , 6 - 1', 'lori mcneil helena suková', 'kristie boogert magdalena maleeva'], ['30 october', 'tier iii', 'brenda schultz - mccarthy 7 - 6 , 6 - 2', 'dominique monami', 'lindsay lee rennae stubbs'], ['30 october', 'tier iii', 'nicole arendt manon bollegraf 7 - 6 , 4 - 6 , 6 - 2', 'lisa raymond rennae stubbs', 'lindsay lee rennae stubbs'], ['30 october', 'tier ii', 'magdalena maleeva 6 - 3 , 6 - 4', 'ai sugiyama', 'lindsay davenport mary joe fernández'], ['30 october', 'tier ii', 'lori mcneil helena suková 3 - 6 , 6 - 4 , 6 - 3', 'katrina adams zina garrison - jackson', 'lindsay davenport mary joe fernández']]

1982 denver broncos season

https://en.wikipedia.org/wiki/1982_Denver_Broncos_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17928444-1.html.csv

superlative

the game on week 14 was the highest attended game in the 1982 denver broncos season .

{'scope': 'all', 'col_superlative': '7', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'week'], 'result': '14', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; week }'}, '14'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; week } ; 14 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the week record of this row is 14 .'}

eq { hop { argmax { all_rows ; attendance } ; week } ; 14 } = true

select the row whose attendance record of all rows is maximum . the week record of this row is 14 .

3

3

{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'week_6': 6, '14_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'week_6': 'week', '14_7': '14'}

{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'week_6': [1], '14_7': [2]}

['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance']

[['1', 'september 12', 'san diego chargers', 'l 3 - 23', 'mile high stadium', '0 - 1', '73564'], ['2', 'september 19', 'san francisco 49ers', 'w 24 - 21', 'mile high stadium', '1 - 1', '73899'], ['10', 'november 21', 'seattle seahawks', 'l 10 - 17', 'mile high stadium', '1 - 2', '73996'], ['11', 'november 28', 'san diego chargers', 'l 20 - 30', 'jack murphy stadium', '1 - 3', '47629'], ['12', 'december 5', 'atlanta falcons', 'l 27 - 34', 'mile high stadium', '1 - 4', '73984'], ['13', 'december 12', 'los angeles rams', 'w 27 - 24', 'anaheim stadium', '2 - 4', '48112'], ['14', 'december 19', 'kansas city chiefs', 'l 16 - 37', 'mile high stadium', '2 - 5', '74192'], ['15', 'december 26', 'los angeles raiders', 'l 10 - 27', 'los angeles memorial coliseum', '2 - 6', '44160'], ['16', 'january 2', 'seattle seahawks', 'l 11 - 13', 'kingdome', '2 - 7', '43145']]

united states house of representatives elections , 1996

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1996

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341472-45.html.csv

unique

at the united states house of representatives elections-1996 , only one incubment from republican party retired .

{'scope': 'subset', 'row': '2', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'retired', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'republican'}}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; party ; republican }', 'tointer': 'select the rows whose party record fuzzily matches to republican .'}, 'result', 'retired'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose party record fuzzily matches to republican . among these rows , select the rows whose result record fuzzily matches to retired .', 'tostr': 'filter_eq { filter_eq { all_rows ; party ; republican } ; result ; retired }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; retired } }', 'tointer': 'select the rows whose party record fuzzily matches to republican . among these rows , select the rows whose result record fuzzily matches to retired . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; party ; republican }', 'tointer': 'select the rows whose party record fuzzily matches to republican .'}, 'result', 'retired'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose party record fuzzily matches to republican . among these rows , select the rows whose result record fuzzily matches to retired .', 'tostr': 'filter_eq { filter_eq { all_rows ; party ; republican } ; result ; retired }'}, 'incumbent'], 'result': 'jack fields', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; retired } ; incumbent }'}, 'jack fields'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; retired } ; incumbent } ; jack fields }', 'tointer': 'the incumbent record of this unqiue row is jack fields .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; retired } } ; eq { hop { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; retired } ; incumbent } ; jack fields } } = true', 'tointer': 'select the rows whose party record fuzzily matches to republican . among these rows , select the rows whose result record fuzzily matches to retired . there is only one such row in the table . the incumbent record of this unqiue row is jack fields .'}

and { only { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; retired } } ; eq { hop { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; retired } ; incumbent } ; jack fields } } = true

select the rows whose party record fuzzily matches to republican . among these rows , select the rows whose result record fuzzily matches to retired . there is only one such row in the table . the incumbent record of this unqiue row is jack fields .

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, 'party_8': 8, 'republican_9': 9, 'result_10': 10, 'retired_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'incumbent_12': 12, 'jack fields_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', 'party_8': 'party', 'republican_9': 'republican', 'result_10': 'result', 'retired_11': 'retired', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'incumbent_12': 'incumbent', 'jack fields_13': 'jack fields'}

{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'party_8': [0], 'republican_9': [0], 'result_10': [1], 'retired_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'incumbent_12': [3], 'jack fields_13': [4]}

['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']

[['texas 5', 'john bryant', 'democratic', '1982', 'retired to run for us senate republican gain', 'pete sessions ( r ) 53.07 % john pouland ( d ) 46.93 %'], ['texas 8', 'jack fields', 'republican', '1980', 'retired republican hold', 'kevin brady ( r ) 59.11 % gene fontenot ( d ) 40.89 %'], ['texas 9', 'steve stockman', 'republican', '1994', 'lost re - election democratic gain', 'nick lampson ( d ) 52.83 % steve stockman ( r ) 47.16 %'], ['texas 19', 'larry combest', 'republican', '1984', 're - elected', 'larry combest ( r ) 80.37 % john sawyer ( d ) 19.63 %'], ['texas 22', 'tom delay', 'republican', '1984', 're - elected', 'tom delay ( r ) 68.11 % scott cunningham ( d ) 31.89 %']]

1960 vfl season

https://en.wikipedia.org/wiki/1960_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10775890-14.html.csv

count

in the 1960 vfl season , among the games where home team scored below 10.00 , two of them had attendance above 16,000 people .

{'scope': 'subset', 'criterion': 'greater_than', 'value': '16000', 'result': '2', 'col': '6', 'subset': {'col': '2', 'criterion': 'less_than', 'value': '10.0'}}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'home team score', '10.0'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; home team score ; 10.0 }', 'tointer': 'select the rows whose home team score record is less than 10.0 .'}, 'crowd', '16000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team score record is less than 10.0 . among these rows , select the rows whose crowd record is greater than 16000 .', 'tostr': 'filter_greater { filter_less { all_rows ; home team score ; 10.0 } ; crowd ; 16000 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_less { all_rows ; home team score ; 10.0 } ; crowd ; 16000 } }', 'tointer': 'select the rows whose home team score record is less than 10.0 . among these rows , select the rows whose crowd record is greater than 16000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_less { all_rows ; home team score ; 10.0 } ; crowd ; 16000 } } ; 2 } = true', 'tointer': 'select the rows whose home team score record is less than 10.0 . among these rows , select the rows whose crowd record is greater than 16000 . the number of such rows is 2 .'}

eq { count { filter_greater { filter_less { all_rows ; home team score ; 10.0 } ; crowd ; 16000 } } ; 2 } = true

select the rows whose home team score record is less than 10.0 . among these rows , select the rows whose crowd record is greater than 16000 . the number of such rows is 2 .

4

4

{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'home team score_6': 6, '10.0_7': 7, 'crowd_8': 8, '16000_9': 9, '2_10': 10}

{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'home team score_6': 'home team score', '10.0_7': '10.0', 'crowd_8': 'crowd', '16000_9': '16000', '2_10': '2'}

{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'home team score_6': [0], '10.0_7': [0], 'crowd_8': [1], '16000_9': [1], '2_10': [3]}

['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']

[['footscray', '5.9 ( 39 )', 'hawthorn', '9.21 ( 75 )', 'western oval', '16794', '30 july 1960'], ['collingwood', '9.11 ( 65 )', 'essendon', '6.9 ( 45 )', 'victoria park', '39110', '30 july 1960'], ['carlton', '10.12 ( 72 )', 'st kilda', '11.17 ( 83 )', 'princes park', '24684', '30 july 1960'], ['richmond', '9.13 ( 67 )', 'north melbourne', '12.7 ( 79 )', 'punt road oval', '8500', '30 july 1960'], ['south melbourne', '10.10 ( 70 )', 'melbourne', '16.13 ( 109 )', 'lake oval', '18000', '30 july 1960'], ['geelong', '7.11 ( 53 )', 'fitzroy', '14.11 ( 95 )', 'kardinia park', '15022', '30 july 1960']]

tacoma public schools

https://en.wikipedia.org/wiki/Tacoma_Public_Schools

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1414702-3.html.csv

comparative

in the tacoma public schools , the enrollment at lincoln is 1118 more than the enrollment at tacoma school of the arts .

{'row_1': '2', 'row_2': '5', 'col': '4', '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', 'high school', 'lincoln'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high school record fuzzily matches to lincoln .', 'tostr': 'filter_eq { all_rows ; high school ; lincoln }'}, 'enrollment'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; high school ; lincoln } ; enrollment }', 'tointer': 'select the rows whose high school record fuzzily matches to lincoln . take the enrollment record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high school', 'tacoma school of the arts'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose high school record fuzzily matches to tacoma school of the arts .', 'tostr': 'filter_eq { all_rows ; high school ; tacoma school of the arts }'}, 'enrollment'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; high school ; tacoma school of the arts } ; enrollment }', 'tointer': 'select the rows whose high school record fuzzily matches to tacoma school of the arts . take the enrollment record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; high school ; lincoln } ; enrollment } ; hop { filter_eq { all_rows ; high school ; tacoma school of the arts } ; enrollment } } = true', 'tointer': 'select the rows whose high school record fuzzily matches to lincoln . take the enrollment record of this row . select the rows whose high school record fuzzily matches to tacoma school of the arts . take the enrollment record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; high school ; lincoln } ; enrollment } ; hop { filter_eq { all_rows ; high school ; tacoma school of the arts } ; enrollment } } = true

select the rows whose high school record fuzzily matches to lincoln . take the enrollment record of this row . select the rows whose high school record fuzzily matches to tacoma school of the arts . take the enrollment 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, 'high school_7': 7, 'lincoln_8': 8, 'enrollment_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'high school_11': 11, 'tacoma school of the arts_12': 12, 'enrollment_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', 'high school_7': 'high school', 'lincoln_8': 'lincoln', 'enrollment_9': 'enrollment', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'high school_11': 'high school', 'tacoma school of the arts_12': 'tacoma school of the arts', 'enrollment_13': 'enrollment'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'high school_7': [0], 'lincoln_8': [0], 'enrollment_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'high school_11': [1], 'tacoma school of the arts_12': [1], 'enrollment_13': [3]}

['high school', 'type', 'established', 'enrollment', 'mascot', 'wiaa classification', 'notes']

[['henry foss', 'comprehensive', '1973', '1298', 'falcons', '3a', 'located in central tacoma'], ['lincoln', 'comprehensive', '1913', '1618', 'abes', '3a', 'located in east tacoma'], ['mount tahoma', 'comprehensive', '1961', '1865', 'thunderbirds', '3a', 'located in south tacoma'], ['oakland alternative', 'alternative', '1988', '106', 'eagles', 'n / a', 'located in central tacoma'], ['tacoma school of the arts', 'magnet', '2001', '500', 'n / a', 'n / a', 'located in downtown tacoma']]

list of counts of burgundy

https://en.wikipedia.org/wiki/List_of_counts_of_Burgundy

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1178691-9.html.csv

unique

maximilian is the only count of burgundy with 2 listed relationships with predecessor .

{'scope': 'all', 'row': '5', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'and', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'relationship with predecessor', 'and'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose relationship with predecessor record fuzzily matches to and .', 'tostr': 'filter_eq { all_rows ; relationship with predecessor ; and }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; relationship with predecessor ; and } }', 'tointer': 'select the rows whose relationship with predecessor record fuzzily matches to and . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'relationship with predecessor', 'and'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose relationship with predecessor record fuzzily matches to and .', 'tostr': 'filter_eq { all_rows ; relationship with predecessor ; and }'}, 'name'], 'result': 'maximilian', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; relationship with predecessor ; and } ; name }'}, 'maximilian'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; relationship with predecessor ; and } ; name } ; maximilian }', 'tointer': 'the name record of this unqiue row is maximilian .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; relationship with predecessor ; and } } ; eq { hop { filter_eq { all_rows ; relationship with predecessor ; and } ; name } ; maximilian } } = true', 'tointer': 'select the rows whose relationship with predecessor record fuzzily matches to and . there is only one such row in the table . the name record of this unqiue row is maximilian .'}

and { only { filter_eq { all_rows ; relationship with predecessor ; and } } ; eq { hop { filter_eq { all_rows ; relationship with predecessor ; and } ; name } ; maximilian } } = true

select the rows whose relationship with predecessor record fuzzily matches to and . there is only one such row in the table . the name record of this unqiue row is maximilian .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'relationship with predecessor_7': 7, 'and_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'maximilian_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'relationship with predecessor_7': 'relationship with predecessor', 'and_8': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'maximilian_10': 'maximilian'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'relationship with predecessor_7': [0], 'and_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'maximilian_10': [3]}

['name', 'date of birth', 'date of death', 'reign', 'relationship with predecessor']

[['john the fearless', '28 may 1371', '10 september 1419', '16 / 21 march 1405 to 10 september 1419', 'their son'], ['philip v the good', '31 july 1396', '15 june 1467', '10 september 1419 to 15 june 1467', 'his son'], ['charles i the bold', '10 november 1433', '5 january 1477', '15 june 1467 to 5 january 1477', 'his son'], ['mary the rich', '13 february 1457', '27 march 1482', '5 january 1477 to 27 march 1482', 'his daughter'], ['maximilian', '22 march 1459', '12 january 1519', '5 january 1477 to 27 march 1482', 'her husband and co - ruler']]

song - hee kim

https://en.wikipedia.org/wiki/Song-Hee_Kim

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24330912-1.html.csv

unique

the only year that song-hee kim did not make the top ten is 2007 .

{'scope': 'all', 'row': '1', 'col': '7', 'col_other': '1', 'criterion': 'equal', 'value': '0', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'top 10s', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top 10s record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; top 10s ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; top 10s ; 0 } }', 'tointer': 'select the rows whose top 10s record is equal to 0 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'top 10s', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top 10s record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; top 10s ; 0 }'}, 'year'], 'result': '2007', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; top 10s ; 0 } ; year }'}, '2007'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; top 10s ; 0 } ; year } ; 2007 }', 'tointer': 'the year record of this unqiue row is 2007 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; top 10s ; 0 } } ; eq { hop { filter_eq { all_rows ; top 10s ; 0 } ; year } ; 2007 } } = true', 'tointer': 'select the rows whose top 10s record is equal to 0 . there is only one such row in the table . the year record of this unqiue row is 2007 .'}

and { only { filter_eq { all_rows ; top 10s ; 0 } } ; eq { hop { filter_eq { all_rows ; top 10s ; 0 } ; year } ; 2007 } } = true

select the rows whose top 10s record is equal to 0 . there is only one such row in the table . the year record of this unqiue row is 2007 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'top 10s_7': 7, '0_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2007_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'top 10s_7': 'top 10s', '0_8': '0', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2007_10': '2007'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'top 10s_7': [0], '0_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2007_10': [3]}

['year', 'tournaments played', 'cuts made', 'wins', '2nd', '3rd', 'top 10s', 'best finish', 'earnings', 'money list rank', 'scoring average', 'scoring rank']

[['2007', '19', '10', '0', '0', '0', '0', 't22', '78660', '99', '73.72', '75'], ['2008', '25', '21', '0', '2', '1', '7', '2', '980883', '14', '71.23', '10'], ['2009', '25', '23', '0', '0', '2', '12', 't3', '1032031', '11', '70.52', '8'], ['2010', '22', '22', '0', '2', '3', '15', '2', '1208698', '8', '70.21', '4'], ['2011', '22', '19', '0', '1', '0', '2', '2', '350376', '33', '72.62', '47']]

nicolas lapierre

https://en.wikipedia.org/wiki/Nicolas_Lapierre

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1628448-4.html.csv

aggregation

from 2007 to 2013 , nicolas lapierre averaged 312.5 laps per race in 24 hours of le mans .

{'scope': 'all', 'col': '5', 'type': 'average', 'result': '312.5', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'laps'], 'result': '312.5', 'ind': 0, 'tostr': 'avg { all_rows ; laps }'}, '312.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; laps } ; 312.5 } = true', 'tointer': 'the average of the laps record of all rows is 312.5 .'}

round_eq { avg { all_rows ; laps } ; 312.5 } = true

the average of the laps record of all rows is 312.5 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'laps_4': 4, '312.5_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '312.5_5': '312.5'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'laps_4': [0], '312.5_5': [1]}

['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos']

[['2007', 'team oreca', 'stéphane ortelli soheil ayari', 'gt1', '318', '16th', '9th'], ['2009', 'team oreca - matmut aim', 'olivier panis soheil ayari', 'lmp1', '370', '5th', '5th'], ['2010', 'team oreca - matmut', 'olivier panis loïc duval', 'lmp1', '373', 'dnf', 'dnf'], ['2011', 'team oreca - matmut', 'olivier panis loïc duval', 'lmp1', '339', '5th', '5th'], ['2012', 'toyota racing', 'alexander wurz kazuki nakajima', 'lmp1', '134', 'dnf', 'dnf'], ['2013', 'toyota racing', 'alexander wurz kazuki nakajima', 'lmp1', '341', '4th', '4th']]

list of united states senators expelled or censured

https://en.wikipedia.org/wiki/List_of_United_States_senators_expelled_or_censured

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1436309-2.html.csv

ordinal

bob packwood was the 2nd us senator from oregon ever to undergo expulsion proceedings that did not lead to expulsion .

{'scope': 'subset', 'row': '17', 'col': '1', 'order': '2', 'col_other': '5', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'oregon'}}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'state', 'oregon'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; state ; oregon }', 'tointer': 'select the rows whose state record fuzzily matches to oregon .'}, 'year', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; state ; oregon } ; year ; 2 }'}, 'result'], 'result': 'resigned', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; state ; oregon } ; year ; 2 } ; result }'}, 'resigned'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; state ; oregon } ; year ; 2 } ; result } ; resigned } = true', 'tointer': 'select the rows whose state record fuzzily matches to oregon . select the row whose year record of these rows is 2nd minimum . the result record of this row is resigned .'}

eq { hop { nth_argmin { filter_eq { all_rows ; state ; oregon } ; year ; 2 } ; result } ; resigned } = true

select the rows whose state record fuzzily matches to oregon . select the row whose year record of these rows is 2nd minimum . the result record of this row is resigned .

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, 'state_6': 6, 'oregon_7': 7, 'year_8': 8, '2_9': 9, 'result_10': 10, 'resigned_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', 'state_6': 'state', 'oregon_7': 'oregon', 'year_8': 'year', '2_9': '2', 'result_10': 'result', 'resigned_11': 'resigned'}

{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'state_6': [0], 'oregon_7': [0], 'year_8': [1], '2_9': [1], 'result_10': [2], 'resigned_11': [3]}

['year', 'senator', 'party', 'state', 'result']

[['1808', 'john smith', 'democrat - republican', 'ohio', 'not expelled'], ['1856', 'henry mower rice', 'democratic', 'minnesota', 'not expelled'], ['1862', 'lazarus w powell', 'democratic', 'kentucky', 'not expelled'], ['1862', 'james f simmons', 'republican', 'rhode island', 'resigned'], ['1873', 'james w patterson', 'republican', 'new hampshire', 'term expired'], ['1893', 'william n roach', 'democratic', 'north dakota', 'not expelled'], ['1905', 'john h mitchell', 'republican', 'oregon', 'died during proceedings'], ['1906', 'joseph r burton', 'republican', 'kansas', 'resigned'], ['1907', 'reed smoot', 'republican', 'utah', 'not expelled'], ['1919', 'robert m la follette , sr', 'republican', 'wisconsin', 'not expelled'], ['1922', 'truman handy newberry', 'republican', 'michigan', 'resigned'], ['1924', 'burton k wheeler', 'democratic', 'montana', 'not expelled'], ['1934', 'john h overton', 'democratic', 'louisiana', 'not expelled'], ['1934', 'huey long', 'democratic', 'louisiana', 'not expelled'], ['1942', 'william langer', 'republican', 'north dakota', 'not expelled'], ['1982', 'harrison a williams', 'democratic', 'new jersey', 'resigned'], ['1995', 'bob packwood', 'republican', 'oregon', 'resigned'], ['2011', 'john ensign', 'republican', 'nevada', 'resigned']]

2005 cologne centurions season

https://en.wikipedia.org/wiki/2005_Cologne_Centurions_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27764201-2.html.csv

count

the 2005 cologne centurions season featured an attendance of more than 10000 fans six times .

{'scope': 'all', 'criterion': 'greater_than', 'value': '10000', 'result': '6', 'col': '8', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'attendance', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is greater than 10000 .', 'tostr': 'filter_greater { all_rows ; attendance ; 10000 }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; attendance ; 10000 } }', 'tointer': 'select the rows whose attendance record is greater than 10000 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; attendance ; 10000 } } ; 6 } = true', 'tointer': 'select the rows whose attendance record is greater than 10000 . the number of such rows is 6 .'}

eq { count { filter_greater { all_rows ; attendance ; 10000 } } ; 6 } = true

select the rows whose attendance record is greater than 10000 . the number of such rows is 6 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '10000_6': 6, '6_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '10000_6': '10000', '6_7': '6'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '10000_6': [0], '6_7': [2]}

['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance']

[['1', 'saturday , april 2', '6:00 pm', 'hamburg sea devils', 'w 24 - 23', '1 - 0', 'rheinenergiestadion', '9468'], ['2', 'sunday , april 10', '4:00 pm', 'rhein fire', 'w 23 - 10', '2 - 0', 'ltu arena', '25304'], ['3', 'saturday , april 16', '6:00 pm', 'frankfurt galaxy', 'w 23 - 14', '3 - 0', 'rheinenergiestadion', '10821'], ['4', 'saturday , april 23', '6:00 pm', 'amsterdam admirals', 'l 24 - 37', '3 - 1', 'rheinenergiestadion', '8863'], ['5', 'saturday , april 30', '7:00 pm', 'hamburg sea devils', 'l 6 - 23', '3 - 2', 'aol arena', '15228'], ['6', 'sunday , may 8', '4:00 pm', 'berlin thunder', 'w 23 - 17', '4 - 2', 'rheinenergiestadion', '9485'], ['7', 'saturday , may 14', '7:00 pm', 'frankfurt galaxy', 'w 20 - 17 ot', '5 - 2', 'commerzbank - arena', '25347'], ['8', 'monday , may 23', '8:00 pm', 'amsterdam admirals', 'l 12 - 30', '5 - 3', 'amsterdam arena', '14423'], ['9', 'sunday , may 29', '4:00 pm', 'rhein fire', 'l 16 - 28', '5 - 4', 'rheinenergiestadion', '32521']]

2008 washington redskins season

https://en.wikipedia.org/wiki/2008_Washington_Redskins_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10966926-4.html.csv

unique

week 10 is the only week in the 2008 washington redskins season where there was no game .

{'scope': 'all', 'row': '10', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '-', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'date', '-'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record is equal to - .', 'tostr': 'filter_eq { all_rows ; date ; - }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date ; - } }', 'tointer': 'select the rows whose date record is equal to - . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'date', '-'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record is equal to - .', 'tostr': 'filter_eq { all_rows ; date ; - }'}, 'week'], 'result': '10', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; - } ; week }'}, '10'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; - } ; week } ; 10 }', 'tointer': 'the week record of this unqiue row is 10 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; date ; - } } ; eq { hop { filter_eq { all_rows ; date ; - } ; week } ; 10 } } = true', 'tointer': 'select the rows whose date record is equal to - . there is only one such row in the table . the week record of this unqiue row is 10 .'}

and { only { filter_eq { all_rows ; date ; - } } ; eq { hop { filter_eq { all_rows ; date ; - } ; week } ; 10 } } = true

select the rows whose date record is equal to - . there is only one such row in the table . the week record of this unqiue row is 10 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '-_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'week_9': 9, '10_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '-_8': '-', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'week_9': 'week', '10_10': '10'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'date_7': [0], '-_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'week_9': [2], '10_10': [3]}

['week', 'date', 'opponent', 'time ( et )', 'result', 'game site', 'record', 'match report']

[['1', 'september 4 , 2008', 'new york giants', '7:00', 'l 7 - 16', 'giants stadium', '0 - 1', 'recap'], ['2', 'september 14 , 2008', 'new orleans saints', '1:00', 'w 29 - 24', 'fedex field', '1 - 1', 'recap'], ['3', 'september 21 , 2008', 'arizona cardinals', '1:00', 'w 24 - 17', 'fedex field', '2 - 1', 'recap'], ['4', 'september 28 , 2008', 'dallas cowboys', '4:15', 'w 26 - 24', 'texas stadium', '3 - 1', 'recap'], ['5', 'october 5 , 2008', 'philadelphia eagles', '1:00', 'w 23 - 17', 'lincoln financial field', '4 - 1', 'recap'], ['6', 'october 12 , 2008', 'st louis rams', '1:00', 'l 17 - 19', 'fedex field', '4 - 2', 'recap'], ['7', 'october 19 , 2008', 'cleveland browns', '4:15', 'w 14 - 11', 'fedex field', '5 - 2', 'recap'], ['8', 'october 26 , 2008', 'detroit lions', '1:00', 'w 25 - 17', 'ford field', '6 - 2', 'recap'], ['9', 'november 3 , 2008', 'pittsburgh steelers', '8:30', 'l 6 - 23', 'fedex field', '6 - 3', 'recap'], ['10', '-', '-', '-', '-', '-', '-', ''], ['11', 'november 16 , 2008', 'dallas cowboys', '8:15', 'l 10 - 14', 'fedex field', '6 - 4', 'recap'], ['12', 'november 23 , 2008', 'seattle seahawks', '4:15', 'w 20 - 17', 'qwest field', '7 - 4', 'recap'], ['13', 'november 30 , 2008', 'new york giants', '1:00', 'l 7 - 23', 'fedex field', '7 - 5', 'recap'], ['14', 'december 7 , 2008', 'baltimore ravens', '8:15', 'l 10 - 24', 'm & t bank stadium', '7 - 6', 'recap'], ['15', 'december 14 , 2008', 'cincinnati bengals', '1:00', 'l 13 - 20', 'paul brown stadium', '7 - 7', 'recap'], ['16', 'december 21 , 2008', 'philadelphia eagles', '4:15', 'w 10 - 3', 'fedex field', '8 - 7', 'recap'], ['17', 'december 28 , 2008', 'san francisco 49ers', '4:15', 'l 24 - 27', 'candlestick park', '8 - 8', 'recap']]

fabio fognini

https://en.wikipedia.org/wiki/Fabio_Fognini

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11983898-4.html.csv

count

of the tournaments that fabio fognini participated in , four of them were on a clay surface .

{'scope': 'all', 'criterion': 'equal', 'value': 'clay', 'result': '4', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to clay .', 'tostr': 'filter_eq { all_rows ; surface ; clay }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; surface ; clay } }', 'tointer': 'select the rows whose surface record fuzzily matches to clay . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; surface ; clay } } ; 4 } = true', 'tointer': 'select the rows whose surface record fuzzily matches to clay . the number of such rows is 4 .'}

eq { count { filter_eq { all_rows ; surface ; clay } } ; 4 } = true

select the rows whose surface record fuzzily matches to clay . 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, 'surface_5': 5, 'clay_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', 'surface_5': 'surface', 'clay_6': 'clay', '4_7': '4'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'clay_6': [0], '4_7': [2]}

['outcome', 'date', 'tournament', 'surface', 'opponent in the final', 'score in the final']

[['runner - up', '29 april 2012', 'brd năstase ţiriac trophy , bucharest , romania', 'clay', 'gilles simon', '4 - 6 , 3 - 6'], ['runner - up', '23 september 2012', 'st petersburg open , st petersburg , russia', 'hard ( i )', 'martin kližan', '2 - 6 , 3 - 6'], ['winner', '14 july 2013', 'stuttgart open , stuttgart , germany', 'clay', 'philipp kohlschreiber', '5 - 7 , 6 - 4 , 6 - 4'], ['winner', '21 july 2013', 'international german open , hamburg , germany', 'clay', 'federico delbonis', '4 - 6 , 7 - 6 ( 10 - 8 ) , 6 - 2'], ['runner - up', '28 july 2013', 'atp vegeta croatia open umag , umag , croatia', 'clay', 'tommy robredo', '0 - 6 , 3 - 6']]

lard

https://en.wikipedia.org/wiki/Lard

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18621997-1.html.csv

unique

only suet has a polyunsaturated fat level of less that 10 % .

{'scope': 'all', 'row': '10', 'col': '5', 'col_other': '1', 'criterion': 'less_than', 'value': '10 %', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'polyunsaturated fat', '10 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose polyunsaturated fat record is less than 10 % .', 'tostr': 'filter_less { all_rows ; polyunsaturated fat ; 10 % }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; polyunsaturated fat ; 10 % } }', 'tointer': 'select the rows whose polyunsaturated fat record is less than 10 % . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'polyunsaturated fat', '10 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose polyunsaturated fat record is less than 10 % .', 'tostr': 'filter_less { all_rows ; polyunsaturated fat ; 10 % }'}, ''], 'result': 'suet', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; polyunsaturated fat ; 10 % } ; }'}, 'suet'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; polyunsaturated fat ; 10 % } ; } ; suet }', 'tointer': 'the record of this unqiue row is suet .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; polyunsaturated fat ; 10 % } } ; eq { hop { filter_less { all_rows ; polyunsaturated fat ; 10 % } ; } ; suet } } = true', 'tointer': 'select the rows whose polyunsaturated fat record is less than 10 % . there is only one such row in the table . the record of this unqiue row is suet .'}

and { only { filter_less { all_rows ; polyunsaturated fat ; 10 % } } ; eq { hop { filter_less { all_rows ; polyunsaturated fat ; 10 % } ; } ; suet } } = true

select the rows whose polyunsaturated fat record is less than 10 % . there is only one such row in the table . the record of this unqiue row is suet .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'polyunsaturated fat_7': 7, '10%_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, '_9': 9, 'suet_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'polyunsaturated fat_7': 'polyunsaturated fat', '10%_8': '10 %', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', '_9': '', 'suet_10': 'suet'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'polyunsaturated fat_7': [0], '10%_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], '_9': [2], 'suet_10': [3]}

['', 'total fat', 'saturated fat', 'monounsaturated fat', 'polyunsaturated fat', 'smoke point']

[['sunflower oil', '100 g', '11 g', '20 g ( 84 g in high oleic variety )', '69 g ( 4 g in high oleic variety )', 'degree'], ['soybean oil', '100 g', '16 g', '23 g', '58 g', 'degree'], ['canola oil', '100 g', '7 g', '63 g', '28 g', 'degree'], ['olive oil', '100 g', '14 g', '73 g', '11 g', 'degree'], ['corn oil', '100 g', '15 g', '30 g', '55 g', 'degree'], ['peanut oil', '100 g', '17 g', '46 g', '32 g', 'degree'], ['rice bran oil', '100 g', '25 g', '38 g', '37 g', 'degree'], ['vegetable shortening ( hydrogenated )', '71 g', '23 g ( 34 % )', '8 g ( 11 % )', '37 g ( 52 % )', 'degree'], ['lard', '100 g', '39 g', '45 g', '11 g', 'degree'], ['suet', '94 g', '52 g ( 55 % )', '32 g ( 34 % )', '3 g ( 3 % )', '200degree ( 400degree )']]

tomomi manako

https://en.wikipedia.org/wiki/Tomomi_Manako

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12907958-2.html.csv

aggregation

when tonomi manako 's team was honda , his total number of wins is 6 .

{'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '6', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'honda'}}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'honda'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; team ; honda }', 'tointer': 'select the rows whose team record fuzzily matches to honda .'}, 'wins'], 'result': '6', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; team ; honda } ; wins }'}, '6'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; team ; honda } ; wins } ; 6 } = true', 'tointer': 'select the rows whose team record fuzzily matches to honda . the sum of the wins record of these rows is 6 .'}

round_eq { sum { filter_eq { all_rows ; team ; honda } ; wins } ; 6 } = true

select the rows whose team record fuzzily matches to honda . the sum of the wins record of these rows is 6 .

3

3

{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'honda_6': 6, 'wins_7': 7, '6_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'honda_6': 'honda', 'wins_7': 'wins', '6_8': '6'}

{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'honda_6': [0], 'wins_7': [1], '6_8': [2]}

['year', 'class', 'team', 'points', 'rank', 'wins']

[['1994', '125cc', 'honda', '24', '20th', '0'], ['1995', '125cc', 'honda', '102', '8th', '0'], ['1996', '125cc', 'honda', '167', '3rd', '1'], ['1997', '125cc', 'honda', '190', '3rd', '0'], ['1998', '125cc', 'honda', '217', '2nd', '5'], ['1999', '250cc', 'yamaha', '52', '15th', '0']]

1983 - 84 north west counties football league

https://en.wikipedia.org/wiki/1983%E2%80%9384_North_West_Counties_Football_League

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17718005-2.html.csv

majority

most of the teams in the 1983 – 84 north west counties football league had points under 40 .

{'scope': 'all', 'col': '9', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '40', 'subset': None}

{'func': 'most_less', 'args': ['all_rows', 'points 1', '40'], 'result': True, 'ind': 0, 'tointer': 'for the points 1 records of all rows , most of them are less than 40 .', 'tostr': 'most_less { all_rows ; points 1 ; 40 } = true'}

most_less { all_rows ; points 1 ; 40 } = true

for the points 1 records of all rows , most of them are less than 40 .

1

1

{'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points 1_3': 3, '40_4': 4}

{'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points 1_3': 'points 1', '40_4': '40'}

{'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'points 1_3': [0], '40_4': [0]}

['position', 'team', 'played', 'drawn', 'lost', 'goals for', 'goals against', 'goal difference', 'points 1']

[['1', 'fleetwood town', '34', '8', '2', '73', '24', '+ 49', '56'], ['2', 'eastwood hanley', '34', '6', '7', '69', '35', '+ 34', '48'], ['3', 'irlam town', '34', '8', '7', '67', '41', '+ 26', '46'], ['4', 'warrington town', '34', '7', '9', '65', '45', '+ 20', '43'], ['5', 'droylsden', '34', '5', '10', '59', '42', '+ 17', '43'], ['6', 'colne dynamoes', '34', '9', '9', '55', '37', '+ 18', '41'], ['7', 'ellesmere port & neston', '34', '10', '12', '49', '38', '+ 11', '34'], ['8', 'chadderton', '34', '6', '14', '56', '46', '+ 10', '34'], ['9', 'atherton laburnum rovers', '34', '11', '12', '37', '41', '4', '33'], ['10', 'wren rovers', '34', '10', '13', '45', '47', '2', '33'], ['11', 'skelmersdale united', '34', '6', '15', '60', '63', '3', '32'], ['12', 'ford motors', '34', '9', '16', '38', '53', '15', '27'], ['13', 'prescot bi', '34', '9', '16', '50', '66', '16', '27'], ['14', 'lytham', '34', '3', '18', '56', '81', '25', '27 2'], ['15', 'rossendale united', '34', '6', '18', '53', '84', '31', '26'], ['16', 'great harwood town', '34', '12', '17', '36', '60', '24', '22'], ['17', 'salford', '34', '11', '18', '24', '60', '36', '21'], ['18', 'nantwich town', '34', '2', '24', '44', '73', '29', '18']]

list of game of the year awards

https://en.wikipedia.org/wiki/List_of_Game_of_the_Year_awards

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1851722-10.html.csv

count

a total of three game of the year winners are available on the playstation 3 platform .

{'scope': 'all', 'criterion': 'equal', 'value': 'playstation 3', 'result': '3', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'platform ( s )', 'playstation 3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose platform ( s ) record fuzzily matches to playstation 3 .', 'tostr': 'filter_eq { all_rows ; platform ( s ) ; playstation 3 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; platform ( s ) ; playstation 3 } }', 'tointer': 'select the rows whose platform ( s ) record fuzzily matches to playstation 3 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; platform ( s ) ; playstation 3 } } ; 3 } = true', 'tointer': 'select the rows whose platform ( s ) record fuzzily matches to playstation 3 . the number of such rows is 3 .'}

eq { count { filter_eq { all_rows ; platform ( s ) ; playstation 3 } } ; 3 } = true

select the rows whose platform ( s ) record fuzzily matches to playstation 3 . 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, 'platform (s)_5': 5, 'playstation 3_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', 'platform (s)_5': 'platform ( s )', 'playstation 3_6': 'playstation 3', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'platform (s)_5': [0], 'playstation 3_6': [0], '3_7': [2]}

['year', 'game', 'genre', 'platform ( s )', 'developer ( s )']

[['2003', 'the legend of zelda : the wind waker', 'action - adventure : open world', 'nintendo gamecube', 'nintendo ead'], ['2009', "demon 's souls", 'action rpg : hack & slash', 'playstation 3', 'from software'], ['2010', 'super mario galaxy 2', 'platformer', 'wii', 'nintendo ead'], ['2011', 'dead space 2', 'survival horror : ( third - person ) shooter', 'microsoft windows , playstation 3 , xbox 360', 'visceral games'], ['2012', 'borderlands 2', 'first - person shooter', 'xbox 360 , windows , playstation 3', 'gearbox software']]

2010 veikkausliiga

https://en.wikipedia.org/wiki/2010_Veikkausliiga

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25129482-1.html.csv

count

three of the veikkausliiga stadiums can seat more than 10000 fans .

{'scope': 'all', 'criterion': 'greater_than', 'value': '10000', 'result': '3', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'capacity', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose capacity record is greater than 10000 .', 'tostr': 'filter_greater { all_rows ; capacity ; 10000 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; capacity ; 10000 } }', 'tointer': 'select the rows whose capacity record is greater than 10000 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; capacity ; 10000 } } ; 3 } = true', 'tointer': 'select the rows whose capacity record is greater than 10000 . the number of such rows is 3 .'}

eq { count { filter_greater { all_rows ; capacity ; 10000 } } ; 3 } = true

select the rows whose capacity record is greater than 10000 . the number of such rows is 3 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'capacity_5': 5, '10000_6': 6, '3_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', '10000_6': '10000', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'capacity_5': [0], '10000_6': [0], '3_7': [2]}

['club', 'location', 'stadium', 'capacity', 'manager', 'kitmaker']

[['ac oulu', 'oulu', 'castrén', '4000', 'juha malinen', 'umbro'], ['fc honka', 'espoo', 'tapiolan urheilupuisto', '6000', 'mika lehkosuo', 'kappa'], ['fc inter', 'turku', 'veritas stadion', '9372', 'job dragtsma', 'nike'], ['fc lahti', 'lahti', 'lahden stadion', '15000', 'ilkka mäkelä', 'umbro'], ['ff jaro', 'jakobstad', 'jakobstads centralplan', '5000', 'alexei eremenko sr', 'errea'], ['haka', 'valkeakoski', 'tehtaan kenttä', '3516', 'sami ristilä', 'umbro'], ['hjk', 'helsinki', 'sonera stadium', '10770', 'antti muurinen', 'adidas'], ['ifk mariehamn', 'mariehamn', 'wiklöf holding arena', '4000', 'pekka lyyski', 'puma'], ['jjk', 'jyväskylä', 'harjun stadion', '3000', 'kari martonen', 'legea'], ['kups', 'kuopio', 'kuopion keskuskenttä', '5000', 'esa pekonen', 'puma'], ['mypa', 'anjalankoski', 'saviniemi', '4167', 'janne lindberg', 'puma'], ['tampere united', 'tampere', 'ratina stadion', '17000', 'ari hjelm', 'puma'], ['tps', 'turku', 'veritas stadion', '9372', 'marko rajamäki', 'puma']]

2003 - 04 primeira liga

https://en.wikipedia.org/wiki/2003%E2%80%9304_Primeira_Liga

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17933600-2.html.csv

majority

the majority of coaching vacancies for the 03-04 primeira liga were due to coaches being sacked .

{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'sacked', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'manner', 'sacked'], 'result': True, 'ind': 0, 'tointer': 'for the manner records of all rows , most of them fuzzily match to sacked .', 'tostr': 'most_eq { all_rows ; manner ; sacked } = true'}

most_eq { all_rows ; manner ; sacked } = true

for the manner records of all rows , most of them fuzzily match to sacked .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'manner_3': 3, 'sacked_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'manner_3': 'manner', 'sacked_4': 'sacked'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'manner_3': [0], 'sacked_4': [0]}

['team', 'outgoing manage', 'manner', 'date of vacancy', 'incoming manager', 'date of appointment']

[['académica de coimbra', 'artur jorge', 'resigned', '28 august 2003', 'vítor oliveira', '28 august 2003'], ['vitória de guimarães', 'augusto inácio', 'sacked', '8 december 2003', 'jorge jesus', '8 december 2003'], ['paços de ferreira', 'josé gomes', 'mutual consent', '21 october 2003', 'josé mota', '22 october 2003'], ['estrela da amadora', 'joão alves', 'sacked', '3 november 2003', 'miguel quaresma', '3 november 2003'], ['gil vicente', 'mário reis', 'sacked', '11 november 2003', 'luís campos', '25 november 2003'], ['belenenses', 'manuel josé', 'resigned', '22 november 2003', 'bogićević', '23 november 2003'], ['belenenses', 'bogićević', 'sacked', '19 january 2004', 'augusto inácio', '20 january 2004'], ['académica de coimbra', 'vítor oliveira', 'sacked', '26 january 2004', 'joão pereira', '27 january 2004']]

1985 pga tour

https://en.wikipedia.org/wiki/1985_PGA_Tour

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14640372-3.html.csv

count

in the 1985 pga tour , there were two golfers ranked in the top five that had two wins .

{'scope': 'all', 'criterion': 'equal', 'value': '2', 'result': '2', 'col': '6', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 2 .', 'tostr': 'filter_eq { all_rows ; wins ; 2 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; wins ; 2 } }', 'tointer': 'select the rows whose wins record is equal to 2 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; wins ; 2 } } ; 2 } = true', 'tointer': 'select the rows whose wins record is equal to 2 . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; wins ; 2 } } ; 2 } = true

select the rows whose wins record is equal to 2 . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'wins_5': 5, '2_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'wins_5': 'wins', '2_6': '2', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'wins_5': [0], '2_6': [0], '2_7': [2]}

['rank', 'player', 'country', 'earnings', 'events', 'wins']

[['1', 'curtis strange', 'united states', '542321', '25', '3'], ['2', 'lanny wadkins', 'united states', '446893', '24', '3'], ['3', 'calvin peete', 'united states', '384489', '22', '2'], ['4', 'jim thorpe', 'united states', '379091', '28', '2'], ['5', 'raymond floyd', 'united states', '378989', '22', '1']]