Datasets:

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nigel melker

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26178824-1.html.csv

aggregation

in 2012 , the total number of points nigel melker had was 40 .

{'scope': 'subset', 'col': '9', 'type': 'sum', 'result': '40', 'subset': {'col': '1', 'criterion': 'equal', 'value': '2012'}}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'season', '2012'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; season ; 2012 }', 'tointer': 'select the rows whose season record is equal to 2012 .'}, 'points'], 'result': '40', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; season ; 2012 } ; points }'}, '40'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; season ; 2012 } ; points } ; 40 } = true', 'tointer': 'select the rows whose season record is equal to 2012 . the sum of the points record of these rows is 40 .'}

round_eq { sum { filter_eq { all_rows ; season ; 2012 } ; points } ; 40 } = true

select the rows whose season record is equal to 2012 . the sum of the points record of these rows is 40 .

3

3

{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'season_5': 5, '2012_6': 6, 'points_7': 7, '40_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'season_5': 'season', '2012_6': '2012', 'points_7': 'points', '40_8': '40'}

{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'season_5': [0], '2012_6': [0], 'points_7': [1], '40_8': [2]}

['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position']

[['2008', 'formula renault 2.0 nec', 'van amersfoort racing', '15', '0', '0', '0', '0', '120', '12th'], ['2008', 'formula renault 2.0 italy', 'van amersfoort racing', '10', '0', '0', '0', '0', '37', '18th'], ['2009', 'formula renault 2.0 eurocup', 'mp motorsport', '10', '0', '0', '0', '0', '5', '23rd'], ['2009', 'formula renault 2.0 nec', 'mp motorsport', '6', '0', '0', '0', '0', '77', '18th'], ['2010', 'gp3 series', 'rsc mücke motorsport', '16', '0', '2', '0', '0', '5', '23rd'], ['2011', 'gp3 series', 'rsc mücke motorsport', '16', '1', '0', '2', '5', '38', '3rd'], ['2011', 'formula 3 euro series', 'mücke motorsport', '24', '4', '2', '2', '9', '251', '4th'], ['2011', 'gp2 final', 'dams', '2', '0', '0', '0', '0', '0', '20th'], ['2012', 'gp2 series', 'ocean racing technology', '24', '0', '0', '0', '0', '25', '19th'], ['2012', 'formula renault 3.5 series', 'lotus', '2', '0', '0', '0', '1', '15', '19th']]

cho kwang - rae

https://en.wikipedia.org/wiki/Cho_Kwang-Rae

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12513368-1.html.csv

comparative

cho kwang-rae scored the same number of goals in both the 1978 merdeka cup and the 1986 fifa world cup .

{'row_1': '3', 'row_2': '8', 'col': '3', 'col_other': '5', 'relation': 'equal', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '1978 merdeka cup'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to 1978 merdeka cup .', 'tostr': 'filter_eq { all_rows ; competition ; 1978 merdeka cup }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; competition ; 1978 merdeka cup } ; score }', 'tointer': 'select the rows whose competition record fuzzily matches to 1978 merdeka cup . take the score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '1986 fifa world cup'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose competition record fuzzily matches to 1986 fifa world cup .', 'tostr': 'filter_eq { all_rows ; competition ; 1986 fifa world cup }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; competition ; 1986 fifa world cup } ; score }', 'tointer': 'select the rows whose competition record fuzzily matches to 1986 fifa world cup . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; competition ; 1978 merdeka cup } ; score } ; hop { filter_eq { all_rows ; competition ; 1986 fifa world cup } ; score } } = true', 'tointer': 'select the rows whose competition record fuzzily matches to 1978 merdeka cup . take the score record of this row . select the rows whose competition record fuzzily matches to 1986 fifa world cup . take the score record of this row . the first record fuzzily matches to the second record .'}

eq { hop { filter_eq { all_rows ; competition ; 1978 merdeka cup } ; score } ; hop { filter_eq { all_rows ; competition ; 1986 fifa world cup } ; score } } = true

select the rows whose competition record fuzzily matches to 1978 merdeka cup . take the score record of this row . select the rows whose competition record fuzzily matches to 1986 fifa world cup . take the score record of this row . the first record fuzzily matches to the second record .

5

5

{'str_eq_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'competition_7': 7, '1978 merdeka cup_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'competition_11': 11, '1986 fifa world cup_12': 12, 'score_13': 13}

{'str_eq_4': 'str_eq', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'competition_7': 'competition', '1978 merdeka cup_8': '1978 merdeka cup', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'competition_11': 'competition', '1986 fifa world cup_12': '1986 fifa world cup', 'score_13': 'score'}

{'str_eq_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'competition_7': [0], '1978 merdeka cup_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'competition_11': [1], '1986 fifa world cup_12': [1], 'score_13': [3]}

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

[['july 22 , 1977', 'kuala lumpur', '1 goal', '5 - 1', '1977 merdeka cup'], ['july 26 , 1977', 'kuala lumpur', '1 goal', '4 - 0', '1977 merdeka cup'], ['july 12 , 1978', 'kuala lumpur', '1 goal', '4 - 0', '1978 merdeka cup'], ['december 10 , 1978', 'bangkok', '2 goals', '5 - 1', '1978 asian games'], ['september 8 , 1979', 'seoul', '1 goal', '8 - 0', "1979 president 's cup"], ['september 16 , 1979', 'incheon', '3 goals', '9 - 0', "1979 president 's cup"], ['august 29 , 1980', 'gwangju', '1 goal', '5 - 0', "1980 president 's cup"], ['june 10 , 1986', 'puebla', '1 goal ( og )', '2 - 3', '1986 fifa world cup'], ['october 3 , 1986', 'seoul', '1 goal', '4 - 0', '1986 asian games'], ['october 5 , 1986', 'seoul', '1 goal', '2 - 0', '1986 asian games']]

cities of the underworld

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10926568-2.html.csv

count

there are 13 listed episodes in the cities of the underworld series .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '13', 'col': '2', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'episode no'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose episode no record is arbitrary .', 'tostr': 'filter_all { all_rows ; episode no }'}], 'result': '13', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; episode no } }', 'tointer': 'select the rows whose episode no record is arbitrary . the number of such rows is 13 .'}, '13'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; episode no } } ; 13 } = true', 'tointer': 'select the rows whose episode no record is arbitrary . the number of such rows is 13 .'}

eq { count { filter_all { all_rows ; episode no } } ; 13 } = true

select the rows whose episode no record is arbitrary . the number of such rows is 13 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'episode no_5': 5, '13_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'episode no_5': 'episode no', '13_6': '13'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'episode no_5': [0], '13_6': [2]}

['production no', 'episode no', 'original airdate', 'episode title', 'host']

[['15', '201', 'january 28 , 2008', 'underground apocalypse', 'don wildman'], ['16', '202', 'february 4 , 2008', 'vietnam', 'don wildman'], ['17', '203', 'february 11 , 2008', 'a - bomb underground', 'don wildman'], ['18', '204', 'february 25 , 2008', 'viking underground', 'don wildman'], ['19', '205', 'march 3 , 2008', "hitler 's last secret", 'don wildman'], ['20', '206', 'march 10 , 2008', 'maya underground', 'don wildman'], ['21', '207', 'march 17 , 2008', 'mob underground', 'don wildman'], ['22', '208', 'march 24 , 2008', 'prophecies from below', 'don wildman'], ['23', '209', 'march 31 , 2008', 'new york : secret societies', 'don wildman'], ['24', '210', 'april 14 , 2008', 'washington , dc : seat of power', 'don wildman'], ['25', '211', 'april 21 , 2008', "stalin 's secret lair", 'don wildman'], ['26', '212', 'april 28 , 2008', 'katrina underground', 'don wildman'], ['27', '213', 'may 5 , 2008', 'secret soviet bases', 'don wildman']]

1999 - 2000 philadelphia flyers season

https://en.wikipedia.org/wiki/1999%E2%80%932000_Philadelphia_Flyers_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14173105-4.html.csv

aggregation

in the 1999-2000 philadelphia flyers season the average number of points scored was 23.25 .

{'scope': 'all', 'col': '6', 'type': 'average', 'result': '23.25', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '23.25', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '23.25'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 23.25 } = true', 'tointer': 'the average of the points record of all rows is 23.25 .'}

round_eq { avg { all_rows ; points } ; 23.25 } = true

the average of the points record of all rows is 23.25 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '23.25_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '23.25_5': '23.25'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '23.25_5': [1]}

['game', 'november', 'opponent', 'score', 'record', 'points']

[['14', '3', 'mighty ducks of anaheim', '3 - 3 ot', '6 - 5 - 2 - 1', '15'], ['15', '5', 'san jose sharks', '3 - 1', '7 - 5 - 2 - 1', '17'], ['16', '6', 'los angeles kings', '5 - 3', '8 - 5 - 2 - 1', '19'], ['17', '9', 'new jersey devils', '1 - 2', '8 - 6 - 2 - 1', '19'], ['18', '11', 'carolina hurricanes', '4 - 1', '9 - 6 - 2 - 1', '21'], ['19', '13', 'san jose sharks', '3 - 2', '10 - 6 - 2 - 1', '23'], ['20', '18', 'dallas stars', '1 - 1 ot', '10 - 6 - 3 - 1', '24'], ['21', '20', 'tampa bay lightning', '4 - 1', '11 - 6 - 3 - 1', '26'], ['22', '22', 'tampa bay lightning', '1 - 4', '11 - 7 - 3 - 1', '26'], ['23', '24', 'florida panthers', '6 - 1', '12 - 7 - 3 - 1', '28'], ['24', '26', 'toronto maple leafs', '3 - 2 ot', '13 - 7 - 3 - 1', '30'], ['25', '28', 'ottawa senators', '3 - 3 ot', '13 - 7 - 4 - 1', '31']]

1938 u.s. open ( golf )

https://en.wikipedia.org/wiki/1938_U.S._Open_%28golf%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18007213-1.html.csv

majority

the majority of the players in the 1938 us open scored at least 9 over par or above .

{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '9', 'subset': None}

{'func': 'most_greater_eq', 'args': ['all_rows', 'to par', '9'], 'result': True, 'ind': 0, 'tointer': 'for the to par records of all rows , most of them are greater than or equal to 9 .', 'tostr': 'most_greater_eq { all_rows ; to par ; 9 } = true'}

most_greater_eq { all_rows ; to par ; 9 } = true

for the to par records of all rows , most of them are greater than or equal to 9 .

1

1

{'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'to par_3': 3, '9_4': 4}

{'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'to par_3': 'to par', '9_4': '9'}

{'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'to par_3': [0], '9_4': [0]}

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

[['1', 'ralph guldahl', 'united states', '74 + 70 + 71 + 69 = 284', 'e', '1000'], ['2', 'dick metz', 'united states', '73 + 68 + 70 + 79 = 290', '+ 6', '800'], ['t3', 'harry cooper', 'england united states', '76 + 69 + 76 + 71 = 292', '+ 8', '650'], ['t3', 'toney penna', 'italy united states', '78 + 72 + 74 + 68 = 292', '+ 8', '650'], ['t5', 'byron nelson', 'united states', '77 + 71 + 74 + 72 = 294', '+ 10', '412'], ['t5', 'emery zimmerman', 'united states', '72 + 71 + 73 + 78 = 294', '+ 10', '412'], ['t7', 'frank moore', 'united states', '79 + 73 + 72 + 71 = 295', '+ 11', '216'], ['t7', 'henry picard', 'united states', '70 + 70 + 77 + 78 = 295', '+ 11', '216'], ['t7', 'paul runyan', 'united states', '78 + 71 + 72 + 74 = 295', '+ 11', '216'], ['10', 'gene sarazen', 'united states', '74 + 74 + 75 + 73 = 296', '+ 12', '106']]

2008 tt pro league

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24039173-1.html.csv

aggregation

in the 2008 tt pro league , the average capacity for each team ’s stadium was 17,313 .

{'scope': 'all', 'col': '4', 'type': 'average', 'result': '17313', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'capacity'], 'result': '17313', 'ind': 0, 'tostr': 'avg { all_rows ; capacity }'}, '17313'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; capacity } ; 17313 } = true', 'tointer': 'the average of the capacity record of all rows is 17313 .'}

round_eq { avg { all_rows ; capacity } ; 17313 } = true

the average of the capacity record of all rows is 17313 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'capacity_4': 4, '17313_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'capacity_4': 'capacity', '17313_5': '17313'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'capacity_4': [0], '17313_5': [1]}

['team', 'location', 'stadium', 'capacity', 'manager', 'captain']

[['caledonia aia', 'morvant / laventille', 'larry gomes stadium', '10000', 'jamaal shabazz', 'sheldon emmanuel'], ['defence force', 'chaguaramas', 'hasely crawford stadium', '27000', 'kerry jamerson', 'anton pierre'], ['joe public', 'arouca', 'marvin lee stadium', '6000', 'derek king', 'dale saunders'], ['ma pau', 'woodbrook', 'hasely crawford stadium', '27000', 'ronald la forest', 'lorne joseph'], ['north east stars', 'sangre grande', 'sangre grande ground', '7000', 'miguel hackett', 'anthony haynes'], ['san juan jabloteh', 'san juan', 'hasely crawford stadium', '27000', 'terry fenwick', 'trent noel'], ["st ann 's rangers", 'san juan', 'hasely crawford stadium', '27000', 'anthony streete', 'errol mcfarlane'], ['tobago united', 'bacolet', 'dwight yorke stadium', '7500', 'peter granville', 'george dublin']]

1987 denver broncos season

https://en.wikipedia.org/wiki/1987_Denver_Broncos_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16727837-1.html.csv

majority

the denver broncos won most of their december games in the 1987 season .

{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None}

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

most_eq { all_rows ; result ; w } = true

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

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]}

['week', 'date', 'opponent', 'result', 'game site', 'record']

[['1', 'september 13', 'seattle seahawks', 'w 40 - 17', 'mile high stadium', '1 - 0'], ['2', 'september 20', 'green bay packers', 't 17 - 17 ( ot )', 'milwaukee county stadium', '1 - 0 - 1'], ['-', 'september 28', 'cleveland browns', 'canceled', 'cleveland stadium', '1 - 0 - 1'], ['4', 'october 4', 'houston oilers', 'l 10 - 40', 'mile high stadium', '1 - 1 - 1'], ['5', 'october 12', 'los angeles raiders', 'w 30 - 14', 'mile high stadium', '2 - 1 - 1'], ['6', 'october 18', 'kansas city chiefs', 'w 26 - 17', 'arrowhead stadium', '3 - 1 - 1'], ['7', 'october 26', 'minnesota vikings', 'l 27 - 34', 'hubert h humphrey metrodome', '3 - 2 - 1'], ['8', 'november 1', 'detroit lions', 'w 34 - 0', 'mile high stadium', '4 - 2 - 1'], ['9', 'november 8', 'buffalo bills', 'l 14 - 21', 'rich stadium', '4 - 3 - 1'], ['10', 'november 16', 'chicago bears', 'w 31 - 29', 'mile high stadium', '5 - 3 - 1'], ['11', 'november 22', 'los angeles raiders', 'w 23 - 17', 'los angeles memorial coliseum', '6 - 3 - 1'], ['12', 'november 29', 'san diego chargers', 'w 31 - 17', 'jack murphy stadium', '7 - 3 - 1'], ['13', 'december 6', 'new england patriots', 'w 31 - 20', 'mile high stadium', '8 - 3 - 1'], ['14', 'december 13', 'seattle seahawks', 'l 21 - 28', 'kingdome', '8 - 4 - 1'], ['15', 'december 19', 'kansas city chiefs', 'w 20 - 17', 'mile high stadium', '9 - 4 - 1'], ['16', 'december 27', 'san diego chargers', 'w 24 - 0', 'mile high stadium', '10 - 4 - 1']]

2004 nba expansion draft

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15623086-3.html.csv

unique

the golden state warriors were the only team to take a player from bosnia and herzegovina in the 2004 expansion draft .

{'scope': 'all', 'row': '2', 'col': '2', 'col_other': '3', 'criterion': 'equal', 'value': 'bosnia and herzegovina', 'subset': None}

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

and { only { filter_eq { all_rows ; nationality ; bosnia and herzegovina } } ; eq { hop { filter_eq { all_rows ; nationality ; bosnia and herzegovina } ; previous team } ; golden state warriors } } = true

select the rows whose nationality record fuzzily matches to bosnia and herzegovina . there is only one such row in the table . the previous team record of this unqiue row is golden state warriors .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'bosnia and herzegovina_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'previous team_9': 9, 'golden state warriors_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'bosnia and herzegovina_8': 'bosnia and herzegovina', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'previous team_9': 'previous team', 'golden state warriors_10': 'golden state warriors'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'bosnia and herzegovina_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'previous team_9': [2], 'golden state warriors_10': [3]}

['pos', 'nationality', 'previous team', 'nba years', 'career with the franchise']

[['f', 'united states', 'washington wizards', '2', '2006'], ['g', 'bosnia and herzegovina', 'golden state warriors', '2', '-'], ['c', 'slovenia', 'indiana pacers', '3', '2004 - 2007'], ['g', 'united states', 'new orleans hornets', '1', '-'], ['c', 'montenegro', 'los angeles clippers', '3', '-'], ['g / f', 'united states', 'portland trail blazers', '1', '-'], ['f', 'united states', 'chicago bulls', '4', '-'], ['g', 'united states', 'seattle supersonics', '1', '-'], ['f', 'united states', 'boston celtics', '1', '-'], ['f', 'united states', 'cleveland cavaliers', '1', '2004 - 2005'], ['c', 'georgia', 'orlando magic', '1', '-'], ['g / f', 'serbia', 'utah jazz', '1', '-'], ['f / c', 'united states', 'los angeles lakers', '2', '2004 - 2005'], ['g', 'united states', 'new jersey nets', '2', '2004 - 2005'], ['f', 'united states', 'memphis grizzlies', '1', '2004 - 2005'], ['g', 'united states', 'denver nuggets', '3', '-'], ['f', 'united states', 'sacramento kings', '3', '2004 - 2011'], ['f / c', 'united states', 'phoenix suns', '6', '2004 - 2005'], ['f / c', 'united states', 'miami heat', '3', '-']]

wong chin hung

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13035867-2.html.csv

unique

of wong chin hung 's competitions , the only one that was a 2014 fifa world cup qualification was on july 28 , 2011 .

{'scope': 'all', 'row': '10', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '2014 fifa world cup qualification', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '2014 fifa world cup qualification'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to 2014 fifa world cup qualification .', 'tostr': 'filter_eq { all_rows ; competition ; 2014 fifa world cup qualification }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; competition ; 2014 fifa world cup qualification } }', 'tointer': 'select the rows whose competition record fuzzily matches to 2014 fifa world cup qualification . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '2014 fifa world cup qualification'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to 2014 fifa world cup qualification .', 'tostr': 'filter_eq { all_rows ; competition ; 2014 fifa world cup qualification }'}, 'date'], 'result': '28 july 2011', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; competition ; 2014 fifa world cup qualification } ; date }'}, '28 july 2011'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; competition ; 2014 fifa world cup qualification } ; date } ; 28 july 2011 }', 'tointer': 'the date record of this unqiue row is 28 july 2011 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; competition ; 2014 fifa world cup qualification } } ; eq { hop { filter_eq { all_rows ; competition ; 2014 fifa world cup qualification } ; date } ; 28 july 2011 } } = true', 'tointer': 'select the rows whose competition record fuzzily matches to 2014 fifa world cup qualification . there is only one such row in the table . the date record of this unqiue row is 28 july 2011 .'}

and { only { filter_eq { all_rows ; competition ; 2014 fifa world cup qualification } } ; eq { hop { filter_eq { all_rows ; competition ; 2014 fifa world cup qualification } ; date } ; 28 july 2011 } } = true

select the rows whose competition record fuzzily matches to 2014 fifa world cup qualification . there is only one such row in the table . the date record of this unqiue row is 28 july 2011 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'competition_7': 7, '2014 fifa world cup qualification_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '28 july 2011_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'competition_7': 'competition', '2014 fifa world cup qualification_8': '2014 fifa world cup qualification', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '28 july 2011_10': '28 july 2011'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'competition_7': [0], '2014 fifa world cup qualification_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '28 july 2011_10': [3]}

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

[['19 november 2008', 'macau ust stadium , macau', '9 - 1', '0', 'friendly'], ['23 august 2009', 'world games stadium , kaohsiung , taiwan', '4 - 0', '0', '2010 eaff championship semi - finals'], ['27 august 2009', 'world games stadium , kaohsiung , taiwan', '12 - 0', '1', '2010 eaff championship semi - finals'], ['18 november 2009', 'hong kong stadium , hong kong', '0 - 4', '0', '2011 afc asian cup qualification'], ['11 february 2010', 'olympic stadium , tokyo , japan', '0 - 3', '0', '2010 east asian football championship'], ['14 february 2010', 'olympic stadium , tokyo , japan', '0 - 2', '0', '2010 east asian football championship'], ['3 march 2010', 'hong kong stadium , hong kong', '0 - 0', '0', '2011 afc asian cup qualification'], ['9 february 2011', 'shah alam stadium , kuala lumpur', '0 - 2', '0', 'friendly'], ['3 june 2011', 'siu sai wan sports ground , hong kong', '1 - 1', '0', 'friendly'], ['28 july 2011', 'siu sai wan sports ground , hong kong', '0 - 5', '0', '2014 fifa world cup qualification'], ['30 september 2011', 'kaohsiung national stadium , kaohsiung , taiwan', '3 - 3', '0', '2011 long teng cup'], ['2 october 2011', 'kaohsiung national stadium , kaohsiung , taiwan', '5 - 1', '2', '2011 long teng cup'], ['4 october 2011', 'kaohsiung national stadium , kaohsiung , taiwan', '6 - 0', '0', '2011 long teng cup']]

2007 european curling championships

https://en.wikipedia.org/wiki/2007_European_Curling_Championships

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14385184-56.html.csv

unique

only one team in the 2007 european curling championships was representing serbia .

{'scope': 'all', 'row': '6', 'col': '1', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'serbia', 'subset': None}

{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'serbia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to serbia .', 'tostr': 'filter_eq { all_rows ; nation ; serbia }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nation ; serbia } } = true', 'tointer': 'select the rows whose nation record fuzzily matches to serbia . there is only one such row in the table .'}

only { filter_eq { all_rows ; nation ; serbia } } = true

select the rows whose nation record fuzzily matches to serbia . there is only one such row in the table .

2

2

{'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'nation_4': 4, 'serbia_5': 5}

{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'nation_4': 'nation', 'serbia_5': 'serbia'}

{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'nation_4': [0], 'serbia_5': [0]}

['nation', 'skip', 'third', 'second', 'lead']

[['belarus', 'oleksii voloshenko', 'siarhei sarokin', 'alexandr radaev', 'aliaksandr tsiushkevich'], ['bulgaria', 'nikolai runtov', 'tihomir todorov', 'stoil georgiev', 'ilian kirilov'], ['england', 'andrew reed', 'james dixon', 'tom jaeggi', 'andrew dixon'], ['latvia', 'ritvars gulbis', 'ainars gulbis', 'aivars avotins', 'normunds sarsuns'], ['lithuania', 'martynas norkus', 'vygantas zalieckas', 'piotras gerasimovic', 'dalius garakvinas'], ['serbia', 'marko stojanovic', 'darko sovran', 'bojan mijatovic', 'vuk krajacic'], ['wales', 'jamie meikle', 'stuart hills', 'andrew tanner', 'james pougher']]

united states house of representatives elections , 1800

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1800

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668401-17.html.csv

unique

john nicholas was the only virginia incumbent in the 1800 united states house of representatives elections that was first elected in 1793 .

{'scope': 'all', 'row': '13', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '1793', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'first elected', '1793'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record is equal to 1793 .', 'tostr': 'filter_eq { all_rows ; first elected ; 1793 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; first elected ; 1793 } }', 'tointer': 'select the rows whose first elected record is equal to 1793 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'first elected', '1793'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record is equal to 1793 .', 'tostr': 'filter_eq { all_rows ; first elected ; 1793 }'}, 'incumbent'], 'result': 'john nicholas', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; first elected ; 1793 } ; incumbent }'}, 'john nicholas'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; first elected ; 1793 } ; incumbent } ; john nicholas }', 'tointer': 'the incumbent record of this unqiue row is john nicholas .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; first elected ; 1793 } } ; eq { hop { filter_eq { all_rows ; first elected ; 1793 } ; incumbent } ; john nicholas } } = true', 'tointer': 'select the rows whose first elected record is equal to 1793 . there is only one such row in the table . the incumbent record of this unqiue row is john nicholas .'}

and { only { filter_eq { all_rows ; first elected ; 1793 } } ; eq { hop { filter_eq { all_rows ; first elected ; 1793 } ; incumbent } ; john nicholas } } = true

select the rows whose first elected record is equal to 1793 . there is only one such row in the table . the incumbent record of this unqiue row is john nicholas .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'first elected_7': 7, '1793_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'john nicholas_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'first elected_7': 'first elected', '1793_8': '1793', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'john nicholas_10': 'john nicholas'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'first elected_7': [0], '1793_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'john nicholas_10': [3]}

['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']

[['virginia 2', 'david holmes', 'democratic - republican', '1797', 're - elected', 'david holmes ( dr ) alexander sinclair ( f )'], ['virginia 4', 'abram trigg', 'democratic - republican', '1797', 're - elected', 'abram trigg ( dr )'], ['virginia 5', 'john j trigg', 'democratic - republican', '1797', 're - elected', 'john j trigg ( dr )'], ['virginia 6', 'matthew clay', 'democratic - republican', '1797', 're - elected', 'matthew clay ( dr )'], ['virginia 7', 'john randolph', 'democratic - republican', '1799', 're - elected', 'john randolph ( dr )'], ['virginia 8', 'samuel goode', 'federalist', '1799', 'democratic - republican gain', 'thomas claiborne ( dr )'], ['virginia 9', 'joseph eggleston', 'democratic - republican', '1798 ( special )', 'democratic - republican hold', 'william b giles ( dr )'], ['virginia 10', 'edwin gray', 'democratic - republican', '1799', 're - elected', 'edwin gray ( dr ) nicholas faulcon ( dr )'], ['virginia 12', 'thomas evans', 'federalist', '1797', 'retired federalist hold', 'john stratton ( f ) john page ( dr )'], ['virginia 13', 'littleton waller tazewell', 'democratic - republican', '1800 ( special )', 'retired democratic - republican hold', 'john clopton ( dr ) samuel tyler ( dr )'], ['virginia 14', 'samuel j cabell', 'democratic - republican', '1795', 're - elected', 'samuel j cabell ( dr )'], ['virginia 15', 'john dawson', 'democratic - republican', '1797', 're - elected', 'john dawson ( dr )'], ['virginia 18', 'john nicholas', 'democratic - republican', '1793', 'retired democratic - republican hold', 'philip r thompson ( dr ) john blackwell ( f )']]

1997 - 98 a pfg

https://en.wikipedia.org/wiki/1997%E2%80%9398_A_PFG

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10533828-2.html.csv

aggregation

during 1997-98 a pfg season , an average number of points earned by clubs was 43 .

{'scope': 'all', 'col': '9', 'type': 'average', 'result': '43', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '43', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '43'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 43 } = true', 'tointer': 'the average of the points record of all rows is 43 .'}

round_eq { avg { all_rows ; points } ; 43 } = true

the average of the points record of all rows is 43 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '43_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '43_5': '43'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '43_5': [1]}

['position', 'club', 'played', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'points', 'goal difference']

[['1', 'litex lovech', '30', '21', '6', '3', '73', '25', '69', '+ 38'], ['2', 'levski sofia', '30', '19', '7', '4', '73', '27', '64', '+ 36'], ['3', 'cska sofia', '30', '18', '7', '5', '71', '29', '61', '+ 38'], ['4', 'neftochimic burgas', '30', '17', '4', '9', '59', '31', '55', '+ 28'], ['5', 'slavia sofia', '30', '15', '9', '6', '51', '30', '54', '+ 21'], ['6', 'levski kyustendil', '30', '15', '1', '14', '45', '40', '46', '+ 5'], ['7', 'spartak varna', '30', '12', '6', '12', '42', '36', '42', '+ 8'], ['8', 'minyor pernik', '30', '12', '5', '13', '32', '35', '41', '- 3'], ['9', 'lokomotiv sofia', '30', '11', '6', '13', '42', '40', '39', '+ 2'], ['10', 'metalurg pernik', '30', '11', '4', '15', '28', '36', '37', '- 8'], ['11', 'botev plovdiv', '30', '11', '3', '16', '35', '48', '36', '- 13'], ['12', 'dobrudzha dobrich', '30', '11', '3', '16', '33', '55', '36', '- 12'], ['13', 'lokomotiv plovdiv', '30', '11', '3', '16', '31', '58', '36', '- 27'], ['14', 'olimpik teteven', '30', '11', '2', '17', '26', '47', '35', '- 21'], ['15', 'spartak pleven', '30', '7', '0', '23', '32', '75', '21', '- 43'], ['16', 'etar veliko tarnovo', '30', '4', '2', '24', '21', '82', '14', '- 61']]

2009 - 10 denver nuggets season

https://en.wikipedia.org/wiki/2009%E2%80%9310_Denver_Nuggets_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23285849-5.html.csv

count

6 of denver nuggets ' games were played at the pepsi center .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'pepsi center', 'result': '6', 'col': '8', 'subset': None}

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

eq { count { filter_eq { all_rows ; location attendance ; pepsi center } } ; 6 } = true

select the rows whose location attendance record fuzzily matches to pepsi center . 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, 'location attendance_5': 5, 'pepsi center_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', 'location attendance_5': 'location attendance', 'pepsi center_6': 'pepsi center', '6_7': '6'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'pepsi center_6': [0], '6_7': [2]}

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

[['3', 'november 1', 'grizzlies', 'w 133 - 123 ( ot )', 'carmelo anthony ( 42 )', 'nenê ( 9 )', 'chauncey billups ( 12 )', 'pepsi center 15823', '3 - 0'], ['4', 'november 3', 'pacers', 'w 111 - 93 ( ot )', 'carmelo anthony ( 25 )', 'nenê ( 13 )', 'anthony carter ( 5 )', 'conseco fieldhouse 10627', '4 - 0'], ['5', 'november 4', 'nets', 'w 122 - 94 ( ot )', 'ty lawson ( 23 )', 'kenyon martin ( 10 )', 'chauncey billups ( 5 )', 'izod center 15319', '5 - 0'], ['7', 'november 7', 'hawks', 'l 100 - 125 ( ot )', 'carmelo anthony ( 30 )', 'chris andersen ( 11 )', 'chauncey billups ( 7 )', 'philips arena 17801', '5 - 2'], ['8', 'november 10', 'bulls', 'w 90 - 89 ( ot )', 'carmelo anthony ( 20 )', 'nenê ( 12 )', 'chauncey billups ( 6 )', 'united center 21409', '6 - 2'], ['9', 'november 11', 'bucks', 'l 102 - 108 ( ot )', 'carmelo anthony ( 32 )', 'carmelo anthony ( 10 )', 'chauncey billups , ty lawson ( 5 )', 'bradley center 12987', '6 - 3'], ['10', 'november 13', 'lakers', 'w 105 - 79 ( ot )', 'carmelo anthony ( 25 )', 'chris andersen ( 11 )', 'chauncey billups ( 8 )', 'pepsi center 19141', '7 - 3'], ['11', 'november 17', 'raptors', 'w 130 - 112 ( ot )', 'carmelo anthony ( 32 )', 'nenê ( 10 )', 'chauncey billups ( 10 )', 'pepsi center 16446', '8 - 3'], ['12', 'november 20', 'clippers', 'l 99 - 106 ( ot )', 'carmelo anthony ( 37 )', 'nenê ( 12 )', 'chauncey billups ( 7 )', 'staples center 18155', '8 - 4'], ['13', 'november 21', 'bulls', 'w 112 - 93 ( ot )', 'carmelo anthony ( 30 )', 'carmelo anthony , kenyon martin ( 11 )', 'carmelo anthony ( 7 )', 'pepsi center 19359', '9 - 4'], ['14', 'november 24', 'nets', 'w 101 - 87 ( ot )', 'carmelo anthony ( 27 )', 'nenê ( 9 )', 'chauncey billups ( 7 )', 'pepsi center 16307', '10 - 4'], ['15', 'november 25', 'timberwolves', 'w 124 - 111 ( ot )', 'carmelo anthony ( 22 )', 'nenê ( 8 )', 'nenê , ty lawson ( 6 )', 'target center 13101', '11 - 4'], ['16', 'november 27', 'knicks', 'w 128 - 125 ( ot )', 'carmelo anthony ( 50 )', 'nenê , kenyon martin ( 11 )', 'chauncey billups ( 8 )', 'pepsi center 19155', '12 - 4']]

robby gordon

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1507423-4.html.csv

superlative

the highest amount of winnings that robby gordon had was in 2004 .

{'scope': 'all', 'col_superlative': '9', 'row_superlative': '11', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'winnings'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; winnings }'}, 'year'], 'result': '2004', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; winnings } ; year }'}, '2004'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; winnings } ; year } ; 2004 } = true', 'tointer': 'select the row whose winnings record of all rows is maximum . the year record of this row is 2004 .'}

eq { hop { argmax { all_rows ; winnings } ; year } ; 2004 } = true

select the row whose winnings record of all rows is maximum . the year record of this row is 2004 .

3

3

{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'winnings_5': 5, 'year_6': 6, '2004_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'winnings_5': 'winnings', 'year_6': 'year', '2004_7': '2004'}

{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'winnings_5': [0], 'year_6': [1], '2004_7': [2]}

['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position']

[['1991', '2', '0', '0', '0', '0', '35.0', '22.0', '27625', '55th'], ['1993', '1', '0', '0', '0', '0', '14.0', '42.0', '17665', '93rd'], ['1994', '1', '0', '0', '0', '0', '38.0', '38.0', '7965', '76th'], ['1996', '3', '0', '0', '0', '0', '17.3', '40.7', '33915', '57th'], ['1997', '20', '0', '1', '1', '1', '25.3', '29.6', '622439', '40th'], ['1998', '1', '0', '0', '0', '0', '18.0', '37.0', '24765', '67th'], ['2000', '17', '0', '1', '2', '0', '29.9', '29.2', '620781', '43rd'], ['2001', '17', '1', '2', '3', '0', '32.4', '24.8', '1371900', '44th'], ['2002', '36', '0', '1', '5', '0', '18.4', '21.1', '3342703', '20th'], ['2003', '36', '2', '4', '10', '0', '23.1', '19.7', '4157064', '16th'], ['2004', '36', '0', '2', '6', '0', '23.2', '21.2', '4225719', '23rd'], ['2005', '29', '0', '1', '2', '0', '27.0', '30.1', '2271313', '37th'], ['2006', '36', '0', '1', '3', '0', '27.5', '25.3', '3143787', '30th'], ['2007', '35', '0', '1', '2', '0', '33.9', '25.8', '3090004', '26th'], ['2008', '36', '0', '0', '3', '0', '30.9', '29.0', '3816362', '33rd'], ['2009', '35', '0', '1', '1', '0', '30.1', '28.5', '3860582', '34th'], ['2010', '27', '0', '1', '1', '0', '33.8', '29.1', '2913816', '34th'], ['2011', '25', '0', '0', '0', '0', '36.5', '33.4', '2271891', '34th'], ['2012', '3', '0', '0', '0', '0', '30.0', '40.3', '405300', '52nd']]

list of soccer clubs in australia

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1742186-14.html.csv

count

two of the soccer clubs of australia were founded in the 1990 's .

{'scope': 'all', 'criterion': 'greater_than_eq', 'value': '1990', 'result': '2', 'col': '5', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'founded', '1990'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose founded record is greater than or equal to 1990 .', 'tostr': 'filter_greater_eq { all_rows ; founded ; 1990 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; founded ; 1990 } }', 'tointer': 'select the rows whose founded record is greater than or equal to 1990 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; founded ; 1990 } } ; 2 } = true', 'tointer': 'select the rows whose founded record is greater than or equal to 1990 . the number of such rows is 2 .'}

eq { count { filter_greater_eq { all_rows ; founded ; 1990 } } ; 2 } = true

select the rows whose founded record is greater than or equal to 1990 . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'founded_5': 5, '1990_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'founded_5': 'founded', '1990_6': '1990', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'founded_5': [0], '1990_6': [0], '2_7': [2]}

['team', 'coach', 'home ground', 'location', 'founded']

[['adelaide blue eagles', 'zoran karadzic', 'marden sports complex', 'marden', '1958'], ['adelaide city', 'damian mori', 'adelaide city park', 'oakden', '1946'], ['adelaide galaxy', 'brenton heirn', 'con makris park', 'novar gardens', '1933'], ['adelaide raiders', 'michael barnett', 'croatian sports centre', 'gepps cross', '1952'], ['campbelltown city', 'jason trimboli', 'newton sportsground', 'campbelltown', '1963'], ['croydon kings', 'john kosmina', 'polonia reserve', 'croydon', '1950'], ['modbury jets', 'earl pudler', 'jet park', 'modbury north', '1964'], ['metrostars', 'david terminello', 'tk shutter reserve', 'klemzig', '1994'], ['para hills knights', 'kenneth tosh', 'the paddocks', 'para hills', '1964'], ['western strikers', 'charlie villani', 'carnegie reserve', 'royal park', '1998']]

elitexc : street certified

https://en.wikipedia.org/wiki/EliteXC%3A_Street_Certified

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15157472-1.html.csv

unique

the scott smith and kyle noke fight was the only fight to last less than 10 seconds .

{'scope': 'all', 'row': '3', 'col': '6', 'col_other': '2,3', 'criterion': 'less_than', 'value': '0:10', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'time', '0:10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record is less than 0:10 .', 'tostr': 'filter_less { all_rows ; time ; 0:10 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; time ; 0:10 } }', 'tointer': 'select the rows whose time record is less than 0:10 . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'time', '0:10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record is less than 0:10 .', 'tostr': 'filter_less { all_rows ; time ; 0:10 }'}, 'winner'], 'result': 'scott smith', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; time ; 0:10 } ; winner }'}, 'scott smith'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; time ; 0:10 } ; winner } ; scott smith }', 'tointer': 'the winner record of this unqiue row is scott smith .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'time', '0:10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record is less than 0:10 .', 'tostr': 'filter_less { all_rows ; time ; 0:10 }'}, 'loser'], 'result': 'kyle noke', 'ind': 4, 'tostr': 'hop { filter_less { all_rows ; time ; 0:10 } ; loser }'}, 'kyle noke'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_less { all_rows ; time ; 0:10 } ; loser } ; kyle noke }', 'tointer': 'the loser record of this unqiue row is kyle noke .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_less { all_rows ; time ; 0:10 } ; winner } ; scott smith } ; eq { hop { filter_less { all_rows ; time ; 0:10 } ; loser } ; kyle noke } }', 'tointer': 'the winner record of this unqiue row is scott smith . the loser record of this unqiue row is kyle noke .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_less { all_rows ; time ; 0:10 } } ; and { eq { hop { filter_less { all_rows ; time ; 0:10 } ; winner } ; scott smith } ; eq { hop { filter_less { all_rows ; time ; 0:10 } ; loser } ; kyle noke } } } = true', 'tointer': 'select the rows whose time record is less than 0:10 . there is only one such row in the table . the winner record of this unqiue row is scott smith . the loser record of this unqiue row is kyle noke .'}

and { only { filter_less { all_rows ; time ; 0:10 } } ; and { eq { hop { filter_less { all_rows ; time ; 0:10 } ; winner } ; scott smith } ; eq { hop { filter_less { all_rows ; time ; 0:10 } ; loser } ; kyle noke } } } = true

select the rows whose time record is less than 0:10 . there is only one such row in the table . the winner record of this unqiue row is scott smith . the loser record of this unqiue row is kyle noke .

10

8

{'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_less_0': 0, 'all_rows_9': 9, 'time_10': 10, '0:10_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'winner_12': 12, 'scott smith_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'loser_14': 14, 'kyle noke_15': 15}

{'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_9': 'all_rows', 'time_10': 'time', '0:10_11': '0:10', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'winner_12': 'winner', 'scott smith_13': 'scott smith', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'loser_14': 'loser', 'kyle noke_15': 'kyle noke'}

{'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_less_0': [1, 2, 4], 'all_rows_9': [0], 'time_10': [0], '0:10_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'winner_12': [2], 'scott smith_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'loser_14': [4], 'kyle noke_15': [5]}

['weight division', 'winner', 'loser', 'method', 'round', 'time']

[['heavyweight', 'kimbo slice', 'tank abbott', 'ko ( punch )', '1', '0:43'], ['heavyweight', 'antonio silva', 'ricco rodriguez', 'decision ( split )', '3', '5:00'], ['middleweight', 'scott smith', 'kyle noke', 'ko ( punch )', '2', '0:07'], ['lightweight', 'yves edwards', 'james edson berto', 'ko ( flying knee )', '1', '4:56'], ['heavyweight', 'brett rogers', 'james thompson', 'tko ( strikes )', '1', '2:24']]

2008 - 09 leeds united a.f.c. season

https://en.wikipedia.org/wiki/2008%E2%80%9309_Leeds_United_A.F.C._season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17634290-7.html.csv

superlative

becchio from argentina had the highest transfer fee amongst all united afc players in 2008-2009 .

{'scope': 'all', 'col_superlative': '7', 'row_superlative': '5', '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', 'transfer fee'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; transfer fee }'}, 'name'], 'result': 'becchio', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; transfer fee } ; name }'}, 'becchio'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; transfer fee } ; name } ; becchio } = true', 'tointer': 'select the row whose transfer fee record of all rows is maximum . the name record of this row is becchio .'}

eq { hop { argmax { all_rows ; transfer fee } ; name } ; becchio } = true

select the row whose transfer fee record of all rows is maximum . the name record of this row is becchio .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'transfer fee_5': 5, 'name_6': 6, 'becchio_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'transfer fee_5': 'transfer fee', 'name_6': 'name', 'becchio_7': 'becchio'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'transfer fee_5': [0], 'name_6': [1], 'becchio_7': [2]}

['name', 'country', 'type', 'moving from', 'transfer window', 'ends', 'transfer fee', 'source']

[['robinson', 'eng', 'free agent', 'swansea city', 'summer', '2011', 'free', 'leeds united yorkshire evening post'], ['sheehan', 'ire', 'transferred 1', 'leicester city', 'summer', '2011', 'undisclosed', 'leeds united'], ['showunmi', 'ngr eng', 'free agent', 'bristol city', 'summer', '2010', 'free', 'leeds united'], ['snodgrass', 'sco', 'free agent 1', 'livingston', 'summer', '2011', '35k 2', 'leeds united'], ['becchio', 'arg', 'transferred', 'mérida ud', 'summer', '2011', '300k 3', 'leeds united'], ['telfer', 'sco', 'free agent', 'bournemouth', 'summer', '2009 4', 'free', 'leeds united'], ['christie', 'eng', 'free agent', 'middlesbrough', 'summer', 'n / a 5', 'free', 'leeds united'], ['assoumani', 'mli fra', 'free agent', 'sportfreunde siegen', 'summer', '2009', 'free', 'leeds united'], ['grella', 'usa', 'free agent', 'cary clarets', 'winter', '2010', 'free', 'leeds united'], ['naylor', 'eng', 'transferred', 'ipswich town', 'winter', '2011', 'free', 'leeds united']]

2010 isle of man tt

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25220821-3.html.csv

count

there were 8 riders for the 2010 isle of man tt .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '8', 'col': '2', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'rider'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rider record is arbitrary .', 'tostr': 'filter_all { all_rows ; rider }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; rider } }', 'tointer': 'select the rows whose rider record is arbitrary . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; rider } } ; 8 } = true', 'tointer': 'select the rows whose rider record is arbitrary . the number of such rows is 8 .'}

eq { count { filter_all { all_rows ; rider } } ; 8 } = true

select the rows whose rider record is arbitrary . the number of such rows is 8 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'rider_5': 5, '8_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'rider_5': 'rider', '8_6': '8'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'rider_5': [0], '8_6': [2]}

['rank', 'rider', 'sat 29 may', 'mon 31 may', 'tues 1 june', 'wed 2 june', 'thurs 3 june', 'fri 4 june']

[['2', 'klaus klaffenböck / dan sayle 600cc lcr honda', 'cancelled no time', "20 ' 15.35 111.761 mph", "20 ' 05.79 112.647 mph", "19 ' 55.92 113.576 mph", "19 ' 50.47 114.096 mph", "19 ' 56.64 113.508 mph"], ['3', 'john holden / andrew winkle 600cc lcr suzuki', 'cancelled no time', "20 ' 17.36 111.576 mph", "20 ' 09.86 112.267 mph", "20 ' 04.82 112.737 mph", "20 ' 15.90 111.710 mph", "19 ' 59.43 113.224 mph"], ['4', 'simon neary / paul knapton 600cc honda', 'cancelled no time', "20 ' 24.08 110.964 mph", "20 ' 05.64 112.661 mph", "20 ' 11.98 112.071 mph", "20 ' 00.19 113.172 mph", "20 ' 01.41 113.058 mph"], ['5', 'conrad harrison / kerry williams 600cc honda', 'cancelled no time', "20 ' 50.30 108.636 mph", "20 ' 27.78 110.629 mph", "20 ' 25.77 110.810 mph", "20 ' 13.17 111.962 mph", "20 ' 29.39 110.484 mph"], ['6', 'tim reeves / dipash chauhan 600cc honda', 'cancelled no time', '-- no time', "20 ' 59.60 107.834 mph", "20 ' 45.81 109.028 mph", "20 ' 26.35 110.758 mph", "37 ' 03.92 61.076 mph"], ['7', 'gary bryan / gary partridge 600cc honda', 'cancelled no time', "21 ' 21.24 106.013 mph", "21 ' 09.41 107.001 mph", "20 ' 47.90 108.845 mph", "20 ' 27.35 110.668 mph", "20 ' 40.91 109.459 mph"], ['8', 'roy hanks / dave wells 600cc suzuki', 'cancelled no time', "21 ' 36.43 104.771 mph", "21 ' 05.27 107.351 mph", "20 ' 50.62 108.608 mph", "20 ' 27.93 110.615 mph", '-- no time'], ['9', 'tony elmer / darren marshall 600cc ireson yamaha', 'cancelled no time', "21 ' 35.11 108.877 mph", "21 ' 02.66 107.573 mph", "20 ' 43.24 109.253 mph", "20 ' 28.72 110.554 mph", "20 ' 39.74 109.562 mph"]]

1946 vfl season

https://en.wikipedia.org/wiki/1946_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809368-13.html.csv

comparative

the game played at punt road oval had a larger crowd than the game played at glenferrie oval .

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

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'punt road oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to punt road oval .', 'tostr': 'filter_eq { all_rows ; venue ; punt road oval }'}, 'crowd'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; punt road oval } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to punt road oval . take the crowd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'glenferrie oval'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to glenferrie oval .', 'tostr': 'filter_eq { all_rows ; venue ; glenferrie oval }'}, 'crowd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; venue ; glenferrie oval } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to glenferrie oval . take the crowd record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; venue ; punt road oval } ; crowd } ; hop { filter_eq { all_rows ; venue ; glenferrie oval } ; crowd } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to punt road oval . take the crowd record of this row . select the rows whose venue record fuzzily matches to glenferrie oval . take the crowd record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; venue ; punt road oval } ; crowd } ; hop { filter_eq { all_rows ; venue ; glenferrie oval } ; crowd } } = true

select the rows whose venue record fuzzily matches to punt road oval . take the crowd record of this row . select the rows whose venue record fuzzily matches to glenferrie oval . take the crowd 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, 'venue_7': 7, 'punt road oval_8': 8, 'crowd_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'venue_11': 11, 'glenferrie oval_12': 12, 'crowd_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', 'venue_7': 'venue', 'punt road oval_8': 'punt road oval', 'crowd_9': 'crowd', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'venue_11': 'venue', 'glenferrie oval_12': 'glenferrie oval', 'crowd_13': 'crowd'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'venue_7': [0], 'punt road oval_8': [0], 'crowd_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'venue_11': [1], 'glenferrie oval_12': [1], 'crowd_13': [3]}

['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']

[['north melbourne', '6.11 ( 47 )', 'richmond', '11.9 ( 75 )', 'arden street oval', '10000', '20 july 1946'], ['footscray', '5.11 ( 41 )', 'st kilda', '6.10 ( 46 )', 'western oval', '10000', '20 july 1946'], ['hawthorn', '15.22 ( 112 )', 'geelong', '11.15 ( 81 )', 'glenferrie oval', '5000', '20 july 1946'], ['south melbourne', '9.13 ( 67 )', 'essendon', '10.8 ( 68 )', 'junction oval', '23000', '20 july 1946'], ['fitzroy', '8.8 ( 56 )', 'collingwood', '8.13 ( 61 )', 'brunswick street oval', '15000', '20 july 1946'], ['melbourne', '10.12 ( 72 )', 'carlton', '7.13 ( 55 )', 'punt road oval', '26000', '20 july 1946']]

2005 tim hortons brier

https://en.wikipedia.org/wiki/2005_Tim_Hortons_Brier

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1505809-2.html.csv

unique

rod macdonald was the only participant in the 2005 tim hortons brier from the locale of prince edward island .

{'scope': 'all', 'row': '9', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': 'prince edward island', 'subset': None}

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

and { only { filter_eq { all_rows ; locale ; prince edward island } } ; eq { hop { filter_eq { all_rows ; locale ; prince edward island } ; skip } ; rod macdonald } } = true

select the rows whose locale record fuzzily matches to prince edward island . there is only one such row in the table . the skip record of this unqiue row is rod macdonald .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'locale_7': 7, 'prince edward island_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'skip_9': 9, 'rod macdonald_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'locale_7': 'locale', 'prince edward island_8': 'prince edward island', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'skip_9': 'skip', 'rod macdonald_10': 'rod macdonald'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'locale_7': [0], 'prince edward island_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'skip_9': [2], 'rod macdonald_10': [3]}

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

[['alberta', 'randy ferbey', '9', '2', '90', '58', '48', '43', '7', '9', '86 %'], ['manitoba', 'randy dutiaume', '8', '3', '77', '69', '47', '44', '10', '13', '79 %'], ['nova scotia', 'shawn adams', '8', '3', '80', '60', '47', '41', '16', '13', '83 %'], ['quebec', 'jean - michel mãnard', '7', '4', '77', '69', '54', '40', '8', '15', '80 %'], ['british columbia', 'deane horning', '6', '5', '72', '65', '47', '45', '18', '12', '80 %'], ['ontario', 'wayne middaugh', '6', '5', '75', '62', '42', '46', '10', '7', '82 %'], ['newfoundland and labrador', 'brad gushue', '6', '5', '76', '69', '48', '45', '13', '10', '79 %'], ['saskatchewan', 'pat simmons', '6', '5', '66', '61', '43', '45', '12', '9', '80 %'], ['prince edward island', 'rod macdonald', '4', '7', '67', '85', '41', '51', '12', '5', '79 %'], ['northern ontario', 'mike jakubo', '3', '8', '64', '86', '41', '48', '9', '6', '79 %'], ['new brunswick', 'wade blanchard', '3', '8', '56', '83', '41', '45', '17', '8', '78 %']]

scott ferrozzo

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17958251-2.html.csv

aggregation

scott ferrozzo has fought in a total of 6 rounds .

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

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'round'], 'result': '6', 'ind': 0, 'tostr': 'sum { all_rows ; round }'}, '6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; round } ; 6 } = true', 'tointer': 'the sum of the round record of all rows is 6 .'}

round_eq { sum { all_rows ; round } ; 6 } = true

the sum of the round record of all rows is 6 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'round_4': 4, '6_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'round_4': 'round', '6_5': '6'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'round_4': [0], '6_5': [1]}

['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location']

[['loss', '4 - 2', 'vitor belfort', 'tko ( punches )', 'ufc 12', '1', '0:43', 'dothan , alabama , united states'], ['win', '4 - 1', 'jim mullen', 'tko ( punches )', 'ufc 12', '1', '8:02', 'dothan , alabama , united states'], ['win', '3 - 1', 'tank abbott', 'decision ( unanimous )', 'ufc 11', '1', '15:00', 'augusta , georgia , united states'], ['win', '2 - 1', 'sam fulton', 'submission ( strikes )', 'ufc 11', '1', '9:00', 'augusta , georgia , united states'], ['win', '1 - 1', 'steve grinnow', 'ko', 'atlanta fights', '1', '11:58', 'atlanta , georgia , united states'], ['loss', '0 - 1', 'jerry bohlander', 'submission ( guillotine choke )', 'ufc 8', '1', '9:03', 'san juan , puerto rico']]

2010 - 11 atlanta hawks season

https://en.wikipedia.org/wiki/2010%E2%80%9311_Atlanta_Hawks_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27734577-8.html.csv

majority

during this period of the 2010-2011 atlanta hawks season , the atlanta hawks won most of their games .

{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None}

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

most_eq { all_rows ; score ; w } = true

for the score records of all rows , most of them fuzzily match to w .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, 'w_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', 'w_4': 'w'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], 'w_4': [0]}

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

[['36', 'january 2', 'la clippers', 'w 107 - 98 ( ot )', 'joe johnson ( 29 )', 'al horford , josh smith ( 10 )', 'mike bibby , jamal crawford , joe johnson ( 4 )', 'staples center 16750', '22 - 14'], ['37', 'january 4', 'sacramento', 'w 108 - 102 ( ot )', 'jamal crawford ( 31 )', 'josh smith ( 11 )', 'jamal crawford ( 7 )', 'arco arena 11472', '23 - 14'], ['38', 'january 5', 'utah', 'w 110 - 87 ( ot )', 'joe johnson ( 28 )', 'al horford ( 8 )', 'mike bibby ( 8 )', 'energysolutions arena 19911', '24 - 14'], ['39', 'january 8', 'indiana', 'w 108 - 93 ( ot )', 'josh smith ( 27 )', 'al horford , josh smith ( 10 )', 'al horford , joe johnson , josh smith ( 6 )', 'philips arena 13547', '25 - 14'], ['40', 'january 12', 'toronto', 'w 104 - 101 ( ot )', 'jamal crawford ( 36 )', 'al horford ( 13 )', 'mike bibby , josh smith ( 4 )', 'air canada centre 14186', '26 - 14'], ['41', 'january 15', 'houston', 'l 106 - 112 ( ot )', 'joe johnson ( 30 )', 'josh smith ( 12 )', 'al horford ( 8 )', 'philips arena 13420', '26 - 15'], ['42', 'january 17', 'sacramento', 'w 100 - 98 ( ot )', 'joe johnson ( 36 )', 'josh smith ( 10 )', 'jamal crawford ( 7 )', 'philips arena 14820', '27 - 15'], ['43', 'january 18', 'miami', 'w 93 - 89 ( ot )', 'jamal crawford , joe johnson ( 19 )', 'josh smith ( 12 )', 'joe johnson ( 10 )', 'american airlines arena 19600', '28 - 15'], ['44', 'january 21', 'new orleans', 'l 59 - 100 ( ot )', 'jamal crawford ( 14 )', 'josh smith ( 8 )', 'joe johnson , jeff teague ( 3 )', 'philips arena 14875', '28 - 16'], ['45', 'january 22', 'charlotte', 'w 103 - 87 ( ot )', 'joe johnson ( 32 )', 'mike bibby , zaza pachulia ( 8 )', 'joe johnson ( 5 )', 'time warner cable arena 17286', '29 - 16'], ['46', 'january 26', 'milwaukee', 'l 90 - 98 ( ot )', 'jamal crawford ( 20 )', 'josh smith ( 11 )', 'al horford ( 5 )', 'bradley center 13274', '29 - 17'], ['47', 'january 28', 'new york', 'w 111 - 102 ( ot )', 'joe johnson ( 34 )', 'al horford ( 14 )', 'joe johnson ( 7 )', 'philips arena 19069', '30 - 17']]

2010 big east conference football season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28298589-4.html.csv

majority

the majority of the game had an attendance of over 50,000 people .

{'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '50,000', 'subset': None}

{'func': 'most_greater', 'args': ['all_rows', 'attendance', '50,000'], 'result': True, 'ind': 0, 'tointer': 'for the attendance records of all rows , most of them are greater than 50,000 .', 'tostr': 'most_greater { all_rows ; attendance ; 50,000 } = true'}

most_greater { all_rows ; attendance ; 50,000 } = true

for the attendance records of all rows , most of them are greater than 50,000 .

1

1

{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'attendance_3': 3, '50,000_4': 4}

{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'attendance_3': 'attendance', '50,000_4': '50,000'}

{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'attendance_3': [0], '50,000_4': [0]}

['date', 'time', 'visiting team', 'home team', 'site', 'broadcast', 'result', 'attendance']

[['september 10', '7:00 pm', 'no 23 west virginia', 'marshall', 'joan c edwards stadium huntington , wv', 'espn2', 'w 24 - 21 ot', '41382'], ['september 11', '12:00 pm', 'south florida', 'no 8 florida', 'ben hill griffin stadium gainesville , fl', 'big east network', 'l 14 - 38', '90612'], ['september 11', '12:00 pm', 'indiana state', 'cincinnati', 'nippert stadium cincinnati , oh', 'fsohio', 'w 40 - 7', '30807'], ['september 11', '12:00 pm', 'texas southern', 'connecticut', 'rentschler field east hartford , ct', 'big east network', 'w 62 - 3', '37359'], ['september 11', '1:00 pm', 'new hampshire', 'pittsburgh', 'heinz field pittsburgh , pa', 'espn3.com', 'w 38 - 16', '50120'], ['september 11', '3:30 pm', 'eastern kentucky', 'louisville', "papa john 's cardinal stadium louisville , ky", 'big east network', 'w 23 - 13', '51427'], ['september 11', '7:00 pm', 'syracuse', 'washington', 'husky stadium seattle , wa', 'fsn northwest', 'l 20 - 41', '62418']]

jimmy spencer

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1458412-1.html.csv

aggregation

jimmy spencer had a total of 2 wins between 1989 and 2004 .

{'scope': 'all', 'col': '3', 'type': 'sum', 'result': '2', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'wins'], 'result': '2', 'ind': 0, 'tostr': 'sum { all_rows ; wins }'}, '2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; wins } ; 2 } = true', 'tointer': 'the sum of the wins record of all rows is 2 .'}

round_eq { sum { all_rows ; wins } ; 2 } = true

the sum of the wins record of all rows is 2 .

2

2

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

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'wins_4': 'wins', '2_5': '2'}

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

['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )']

[['1989', '17', '0', '0', '3', '0', '26.5', '23.6', '121065', '34th', '88 baker - schiff racing'], ['1990', '26', '0', '0', '2', '0', '26.3', '21.7', '219775', '24th', '57 osterlund motorsports'], ['1991', '29', '0', '1', '6', '0', '24.5', '23.0', '283620', '25th', '98 travis carter enterprises'], ['1993', '30', '0', '5', '10', '0', '19.8', '16.5', '686026', '12th', '12 bobby allison motorsports'], ['1994', '29', '2', '3', '4', '1', '21.5', '25.1', '479235', '29th', '27 junior johnson & associates'], ['1995', '29', '0', '0', '4', '0', '27.3', '22.3', '507210', '26th', '23 travis carter motorsports'], ['1996', '31', '0', '2', '9', '0', '26.0', '17.7', '1090876', '15th', '23 travis carter motorsports'], ['1997', '32', '0', '1', '4', '0', '20.9', '22.9', '1073779', '20th', '23 travis carter motorsports'], ['1998', '31', '0', '3', '8', '0', '25.2', '18.2', '1741012', '14th', '23 haas - carter motorsports'], ['1999', '34', '0', '2', '4', '0', '26.4', '22.4', '1752299', '20th', '23 haas - carter motorsports'], ['2000', '34', '0', '2', '5', '0', '24.0', '23.7', '1936762', '22nd', '26 haas - carter motorsports'], ['2001', '36', '0', '3', '8', '2', '19.7', '20.2', '2669638', '16th', '26 haas - carter motorsports'], ['2002', '34', '0', '2', '6', '0', '21.5', '23.5', '2136792', '27th', '41 chip ganassi racing'], ['2003', '35', '0', '1', '4', '0', '24.0', '24.6', '2565803', '29th', '7 ultra motorsports'], ['2004', '26', '0', '0', '0', '0', '35.1', '29.5', '1985121', '35th', '7 ultra motorsports 4 morgan - mcclure motorsports']]

luke donald

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1590652-4.html.csv

unique

the barclays scottish open tournament was the only tournament luke donald won by a margin of 4 strokes .

{'scope': 'all', 'row': '6', 'col': '6', 'col_other': '3', 'criterion': 'equal', 'value': '4 strokes', 'subset': None}

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

and { only { filter_eq { all_rows ; margin of victory ; 4 strokes } } ; eq { hop { filter_eq { all_rows ; margin of victory ; 4 strokes } ; tournament } ; barclays scottish open } } = true

select the rows whose margin of victory record fuzzily matches to 4 strokes . there is only one such row in the table . the tournament record of this unqiue row is barclays scottish open .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'margin of victory_7': 7, '4 strokes_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'barclays scottish open_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'margin of victory_7': 'margin of victory', '4 strokes_8': '4 strokes', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'barclays scottish open_10': 'barclays scottish open'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'margin of victory_7': [0], '4 strokes_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'barclays scottish open_10': [3]}

['no', 'date', 'tournament', 'winning score', 'to par', 'margin of victory', 'runner ( s ) - up']

[['1', '1 aug 2004', 'scandinavian masters by carlsberg', '69 + 65 + 69 + 69 = 272', '16', '5 strokes', 'peter hanson'], ['2', '5 sep 2004', 'omega european masters', '67 + 67 + 65 + 66 = 265', '19', '5 strokes', 'miguel ángel jiménez'], ['3', '30 may 2010', 'madrid masters', '65 + 67 + 68 + 67 = 267', '21', '1 stroke', 'rhys davies'], ['4', '27 feb 2011', 'wgc - accenture match play championship', '3 and 2', '3 and 2', '3 and 2', 'martin kaymer'], ['5', '29 may 2011', 'bmw pga championship', '64 + 72 + 72 + 70 = 278', '6', 'playoff', 'lee westwood'], ['6', '10 jul 2011', 'barclays scottish open', '67 + 67 + 63 = 197', '19', '4 strokes', 'fredrik andersson hed']]

ramires

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13211909-2.html.csv

majority

all of the times ramires was on the national team , the team was brazil .

{'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'brazil', 'subset': None}

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

all_eq { all_rows ; national team ; brazil } = true

for the national team records of all rows , all of them fuzzily match to brazil .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'national team_3': 3, 'brazil_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'national team_3': 'national team', 'brazil_4': 'brazil'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'national team_3': [0], 'brazil_4': [0]}

['national team', 'club', 'season', 'apps', 'goals']

[['brazil', 'cruzeiro', '2009', '7', '0'], ['brazil', 'benfica', '2009 - 10', '9', '2'], ['brazil', 'chelsea', '2010 - 11', '10', '0'], ['brazil', 'chelsea', '2011 - 12', '1', '0'], ['brazil', 'chelsea', '2012 - 13', '6', '1'], ['total', 'total', 'total', '33', '3']]

sheffield and hallamshire association cup

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14909105-1.html.csv

unique

kiveton park was the only player to win 5-0 in the sheffield and hallamshire association cup from 2002-2013 .

{'scope': 'all', 'row': '4', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': '5-0', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', '5-0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to 5-0 .', 'tostr': 'filter_eq { all_rows ; result ; 5-0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; 5-0 } }', 'tointer': 'select the rows whose result record fuzzily matches to 5-0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', '5-0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to 5-0 .', 'tostr': 'filter_eq { all_rows ; result ; 5-0 }'}, 'winner'], 'result': 'kiveton park', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; 5-0 } ; winner }'}, 'kiveton park'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; 5-0 } ; winner } ; kiveton park }', 'tointer': 'the winner record of this unqiue row is kiveton park .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; 5-0 } } ; eq { hop { filter_eq { all_rows ; result ; 5-0 } ; winner } ; kiveton park } } = true', 'tointer': 'select the rows whose result record fuzzily matches to 5-0 . there is only one such row in the table . the winner record of this unqiue row is kiveton park .'}

and { only { filter_eq { all_rows ; result ; 5-0 } } ; eq { hop { filter_eq { all_rows ; result ; 5-0 } ; winner } ; kiveton park } } = true

select the rows whose result record fuzzily matches to 5-0 . there is only one such row in the table . the winner record of this unqiue row is kiveton park .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, '5-0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'winner_9': 9, 'kiveton park_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', '5-0_8': '5-0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'winner_9': 'winner', 'kiveton park_10': 'kiveton park'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], '5-0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'winner_9': [2], 'kiveton park_10': [3]}

['season', 'winner', 'result', 'runner - up', 'final venue']

[['2002 - 03', 'elm tree', '1 - 0', 'stocksbridge park steels reserves', 'belle vue'], ['2003 - 04', 'hsbc', '3 - 2', 'athersley recreation', 'belle vue'], ['2004 - 05', 'kiveton park', '2 - 2', 'athersley recreation', 'sandy lane'], ['2005 - 06', 'kiveton park', '5 - 0', 'sheffield lane top', 'belle vue'], ['2006 - 07', 'stocksbridge park steels reserves', '3 - 1', 'hemsworth miners welfare', 'millmoor'], ['2007 - 08', 'athersley recreation', '1 - 0', 'hollinsend amateurs', 'oakwell'], ['2008 - 09', 'hall green united', '2 - 1', 'kirkburton', 'keepmoat stadium ( pitch 2 )'], ['2009 - 10', 'sheffield reserves', '2 - 1', 'dearne colliery miners welfare', 'inkersall road'], ['2010 - 11', 'stocksbridge park steels reserves', '3 - 0', 'kirkburton', 'green lane'], ['2012 - 13', 'swinton athletic', '3 - 0', 'kirkburton', 'sandy lane']]

1980 cleveland browns season

https://en.wikipedia.org/wiki/1980_Cleveland_Browns_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10651215-1.html.csv

aggregation

in the 1980 cleaveland browns season , there was a total of 308 points from the university of texas at arlington .

{'scope': 'subset', 'col': '2', 'type': 'sum', 'result': '308', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'university of texas at arlington'}}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'university of texas at arlington'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; school / club team ; university of texas at arlington }', 'tointer': 'select the rows whose school / club team record fuzzily matches to university of texas at arlington .'}, 'overall'], 'result': '308', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; school / club team ; university of texas at arlington } ; overall }'}, '308'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; school / club team ; university of texas at arlington } ; overall } ; 308 } = true', 'tointer': 'select the rows whose school / club team record fuzzily matches to university of texas at arlington . the sum of the overall record of these rows is 308 .'}

round_eq { sum { filter_eq { all_rows ; school / club team ; university of texas at arlington } ; overall } ; 308 } = true

select the rows whose school / club team record fuzzily matches to university of texas at arlington . the sum of the overall record of these rows is 308 .

3

3

{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'school / club team_5': 5, 'university of texas at arlington_6': 6, 'overall_7': 7, '308_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'school / club team_5': 'school / club team', 'university of texas at arlington_6': 'university of texas at arlington', 'overall_7': 'overall', '308_8': '308'}

{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'school / club team_5': [0], 'university of texas at arlington_6': [0], 'overall_7': [1], '308_8': [2]}

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

[['1', '27', 'charles white', 'running back', 'usc'], ['2', '54', 'cleveland crosby', 'defensive end', 'wisconsin'], ['3', '72', 'cliff odom', 'linebacker', 'university of texas at arlington'], ['4', '99', 'ron crews', 'nose tackle', 'unlv'], ['4', '109', 'paul mcdonald', 'quarterback', 'usc'], ['5', '116', 'elvis franks', 'defensive end', 'morgan state'], ['8', '209', 'jeff copeland', 'linebacker', 'texas tech'], ['9', '236', 'roy de walt', 'running back', 'university of texas at arlington'], ['10', '263', 'kevin fidel', 'center', 'san diego state'], ['11', '294', 'roland sales', 'running back', 'arkansas'], ['12', '321', 'marcus jackson', 'defensive end', 'purdue']]

hawthorne ( season 2 )

https://en.wikipedia.org/wiki/Hawthorne_%28season_2%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30030477-1.html.csv

unique

the episode of hawthorne ( season 2 ) titled " road narrows " is the only one of the season written by sang kyu kim .

{'scope': 'all', 'row': '3', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'sang kyu kim', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'sang kyu kim'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to sang kyu kim .', 'tostr': 'filter_eq { all_rows ; written by ; sang kyu kim }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; written by ; sang kyu kim } }', 'tointer': 'select the rows whose written by record fuzzily matches to sang kyu kim . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'sang kyu kim'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to sang kyu kim .', 'tostr': 'filter_eq { all_rows ; written by ; sang kyu kim }'}, 'title'], 'result': 'road narrows', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; written by ; sang kyu kim } ; title }'}, 'road narrows'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; written by ; sang kyu kim } ; title } ; road narrows }', 'tointer': 'the title record of this unqiue row is road narrows .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; written by ; sang kyu kim } } ; eq { hop { filter_eq { all_rows ; written by ; sang kyu kim } ; title } ; road narrows } } = true', 'tointer': 'select the rows whose written by record fuzzily matches to sang kyu kim . there is only one such row in the table . the title record of this unqiue row is road narrows .'}

and { only { filter_eq { all_rows ; written by ; sang kyu kim } } ; eq { hop { filter_eq { all_rows ; written by ; sang kyu kim } ; title } ; road narrows } } = true

select the rows whose written by record fuzzily matches to sang kyu kim . there is only one such row in the table . the title record of this unqiue row is road narrows .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'written by_7': 7, 'sang kyu kim_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'road narrows_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'written by_7': 'written by', 'sang kyu kim_8': 'sang kyu kim', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'road narrows_10': 'road narrows'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'written by_7': [0], 'sang kyu kim_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'road narrows_10': [3]}

['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'viewers ( million )']

[['11', '1', 'no excuses', 'jeff bleckner', 'glen mazzara', 'june 22 , 2010', '3.42'], ['12', '2', 'the starting line', 'ed bianchi', 'john masius & erica shelton', 'june 29 , 2010', '2.95'], ['13', '3', 'road narrows', 'ed bianchi', 'sang kyu kim', 'july 6 , 2010', '2.73'], ['14', '4', 'afterglow', 'jeff bleckner', 'darin goldberg & shelley meals', 'july 13 , 2010', '2.64'], ['15', '5', 'the match', 'mike robe', 'adam e fierro & glen mazzara', 'july 20 , 2010', '2.86'], ['16', '6', 'final curtain', 'tricia brock', 'sarah thorp', 'july 27 , 2010', '2.63'], ['17', '7', 'hidden truths', 'jeff bleckner', 'darin goldberg & shelley meals', 'august 3 , 2010', '3.12'], ['18', '8', 'a mother knows', 'tricia brock', 'erica shelton', 'august 10 , 2010', '3.24']]

united states house of representatives elections in connecticut , 2008

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections_in_Connecticut%2C_2008

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18722787-1.html.csv

majority

for the united states house of representatives election in 2008 in connecticut , all of the incumbents had a 2008 status of re-election .

{'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 're-election', 'subset': None}

{'func': 'all_str_eq', 'args': ['all_rows', '2008 status', 're-election'], 'result': True, 'ind': 0, 'tointer': 'for the 2008 status records of all rows , all of them fuzzily match to re-election .', 'tostr': 'all_eq { all_rows ; 2008 status ; re-election } = true'}

all_eq { all_rows ; 2008 status ; re-election } = true

for the 2008 status records of all rows , all of them fuzzily match to re-election .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, '2008 status_3': 3, 're-election_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', '2008 status_3': '2008 status', 're-election_4': 're-election'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], '2008 status_3': [0], 're-election_4': [0]}

['district', 'incumbent', '2008 status', 'democratic', 'republican', 'green']

[['1', 'john b larson', 're - election', 'john b larson', 'joe visconti', 'stephen e d fournier'], ['2', 'joe courtney', 're - election', 'joe courtney', 'sean sullivan', 'g scott deshefy'], ['3', 'rosa delauro', 're - election', 'rosa delauro', 'bo itshaky', 'ralph ferrucci'], ['4', 'christopher shays', 're - election', 'jim himes', 'christopher shays', 'richard duffee'], ['5', 'chris murphy', 're - election', 'chris murphy', 'david cappiello', 'harold burbank']]

rowing at the 2008 summer olympics - men 's single sculls

https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_single_sculls

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662643-6.html.csv

superlative

in the 2008 olympics men 's single sculls rowing competition , alan campbell ranked the highest .

{'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'rank'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; rank }'}, 'athlete'], 'result': 'alan campbell', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; rank } ; athlete }'}, 'alan campbell'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; rank } ; athlete } ; alan campbell } = true', 'tointer': 'select the row whose rank record of all rows is minimum . the athlete record of this row is alan campbell .'}

eq { hop { argmin { all_rows ; rank } ; athlete } ; alan campbell } = true

select the row whose rank record of all rows is minimum . the athlete record of this row is alan campbell .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'rank_5': 5, 'athlete_6': 6, 'alan campbell_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'rank_5': 'rank', 'athlete_6': 'athlete', 'alan campbell_7': 'alan campbell'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'rank_5': [0], 'athlete_6': [1], 'alan campbell_7': [2]}

['rank', 'athlete', 'country', 'time', 'notes']

[['1', 'alan campbell', 'great britain', '7:14.98', 'q'], ['2', 'peter hardcastle', 'australia', '7:17.74', 'q'], ['3', 'patrick loliger', 'mexico', '7:22.55', 'q'], ['4', 'ken jurkowski', 'united states', '7:25.13', 'q'], ['5', 'ruslan naurzaliev', 'uzbekistan', '7:58.43', 'se / f']]

2008 german motorcycle grand prix

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16878651-1.html.csv

unique

only one motorcycle in the 2008 german motorcycle grand prix was manufactured by kawasaki .

{'scope': 'all', 'row': '10', 'col': '2', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'kawasaki', 'subset': None}

{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manufacturer', 'kawasaki'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manufacturer record fuzzily matches to kawasaki .', 'tostr': 'filter_eq { all_rows ; manufacturer ; kawasaki }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; manufacturer ; kawasaki } } = true', 'tointer': 'select the rows whose manufacturer record fuzzily matches to kawasaki . there is only one such row in the table .'}

only { filter_eq { all_rows ; manufacturer ; kawasaki } } = true

select the rows whose manufacturer record fuzzily matches to kawasaki . there is only one such row in the table .

2

2

{'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'manufacturer_4': 4, 'kawasaki_5': 5}

{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'manufacturer_4': 'manufacturer', 'kawasaki_5': 'kawasaki'}

{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'manufacturer_4': [0], 'kawasaki_5': [0]}

['rider', 'manufacturer', 'laps', 'time', 'grid']

[['casey stoner', 'ducati', '30', '47:30.057', '1'], ['valentino rossi', 'yamaha', '30', '+ 3.708', '7'], ['chris vermeulen', 'suzuki', '30', '+ 14.002', '14'], ['alex de angelis', 'honda', '30', '+ 14.124', '10'], ['andrea dovizioso', 'honda', '30', '+ 42.022', '4'], ['sylvain guintoli', 'ducati', '30', '+ 46.648', '15'], ['loris capirossi', 'suzuki', '30', '+ 1:04.483', '13'], ['randy de puniet', 'honda', '30', '+ 1:04.588', '6'], ['shinya nakano', 'honda', '30', '+ 1:16.773', '9'], ['anthony west', 'kawasaki', '30', '+ 1:29.275', '17'], ['james toseland', 'yamaha', '29', '+ 1 lap', '11'], ['toni elias', 'ducati', '29', '+ 1 lap', '12'], ['nicky hayden', 'honda', '28', '+ 2 laps', '8'], ['colin edwards', 'yamaha', '20', 'accident', '3'], ['marco melandri', 'ducati', '9', 'accident', '16'], ['dani pedrosa', 'honda', '5', 'accident', '2'], ['jorge lorenzo', 'yamaha', '2', 'accident', '5']]

list of australian test bowlers who have taken over 200 test wickets

https://en.wikipedia.org/wiki/List_of_Australian_Test_bowlers_who_have_taken_over_200_Test_wickets

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18914438-1.html.csv

majority

most of the australian test bowlers who have taken over 200 test wickets had under 100 matches .

{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '100', 'subset': None}

{'func': 'most_less', 'args': ['all_rows', 'matches', '100'], 'result': True, 'ind': 0, 'tointer': 'for the matches records of all rows , most of them are less than 100 .', 'tostr': 'most_less { all_rows ; matches ; 100 } = true'}

most_less { all_rows ; matches ; 100 } = true

for the matches records of all rows , most of them are less than 100 .

1

1

{'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'matches_3': 3, '100_4': 4}

{'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'matches_3': 'matches', '100_4': '100'}

{'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'matches_3': [0], '100_4': [0]}

['name', 'career', 'matches', 'overs', 'maidens', 'runs', 'wickets', 'average', 'best']

[['shane warne', '1992 - 2007', '145', '6784.1', '1762', '17995', '708', '25.42', '8 / 71'], ['glenn mcgrath', '1993 - 2007', '124', '4874.4', '1470', '12186', '563', '21.64', '8 / 24'], ['dennis lillee', '1971 - 1984', '70', '2834.1', '652', '8493', '355', '23.92', '7 / 83'], ['brett lee', '1999 - 2010', '76', '2755.1', '547', '9555', '310', '30.82', '5 / 30'], ['craig mcdermott', '1984 - 1996', '71', '2764.2', '583', '8332', '291', '28.63', '8 / 97'], ['jason gillespie', '1996 - 2006', '71', '2372.2', '630', '6770', '259', '26.14', '7 / 37'], ['richie benaud', '1952 - 1964', '63', '2727.2', '805', '6704', '248', '27.03', '7 / 72'], ['graham mckenzie', '1961 - 1971', '60', '2629.5', '547', '7328', '246', '29.79', '8 / 71'], ['ray lindwall', '1946 - 1960', '61', '1970.2', '419', '5251', '228', '23.03', '7 / 38'], ['clarrie grimmett', '1925 - 1936', '37', '2408.3', '736', '5231', '216', '24.22', '7 / 40'], ['merv hughes', '1985 - 1994', '53', '2047.3', '499', '6017', '212', '28.38', '8 / 87'], ['stuart macgill', '1998 - 2008', '44', '1872.5', '365', '6037', '208', '29.02', '8 / 108'], ['mitchell johnson', '2007 -', '50', '1870', '331', '6281', '205', '30.64', '8 / 61'], ['jeff thomson', '1972 - 1985', '51', '1589.3', '300', '5601', '200', '29.01', '6 / 46']]

mountain peaks of the rocky mountains

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12069382-4.html.csv

ordinal

west spanish peak is the second least far north of any of these mountains .

{'row': '3', 'col': '5', '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', 'location', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; location ; 2 }'}, 'mountain peak'], 'result': 'west spanish peak', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; location ; 2 } ; mountain peak }'}, 'west spanish peak'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; location ; 2 } ; mountain peak } ; west spanish peak } = true', 'tointer': 'select the row whose location record of all rows is 2nd minimum . the mountain peak record of this row is west spanish peak .'}

eq { hop { nth_argmin { all_rows ; location ; 2 } ; mountain peak } ; west spanish peak } = true

select the row whose location record of all rows is 2nd minimum . the mountain peak record of this row is west spanish peak .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'location_5': 5, '2_6': 6, 'mountain peak_7': 7, 'west spanish peak_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', 'location_5': 'location', '2_6': '2', 'mountain peak_7': 'mountain peak', 'west spanish peak_8': 'west spanish peak'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'location_5': [0], '2_6': [0], 'mountain peak_7': [1], 'west spanish peak_8': [2]}

['rank', 'mountain peak', 'region', 'mountain range', 'location']

[['1', 'fishers peak', 'colorado', 'raton mesa', '37.0982 degreen 104.4628 degreew'], ['2', 'east spanish peak', 'colorado', 'spanish peaks', '37.3934 degreen 104.9201 degreew'], ['3', 'west spanish peak', 'colorado', 'spanish peaks', '37.3756 degreen 104.9934 degreew'], ['4', 'pikes peak', 'colorado', 'front range', '38.8405 degreen 105.0442 degreew'], ['5', 'blanca peak', 'colorado', 'sangre de cristo mountains', '37.5775 degreen 105.4856 degreew'], ['6', 'mount harvard', 'colorado', 'sawatch range', '38.9244 degreen 106.3207 degreew'], ['7', 'mount elbert', 'colorado', 'sawatch range', '39.1178 degreen 106.4454 degreew']]

2003 canadian grand prix

https://en.wikipedia.org/wiki/2003_Canadian_Grand_Prix

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1123529-2.html.csv

aggregation

ferrari built cars went a total of 140 laps in the 2003 canadian gran prix .

{'scope': 'subset', 'col': '3', 'type': 'sum', 'result': '140', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'ferrari'}}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'constructor', 'ferrari'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; constructor ; ferrari }', 'tointer': 'select the rows whose constructor record fuzzily matches to ferrari .'}, 'laps'], 'result': '140', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; constructor ; ferrari } ; laps }'}, '140'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; constructor ; ferrari } ; laps } ; 140 } = true', 'tointer': 'select the rows whose constructor record fuzzily matches to ferrari . the sum of the laps record of these rows is 140 .'}

round_eq { sum { filter_eq { all_rows ; constructor ; ferrari } ; laps } ; 140 } = true

select the rows whose constructor record fuzzily matches to ferrari . the sum of the laps record of these rows is 140 .

3

3

{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'constructor_5': 5, 'ferrari_6': 6, 'laps_7': 7, '140_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'constructor_5': 'constructor', 'ferrari_6': 'ferrari', 'laps_7': 'laps', '140_8': '140'}

{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'constructor_5': [0], 'ferrari_6': [0], 'laps_7': [1], '140_8': [2]}

['driver', 'constructor', 'laps', 'time / retired', 'grid']

[['michael schumacher', 'ferrari', '70', '1:31:13.591', '3'], ['ralf schumacher', 'williams - bmw', '70', '+ 0.784', '1'], ['juan pablo montoya', 'williams - bmw', '70', '+ 1.355', '2'], ['fernando alonso', 'renault', '70', '+ 4.481', '4'], ['rubens barrichello', 'ferrari', '70', '+ 1:04.261', '5'], ['kimi räikkönen', 'mclaren - mercedes', '70', '+ 1:10.502', '20'], ['mark webber', 'jaguar - cosworth', '69', '+ 1 lap', '6'], ['olivier panis', 'toyota', '69', '+ 1 lap', '7'], ['jos verstappen', 'minardi - cosworth', '68', '+ 2 laps', '15'], ['antônio pizzonia', 'jaguar - cosworth', '64', 'brakes', '13'], ['cristiano da matta', 'toyota', '64', 'suspension', '9'], ['justin wilson', 'minardi - cosworth', '60', 'gearbox', '18'], ['jenson button', 'bar - honda', '51', 'gearbox', '17'], ['david coulthard', 'mclaren - mercedes', '47', 'gearbox', '11'], ['nick heidfeld', 'sauber - petronas', '47', 'engine', '12'], ['jarno trulli', 'renault', '22', 'collision damage', '8'], ['giancarlo fisichella', 'jordan - ford', '20', 'gearbox', '16'], ['ralph firman', 'jordan - ford', '20', 'engine', '19'], ['jacques villeneuve', 'bar - honda', '14', 'brakes', '14'], ['heinz - harald frentzen', 'sauber - petronas', '6', 'electronics', '10']]

list of memorial cup champions

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17751942-2.html.csv

count

the memorial cup championship went into overtime on two occasions .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': '( ot )', 'result': '2', 'col': '2', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', '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': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; score ; ( ot ) } }', 'tointer': 'select the rows whose score record fuzzily matches to ( ot ) . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; score ; ( ot ) } } ; 2 } = true', 'tointer': 'select the rows whose score record fuzzily matches to ( ot ) . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; score ; ( ot ) } } ; 2 } = true

select the rows whose score record fuzzily matches to ( ot ) . 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, 'score_5': 5, '(ot)_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', 'score_5': 'score', '(ot)_6': '( ot )', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'score_5': [0], '(ot)_6': [0], '2_7': [2]}

['champion', 'score', 'runner - up', 'additional participants', 'host location ( s )']

[['cornwall royals ( qmjhl )', '2 - 1', 'peterborough petes ( oha )', 'edmonton oil kings ( wchl )', 'ottawa'], ['toronto marlboros ( oha )', '9 - 1', 'quebec remparts ( qmjhl )', 'medicine hat tigers ( wchl )', 'montreal'], ['regina pats ( wchl )', '7 - 4', 'quebec remparts ( qmjhl )', 'st catharines black hawks ( oha )', 'calgary'], ['toronto marlboros ( oha )', '7 - 3', 'new westminster bruins ( wchl )', 'sherbrooke castors ( qmjhl )', 'kitchener'], ['hamilton fincups ( oha )', '5 - 2', 'new westminster bruins ( wchl )', 'quebec remparts ( qmjhl )', 'montreal'], ['new westminster bruins ( wchl )', '6 - 5', "ottawa 67 's ( oha )", 'sherbrooke castors ( qmjhl )', 'vancouver'], ['new westminster bruins ( whl )', '7 - 4', 'peterborough petes ( oha )', 'trois - rivières draveurs ( qmjhl )', 'sudbury and sault ste marie'], ['peterborough petes ( oha )', '2 - 1 ( ot )', 'brandon wheat kings ( whl )', 'trois - rivières draveurs ( qmjhl )', 'sherbrooke , trois - rivières and verdun'], ['cornwall royals ( qmjhl )', '3 - 2 ( ot )', 'peterborough petes ( oha )', 'regina pats ( whl )', 'brandon and regina'], ['cornwall royals ( qmjhl )', '5 - 2', 'kitchener rangers ( ohl )', 'victoria cougars ( whl )', 'windsor'], ['kitchener rangers ( ohl )', '7 - 4', 'sherbrooke castors ( qmjhl )', 'portland winter hawks ( whl )', 'hull']]

césar eduardo gonzález

https://en.wikipedia.org/wiki/C%C3%A9sar_Eduardo_Gonz%C3%A1lez

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12690988-1.html.csv

comparative

the total goals scored in the 2014 world cup qualifier was higher than the total goals at the 2011 copa america .

{'row_1': '5', 'row_2': '3', 'col': '1', 'col_other': '5', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '2014 world cup qualifier'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to 2014 world cup qualifier .', 'tostr': 'filter_eq { all_rows ; competition ; 2014 world cup qualifier }'}, 'goal'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; competition ; 2014 world cup qualifier } ; goal }', 'tointer': 'select the rows whose competition record fuzzily matches to 2014 world cup qualifier . take the goal record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '2011 copa américa'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose competition record fuzzily matches to 2011 copa américa .', 'tostr': 'filter_eq { all_rows ; competition ; 2011 copa américa }'}, 'goal'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; competition ; 2011 copa américa } ; goal }', 'tointer': 'select the rows whose competition record fuzzily matches to 2011 copa américa . take the goal record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; competition ; 2014 world cup qualifier } ; goal } ; hop { filter_eq { all_rows ; competition ; 2011 copa américa } ; goal } } = true', 'tointer': 'select the rows whose competition record fuzzily matches to 2014 world cup qualifier . take the goal record of this row . select the rows whose competition record fuzzily matches to 2011 copa américa . take the goal record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; competition ; 2014 world cup qualifier } ; goal } ; hop { filter_eq { all_rows ; competition ; 2011 copa américa } ; goal } } = true

select the rows whose competition record fuzzily matches to 2014 world cup qualifier . take the goal record of this row . select the rows whose competition record fuzzily matches to 2011 copa américa . take the goal 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, 'competition_7': 7, '2014 world cup qualifier_8': 8, 'goal_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'competition_11': 11, '2011 copa américa_12': 12, 'goal_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', 'competition_7': 'competition', '2014 world cup qualifier_8': '2014 world cup qualifier', 'goal_9': 'goal', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'competition_11': 'competition', '2011 copa américa_12': '2011 copa américa', 'goal_13': 'goal'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'competition_7': [0], '2014 world cup qualifier_8': [0], 'goal_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'competition_11': [1], '2011 copa américa_12': [1], 'goal_13': [3]}

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

[['1', '24 march 2007', '3 - 1', '3 - 1', 'friendly'], ['2', '3 march 2010', '1 - 2', '1 - 2', 'friendly'], ['3', '9 july 2011', '1 - 0', '1 - 0', '2011 copa américa'], ['4', '22 may 2013', '1 - 1', '2 - 1', 'friendly'], ['5', '10 september 2013', '2 - 1', '3 - 2', '2014 world cup qualifier']]

1975 england rugby union tour of australia

https://en.wikipedia.org/wiki/1975_England_rugby_union_tour_of_Australia

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17004899-1.html.csv

superlative

australia scored the highest number of points against england in the 1975 england rugby union tour of australia .

{'scope': 'all', 'col_superlative': '2', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'against'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; against }'}, 'opposing team'], 'result': 'australia', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; against } ; opposing team }'}, 'australia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; against } ; opposing team } ; australia } = true', 'tointer': 'select the row whose against record of all rows is maximum . the opposing team record of this row is australia .'}

eq { hop { argmax { all_rows ; against } ; opposing team } ; australia } = true

select the row whose against record of all rows is maximum . the opposing team record of this row is australia .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'against_5': 5, 'opposing team_6': 6, 'australia_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'against_5': 'against', 'opposing team_6': 'opposing team', 'australia_7': 'australia'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'against_5': [0], 'opposing team_6': [1], 'australia_7': [2]}

['opposing team', 'against', 'date', 'venue', 'status']

[['western australia', '12', '10 / 05 / 1975', 'perry lakes stadium , perth', 'tour match'], ['sydney', '14', '13 / 05 / 1975', 'sydney cricket ground , sydney', 'tour match'], ['new south wales', '24', '17 / 05 / 1975', 'sydney sports ground , sydney', 'tour match'], ['new south wales country xv', '14', '20 / 05 / 1975', 'goulburn', 'tour match'], ['australia', '16', '24 / 05 / 1975', 'sydney cricket ground , sydney', 'first test'], ['queensland', '3', '27 / 05 / 1975', 'ballymore , brisbane', 'tour match'], ['australia', '30', '31 / 05 / 1975', 'ballymore , brisbane', 'second test'], ['queensland country', '6', '03 / 06 / 1975', 'townsville sports reserve , townsville', 'tour match']]

1976 oakland raiders season

https://en.wikipedia.org/wiki/1976_Oakland_Raiders_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12293930-1.html.csv

count

a total of four players drafted by the oakland raiders played the hb position .

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

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

eq { count { filter_eq { all_rows ; position ; hb } } ; 4 } = true

select the rows whose position record fuzzily matches to hb . 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, 'position_5': 5, 'hb_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', 'position_5': 'position', 'hb_6': 'hb', '4_7': '4'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'hb_6': [0], '4_7': [2]}

['round', 'overall', 'player', 'position', 'college']

[['2', '34', 'charles philyaw', 'de', 'texas southern'], ['2', '50', 'jeb blount', 'qb', 'tulsa'], ['3', '84', 'rik bonness', 'lb', 'nebraska'], ['4', '110', 'herb mcmath', 'de', 'morningside'], ['5', '146', 'fred steinfort', 'k', 'boston college'], ['7', '204', 'clarence chapman', 'wr', 'eastern michigan'], ['8', '220', 'jerome dove', 'db', 'colorado state'], ['8', '231', 'terry kunz', 'hb', 'colorado'], ['10', '286', 'dwight lewis', 'db', 'purdue'], ['11', '313', 'rich jennings', 'hb', 'maryland'], ['12', '343', 'cedric brown', 's', 'kent state'], ['13', '367', 'craig crnick', 'de', 'idaho'], ['13', '370', 'mark young', 'g', 'washington state'], ['14', '397', 'calvin young', 'hb', 'fresno state'], ['15', '427', 'carl hargrave', 'db', 'upper iowa'], ['16', '454', 'doug hogan', 'db', 'southern california'], ['17', '478', 'buddy tate', 'db', 'tulsa'], ['17', '481', 'nate beasley', 'hb', 'delaware']]

list of vancouver canucks draft picks

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11636955-17.html.csv

unique

of the vancouver canucks draft picks , the only player who played for the london knights was jim sandlak .

{'scope': 'all', 'row': '1', 'col': '4', 'col_other': '3', 'criterion': 'fuzzily_match', 'value': 'london knights', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team ( league )', 'london knights'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team ( league ) record fuzzily matches to london knights .', 'tostr': 'filter_eq { all_rows ; team ( league ) ; london knights }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; team ( league ) ; london knights } }', 'tointer': 'select the rows whose team ( league ) record fuzzily matches to london knights . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team ( league )', 'london knights'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team ( league ) record fuzzily matches to london knights .', 'tostr': 'filter_eq { all_rows ; team ( league ) ; london knights }'}, 'player'], 'result': 'jim sandlak', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ( league ) ; london knights } ; player }'}, 'jim sandlak'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; team ( league ) ; london knights } ; player } ; jim sandlak }', 'tointer': 'the player record of this unqiue row is jim sandlak .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; team ( league ) ; london knights } } ; eq { hop { filter_eq { all_rows ; team ( league ) ; london knights } ; player } ; jim sandlak } } = true', 'tointer': 'select the rows whose team ( league ) record fuzzily matches to london knights . there is only one such row in the table . the player record of this unqiue row is jim sandlak .'}

and { only { filter_eq { all_rows ; team ( league ) ; london knights } } ; eq { hop { filter_eq { all_rows ; team ( league ) ; london knights } ; player } ; jim sandlak } } = true

select the rows whose team ( league ) record fuzzily matches to london knights . there is only one such row in the table . the player record of this unqiue row is jim sandlak .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team (league)_7': 7, 'london knights_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'jim sandlak_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team (league)_7': 'team ( league )', 'london knights_8': 'london knights', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'jim sandlak_10': 'jim sandlak'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'team (league)_7': [0], 'london knights_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'jim sandlak_10': [3]}

['rd', 'pick', 'player', 'team ( league )', 'reg gp', 'pl gp']

[['1', '4', 'jim sandlak', 'london knights ( ohl )', '509', '33'], ['2', '25', 'troy gamble', 'medicine hat tigers ( whl )', '72', '4'], ['3', '46', 'shane doyle', 'belleville bulls ( ohl )', '0', '0'], ['4', '67', 'randy siska', 'medicine hat tigers ( whl )', '0', '0'], ['5', '88', 'robert kron', 'brno zkl ( czech )', '144', '11'], ['6', '109', 'martin hrstka', 'hc dukla trenčín ( slovak )', '0', '0'], ['7', '130', 'brian mcfarlane', 'seattle breakers ( whl )', '0', '0'], ['8', '151', 'hakan ahlund', 'malmö if ( swe )', '0', '0'], ['9', '172', 'curtis hunt', 'prince albert raiders ( whl )', '0', '0'], ['10', '193', 'carl valimont', 'university of lowell ( ncaa )', '0', '0'], ['11', '214', 'igor larionov', 'hc cska moscow ( rus )', '210', '19'], ['12', '235', 'darren taylor', 'calgary wranglers ( whl )', '0', '0']]

2008 - 09 new york rangers season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17360905-6.html.csv

ordinal

the new york rangers scored the 12th most points against the boston bruins .

{'row': '12', 'col': '4', 'order': '12', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'score', '12'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; score ; 12 }'}, 'opponent'], 'result': 'boston bruins', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; score ; 12 } ; opponent }'}, 'boston bruins'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; score ; 12 } ; opponent } ; boston bruins } = true', 'tointer': 'select the row whose score record of all rows is 12th maximum . the opponent record of this row is boston bruins .'}

eq { hop { nth_argmax { all_rows ; score ; 12 } ; opponent } ; boston bruins } = true

select the row whose score record of all rows is 12th maximum . the opponent record of this row is boston bruins .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, '12_6': 6, 'opponent_7': 7, 'boston bruins_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', 'score_5': 'score', '12_6': '12', 'opponent_7': 'opponent', 'boston bruins_8': 'boston bruins'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], '12_6': [0], 'opponent_7': [1], 'boston bruins_8': [2]}

['game', 'january', 'opponent', 'score', 'decision', 'record']

[['40', '3', 'washington capitals', '2 - 1', 'valiquette', '23 - 14 - 3'], ['41', '5', 'pittsburgh penguins', '4 - 0', 'lundqvist', '24 - 14 - 3'], ['42', '7', 'montreal canadiens', '6 - 3', 'lundqvist', '24 - 15 - 3'], ['43', '9', 'buffalo sabres', '2 - 1 so', 'valiquette', '24 - 15 - 4'], ['44', '10', 'ottawa senators', '2 - 0', 'lundqvist', '25 - 15 - 4'], ['45', '13', 'new york islanders', '2 - 1', 'lundqvist', '26 - 15 - 4'], ['46', '16', 'chicago blackhawks', '3 - 2 ot', 'lundqvist', '27 - 15 - 4'], ['47', '18', 'pittsburgh penguins', '3 - 0', 'lundqvist', '27 - 16 - 4'], ['48', '20', 'anaheim ducks', '4 - 2', 'lundqvist', '28 - 16 - 4'], ['49', '27', 'carolina hurricanes', '3 - 2', 'valiquette', '29 - 16 - 4'], ['50', '28', 'pittsburgh penguins', '6 - 2', 'lundqvist', '29 - 17 - 4'], ['51', '31', 'boston bruins', '1 - 0', 'lundqvist', '29 - 18 - 4']]

queens county , new brunswick

https://en.wikipedia.org/wiki/Queens_County%2C_New_Brunswick

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-171356-2.html.csv

ordinal

chipman recorded the highest population in the queens county of new brunswick .

{'row': '1', 'col': '4', 'order': '1', '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', 'population', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; population ; 1 }'}, 'official name'], 'result': 'chipman', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; population ; 1 } ; official name }'}, 'chipman'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; population ; 1 } ; official name } ; chipman } = true', 'tointer': 'select the row whose population record of all rows is 1st maximum . the official name record of this row is chipman .'}

eq { hop { nth_argmax { all_rows ; population ; 1 } ; official name } ; chipman } = true

select the row whose population record of all rows is 1st maximum . the official name record of this row is chipman .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'population_5': 5, '1_6': 6, 'official name_7': 7, 'chipman_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', 'population_5': 'population', '1_6': '1', 'official name_7': 'official name', 'chipman_8': 'chipman'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'population_5': [0], '1_6': [0], 'official name_7': [1], 'chipman_8': [2]}

['official name', 'status', 'area km 2', 'population', 'census ranking']

[['chipman', 'parish', '482.81', '962', '2135 of 5008'], ['canning', 'parish', '173.40', '952', '2145 of 5008'], ['waterborough', 'parish', '444.87', '851', '2290 of 5008'], ['petersville', 'parish', '588.42', '723', '2520 of 5008'], ['johnston', 'parish', '359.18', '660', '2649 of 5008'], ['cambridge', 'parish', '113.97', '651', '2662 of 5008'], ['wickham', 'parish', '159.78', '426', '3211 of 5008'], ['gagetown', 'parish', '234.89', '316', '3574 of 5008'], ['hampstead', 'parish', '212.63', '294', '3665 of 5008']]

tokyo skytree

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2638104-1.html.csv

majority

all of the channels broadcast by tokyo skytree have a single power of 10 kw .

{'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': '10 kw', 'subset': None}

{'func': 'all_str_eq', 'args': ['all_rows', 'signal power', '10 kw'], 'result': True, 'ind': 0, 'tointer': 'for the signal power records of all rows , all of them fuzzily match to 10 kw .', 'tostr': 'all_eq { all_rows ; signal power ; 10 kw } = true'}

all_eq { all_rows ; signal power ; 10 kw } = true

for the signal power records of all rows , all of them fuzzily match to 10 kw .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'signal power_3': 3, '10 kw_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'signal power_3': 'signal power', '10 kw_4': '10 kw'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'signal power_3': [0], '10 kw_4': [0]}

['channel', 'channel name', 'callsign', 'signal power', 'broadcast area']

[['1', 'nhk general tv / nhk g ( gtv )', 'joak - dtv', '10 kw', 'greater tokyo'], ['2', 'nhk educational tv / nhk e ( etv )', 'joab - dtv', '10 kw', 'all kantō'], ['4', 'nippon television / nittele ( ntv )', 'joax - dtv', '10 kw', 'all kantō'], ['5', 'tv asahi / tele - asa ( ex )', 'joex - dtv', '10 kw', 'all kantō'], ['6', 'tbs', 'jorx - dtv', '10 kw', 'all kantō'], ['7', 'tv tokyo / teleto ( tx )', 'jotx - dtv', '10 kw', 'all kantō'], ['8', 'fuji television ( cx )', 'jocx - dtv', '10 kw', 'all kantō']]

2009 - 10 leeds united a.f.c. season

https://en.wikipedia.org/wiki/2009%E2%80%9310_Leeds_United_A.F.C._season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22810095-9.html.csv

aggregation

the average age of a player in the 2009-10 leeds united a.f.c. season is 23.7 .

{'scope': 'all', 'col': '5', 'type': 'average', 'result': '23.7', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'age'], 'result': '23.7', 'ind': 0, 'tostr': 'avg { all_rows ; age }'}, '23.7'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; age } ; 23.7 } = true', 'tointer': 'the average of the age record of all rows is 23.7 .'}

round_eq { avg { all_rows ; age } ; 23.7 } = true

the average of the age record of all rows is 23.7 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'age_4': 4, '23.7_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'age_4': 'age', '23.7_5': '23.7'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'age_4': [0], '23.7_5': [1]}

['no', 'p', 'name', 'country', 'age', 'loan club', 'started', 'ended', 'start source', 'end source']

[['4', 'mf', 'michael doyle', 'ire', '28', 'coventry city', '6 aug', '8 may', 'leeds united', 'bbc sport'], ['30', 'gk', 'frank fielding', 'eng', '21', 'blackburn rovers', '29 sep', '26 oct', 'leeds united', 'leeds united'], ['15', 'fw', 'sam vokes', 'wal eng', '20', 'wolverhampton wanderers', '19 oct', '1 jan', 'leeds united', 'leeds united'], ['28', 'mf', 'max gradel', 'civ', '22', 'leicester city', '19 oct', '19 jan', 'leeds united', 'leeds united'], ['35', 'mf', 'hogan ephraim', 'eng', '21', 'queens park rangers', '26 nov', '1 jan', 'leeds united', 'qpr'], ['36', 'gk', 'david martin', 'eng', '24', 'liverpool', '26 nov', '10 feb', 'leeds united', 'sky sports'], ['30', 'df', 'tony capaldi', 'nir nor', '28', 'cardiff city', '26 nov', '4 jan', 'leeds united', 'leeds united'], ['15', 'fw', 'gary mcsheffrey', 'eng', '27', 'birmingham city', '29 jan', '8 may', 'leeds united', 'bbc sport'], ['21', 'df', 'shane lowry', 'aus', '20', 'aston villa', '29 jan', '8 may', 'leeds united', 'bbc sport'], ['33', 'df', 'neill collins', 'sco', '26', 'preston north end', '23 mar', '8 may', 'bbc sport', 'bbc sport']]

list of schools in the canterbury region

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12256602-2.html.csv

aggregation

total enrollment in schools in the canterbury region below the 8 decile is 770 .

{'scope': 'subset', 'col': '7', 'type': 'sum', 'result': '770', 'subset': {'col': '6', 'criterion': 'less_than', 'value': '8'}}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'decile', '8'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; decile ; 8 }', 'tointer': 'select the rows whose decile record is less than 8 .'}, 'roll'], 'result': '770', 'ind': 1, 'tostr': 'sum { filter_less { all_rows ; decile ; 8 } ; roll }'}, '770'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_less { all_rows ; decile ; 8 } ; roll } ; 770 } = true', 'tointer': 'select the rows whose decile record is less than 8 . the sum of the roll record of these rows is 770 .'}

round_eq { sum { filter_less { all_rows ; decile ; 8 } ; roll } ; 770 } = true

select the rows whose decile record is less than 8 . the sum of the roll record of these rows is 770 .

3

3

{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'decile_5': 5, '8_6': 6, 'roll_7': 7, '770_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'decile_5': 'decile', '8_6': '8', 'roll_7': 'roll', '770_8': '770'}

{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'decile_5': [0], '8_6': [0], 'roll_7': [1], '770_8': [2]}

['name', 'years', 'gender', 'area', 'authority', 'decile', 'roll']

[['amberley school', '1 - 8', 'coed', 'amberley', 'state', '7', '230'], ['amuri area school', '1 - 13', 'coed', 'culverden', 'state', '8', '270'], ['broomfield school', '1 - 8', 'coed', 'amberley', 'state', '9', '114'], ['cheviot area school', '1 - 13', 'coed', 'cheviot', 'state', '7', '170'], ['greta valley school', '1 - 8', 'coed', 'greta valley', 'state', '9', '31'], ['hanmer springs school', '1 - 8', 'coed', 'hanmer springs', 'state', '9', '99'], ['hurunui college', '1 - 13', 'coed', 'hawarden', 'state', '7', '236'], ['leithfield school', '1 - 8', 'coed', 'amberley', 'state', '8', '100'], ['omihi school', '1 - 8', 'coed', 'hurunui', 'state', '8', '29'], ['rotherham school', '1 - 6', 'coed', 'rotherham', 'state', '10', '36'], ['waiau school', '1 - 6', 'coed', 'waiau', 'state', '6', '61'], ['waikari school', '1 - 8', 'coed', 'waikari', 'state', '4', '34'], ['waipara school', '1 - 8', 'coed', 'waipara', 'state', '6', '39']]

1966 u.s. open ( golf )

https://en.wikipedia.org/wiki/1966_U.S._Open_%28golf%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17277136-4.html.csv

aggregation

all the players of the 1966 u.s. open ( golf ) had an average score of around 142 .

{'scope': 'all', 'col': '4', 'type': 'average', 'result': '142', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '142', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '142'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 142 } = true', 'tointer': 'the average of the score record of all rows is 142 .'}

round_eq { avg { all_rows ; score } ; 142 } = true

the average of the score record of all rows is 142 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '142_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '142_5': '142'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '142_5': [1]}

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

[['t1', 'billy casper', 'united states', '69 + 68 = 137', '- 3'], ['t1', 'arnold palmer', 'united states', '71 + 66 = 137', '- 3'], ['t3', 'phil rodgers', 'united states', '70 + 70 = 140', 'e'], ['t3', 'rives mcbee', 'united states', '76 + 64 = 140', 'e'], ['t5', 'jack nicklaus', 'united states', '71 + 71 = 142', '+ 2'], ['t5', 'johnny miller ( a )', 'united states', '70 + 72 = 142', '+ 2'], ['t7', 'julius boros', 'united states', '74 + 69 = 143', '+ 3'], ['t7', 'dave hill', 'united states', '72 + 71 = 143', '+ 3'], ['t7', 'kel nagle', 'australia', '70 + 73 = 143', '+ 3'], ['t10', 'bob goalby', 'united states', '71 + 73 = 144', '+ 4'], ['t10', 'al mengert', 'united states', '67 + 77 = 144', '+ 4']]

united states house of representatives elections , 1930

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1930

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342359-41.html.csv

comparative

edward everett eslick was elected to the house of representatives after gordon browning .

{'row_1': '4', 'row_2': '5', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'edward everett eslick'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to edward everett eslick .', 'tostr': 'filter_eq { all_rows ; incumbent ; edward everett eslick }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; edward everett eslick } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to edward everett eslick . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'gordon browning'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to gordon browning .', 'tostr': 'filter_eq { all_rows ; incumbent ; gordon browning }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; gordon browning } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to gordon browning . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; incumbent ; edward everett eslick } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; gordon browning } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to edward everett eslick . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to gordon browning . take the first elected record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; incumbent ; edward everett eslick } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; gordon browning } ; first elected } } = true

select the rows whose incumbent record fuzzily matches to edward everett eslick . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to gordon browning . take the first elected 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, 'incumbent_7': 7, 'edward everett eslick_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'gordon browning_12': 12, 'first elected_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', 'incumbent_7': 'incumbent', 'edward everett eslick_8': 'edward everett eslick', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'gordon browning_12': 'gordon browning', 'first elected_13': 'first elected'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'edward everett eslick_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'gordon browning_12': [1], 'first elected_13': [3]}

['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']

[['tennessee 3', 'sam d mcreynolds', 'democratic', '1922', 're - elected', 'sam d mcreynolds ( d ) unopposed'], ['tennessee 4', 'cordell hull', 'democratic', '1922', 'retired to run for u s senate democratic hold', 'john ridley mitchell ( d ) unopposed'], ['tennessee 5', 'ewin l davis', 'democratic', '1918', 're - elected', 'ewin l davis ( d ) 92.0 % george motlow ( r ) 8.0 %'], ['tennessee 7', 'edward everett eslick', 'democratic', '1924', 're - elected', 'edward everett eslick ( d ) unopposed'], ['tennessee 8', 'gordon browning', 'democratic', '1922', 're - elected', 'gordon browning ( d ) unopposed']]

list of airlines of singapore

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15520072-1.html.csv

ordinal

for the airlines of singapore , the one to commence operations on the 2nd earliest date was silkair .

{'row': '3', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

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

eq { hop { nth_argmin { all_rows ; commenced operations ; 2 } ; airlines } ; silkair } = true

select the row whose commenced operations record of all rows is 2nd minimum . the airlines record of this row is silkair .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'commenced operations_5': 5, '2_6': 6, 'airlines_7': 7, 'silkair_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', 'commenced operations_5': 'commenced operations', '2_6': '2', 'airlines_7': 'airlines', 'silkair_8': 'silkair'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'commenced operations_5': [0], '2_6': [0], 'airlines_7': [1], 'silkair_8': [2]}

['airlines', 'iata', 'icao', 'callsign', 'commenced operations']

[['jetstar asia airways', '3k', 'jsa', 'jetstar asia', '2004'], ['scoot', 'tz', 'sco', 'scooter', '2012'], ['silkair', 'mi', 'slk', 'silkair', '1976'], ['singapore airlines', 'sq', 'sia', 'singapore', '1947'], ['singapore airlines cargo', 'sq', 'sqc', 'singcargo', '2001'], ['tigerair', 'tr', 'tgw', 'go cat', '2003'], ['valuair', 'vf', 'vlu', 'valuair', '2004']]

athletics in jamaica

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15166232-1.html.csv

aggregation

for athletics in jamaica , the average time for the top 3 ranked athletes was 10.73 .

{'scope': 'subset', 'col': '2', 'type': 'average', 'result': '10.73', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '3'}}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'rank', '3'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; rank ; 3 }', 'tointer': 'select the rows whose rank record is less than or equal to 3 .'}, 'time'], 'result': '10.73', 'ind': 1, 'tostr': 'avg { filter_less_eq { all_rows ; rank ; 3 } ; time }'}, '10.73'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_less_eq { all_rows ; rank ; 3 } ; time } ; 10.73 } = true', 'tointer': 'select the rows whose rank record is less than or equal to 3 . the average of the time record of these rows is 10.73 .'}

round_eq { avg { filter_less_eq { all_rows ; rank ; 3 } ; time } ; 10.73 } = true

select the rows whose rank record is less than or equal to 3 . the average of the time record of these rows is 10.73 .

3

3

{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'rank_5': 5, '3_6': 6, 'time_7': 7, '10.73_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'rank_5': 'rank', '3_6': '3', 'time_7': 'time', '10.73_8': '10.73'}

{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'rank_5': [0], '3_6': [0], 'time_7': [1], '10.73_8': [2]}

['rank', 'time', 'athlete', 'nation', 'date', 'location']

[['1', '10.70', 'shelly - ann fraser', 'jamaica', '29 june 2012', 'kingston , jamaica'], ['2', '10.74', 'merlene ottey', 'jamaica', '7 september 1996', 'milan , italy'], ['3', '10.75', 'kerron stewart', 'jamaica', '10 july 2009', 'rome , italy'], ['4', '10.76', 'veronica campbell - brown', 'jamaica', '31 may 2011', 'ostrava , czech republic'], ['5', '10.82', 'sherone simpson', 'jamaica', '24 may 2006', 'kingston , jamaica']]

peter gethin

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226516-1.html.csv

unique

1974 was the only year that peter gethin used a lola t370 chassis .

{'scope': 'all', 'row': '9', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'lola t370', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'lola t370'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to lola t370 .', 'tostr': 'filter_eq { all_rows ; chassis ; lola t370 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; chassis ; lola t370 } }', 'tointer': 'select the rows whose chassis record fuzzily matches to lola t370 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'lola t370'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to lola t370 .', 'tostr': 'filter_eq { all_rows ; chassis ; lola t370 }'}, 'year'], 'result': '1974', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; chassis ; lola t370 } ; year }'}, '1974'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; chassis ; lola t370 } ; year } ; 1974 }', 'tointer': 'the year record of this unqiue row is 1974 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; chassis ; lola t370 } } ; eq { hop { filter_eq { all_rows ; chassis ; lola t370 } ; year } ; 1974 } } = true', 'tointer': 'select the rows whose chassis record fuzzily matches to lola t370 . there is only one such row in the table . the year record of this unqiue row is 1974 .'}

and { only { filter_eq { all_rows ; chassis ; lola t370 } } ; eq { hop { filter_eq { all_rows ; chassis ; lola t370 } ; year } ; 1974 } } = true

select the rows whose chassis record fuzzily matches to lola t370 . there is only one such row in the table . the year record of this unqiue row is 1974 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'chassis_7': 7, 'lola t370_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1974_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'chassis_7': 'chassis', 'lola t370_8': 'lola t370', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1974_10': '1974'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'chassis_7': [0], 'lola t370_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1974_10': [3]}

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

[['1970', 'bruce mclaren motor racing', 'mclaren m14a', 'ford v8', '1'], ['1971', 'bruce mclaren motor racing', 'mclaren m14a', 'ford v8', '9'], ['1971', 'bruce mclaren motor racing', 'mclaren m19a', 'ford v8', '9'], ['1971', 'yardley team brm', 'brm p160', 'brm v12', '9'], ['1972', 'marlboro brm', 'brm p160b', 'brm v12', '1'], ['1972', 'marlboro brm', 'brm p180', 'brm v12', '1'], ['1972', 'marlboro brm', 'brm p160c', 'brm v12', '1'], ['1973', 'marlboro brm', 'brm p160e', 'brm v12', '0'], ['1974', 'embassy racing with graham hill', 'lola t370', 'ford v8', '0']]

chutes too narrow

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1236321-2.html.csv

majority

the majority of the accolades for chutes too narrow came from the us with a total of four versus two accolades from the uk .

{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'us', 'subset': None}

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

most_eq { all_rows ; country ; us } = true

for the country records of all rows , most of them fuzzily match to us .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'us_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'us_4': 'us'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'us_4': [0]}

['publication', 'country', 'accolade', 'year', 'rank']

[['the av club', 'us', 'the best music of the decade', '2009', '17'], ['nme', 'uk', 'the top 100 greatest albums of the decade', '2009', '75'], ['paste', 'us', 'the 50 best albums of the decade ( 2000 - 2009 )', '2009', '24'], ['pitchfork media', 'us', 'the top 200 albums of the 2000s', '2009', '46'], ['slant magazine', 'us', 'best of the aughts : albums', '2009', '91'], ['uncut', 'uk', '150 greatest albums of the decade', '2009', '113']]

texas world speedway

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1405704-1.html.csv

count

aj foyt was the winning driver in four different races .

{'scope': 'all', 'criterion': 'equal', 'value': 'aj foyt', 'result': '4', 'col': '3', 'subset': None}

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

eq { count { filter_eq { all_rows ; winning driver ; aj foyt } } ; 4 } = true

select the rows whose winning driver record fuzzily matches to aj foyt . 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, 'winning driver_5': 5, 'aj foyt_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', 'winning driver_5': 'winning driver', 'aj foyt_6': 'aj foyt', '4_7': '4'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winning driver_5': [0], 'aj foyt_6': [0], '4_7': [2]}

['season', 'race name', 'winning driver', 'chassis', 'engine', 'tires', 'team']

[['1973', 'texas 200', 'al unser', 'parnelli', 'offenhauser', 'firestone', 'vels parnelli jones'], ['1976', 'texas 150', 'aj foyt', 'coyote', 'foyt', 'goodyear', 'gilmore racing'], ['1976', 'benihana world series of auto racing', 'johnny rutherford', 'mclaren', 'offenhauser', 'goodyear', 'team mclaren'], ['1977', 'texas grand prix', 'tom sneva', 'mclaren', 'cosworth', 'goodyear', 'team penske'], ['1977', 'american parts 200', 'johnny rutherford', 'mclaren', 'cosworth', 'goodyear', 'team mclaren'], ['1978', 'coors 200', 'danny ongais', 'parnelli', 'cosworth', 'goodyear', 'interscope racing'], ['1978', 'texas grand prix', 'aj foyt', 'coyote', 'foyt', 'goodyear', 'gilmore racing'], ['1979', 'coors 200', 'aj foyt', 'coyote', 'foyt', 'goodyear', 'gilmore racing'], ['1979', 'lubriloln grand prix', 'aj foyt', 'parnelli', 'cosworth', 'goodyear', 'gilmore racing']]

blackberry storm

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18082541-2.html.csv

ordinal

vodafone au is the blackberry storm carrier that has the second highest package version .

{'row': '6', 'col': '3', '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', 'package version', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; package version ; 2 }'}, 'carrier'], 'result': 'vodafone au', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; package version ; 2 } ; carrier }'}, 'vodafone au'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; package version ; 2 } ; carrier } ; vodafone au } = true', 'tointer': 'select the row whose package version record of all rows is 2nd maximum . the carrier record of this row is vodafone au .'}

eq { hop { nth_argmax { all_rows ; package version ; 2 } ; carrier } ; vodafone au } = true

select the row whose package version record of all rows is 2nd maximum . the carrier record of this row is vodafone au .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'package version_5': 5, '2_6': 6, 'carrier_7': 7, 'vodafone au_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', 'package version_5': 'package version', '2_6': '2', 'carrier_7': 'carrier', 'vodafone au_8': 'vodafone au'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'package version_5': [0], '2_6': [0], 'carrier_7': [1], 'vodafone au_8': [2]}

['device', 'carrier', 'package version', 'applications', 'software platform']

[['blackberry storm 9530', 'mts mobility', '5.0.0.808', '5.0.0.419', '4.2.0.179'], ['blackberry storm 9530', 'verizon wireless', '5.0.0.328', '5.0.0.328', '4.2.0.128'], ['blackberry storm 9530', 'telus mobility', '5.0.0.419', '5.0.0.419', '4.2.0.179'], ['blackberry storm 9530', 'bell mobility', '5.0.0.419', '5.0.0.419', '4.2.0.179'], ['blackberry storm 9530', 'iusacell', '4.7.0.208', '4.7.0.151', '4.0.0.186'], ['blackberry storm 9500', 'vodafone au', '5.0.0.742', '5.0.0.451', '4.2.0.198']]

2008 - 09 segunda división b

https://en.wikipedia.org/wiki/2008%E2%80%9309_Segunda_Divisi%C3%B3n_B

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18160020-8.html.csv

ordinal

rubén martínez had the second lowest goals allowed average of any goalkeeper in the 2008-09 segunda división .

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

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

eq { hop { nth_argmin { all_rows ; average ; 2 } ; goalkeeper } ; rubén martínez } = true

select the row whose average record of all rows is 2nd minimum . the goalkeeper record of this row is rubén martínez .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'average_5': 5, '2_6': 6, 'goalkeeper_7': 7, 'rubén martínez_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', 'average_5': 'average', '2_6': '2', 'goalkeeper_7': 'goalkeeper', 'rubén martínez_8': 'rubén martínez'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'average_5': [0], '2_6': [0], 'goalkeeper_7': [1], 'rubén martínez_8': [2]}

['goalkeeper', 'goals', 'matches', 'average', 'team']

[['miguel zapata', '17', '28', '0.61', 'atlético ciudad'], ['rubén martínez', '24', '32', '0.75', 'cartagena'], ['orlando quintana', '29', '34', '0.85', 'lorca deportiva'], ['álvaro campos', '24', '28', '0.86', 'real murcia b'], ['matías garavano', '26', '30', '0.87', 'mérida']]

adam lambert

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21501511-1.html.csv

count

adam lambert sang a song in a week named hollywood three times .

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

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

eq { count { filter_eq { all_rows ; week ; hollywood } } ; 3 } = true

select the rows whose week record fuzzily matches to hollywood . 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, 'week_5': 5, 'hollywood_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', 'week_5': 'week', 'hollywood_6': 'hollywood', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'week_5': [0], 'hollywood_6': [0], '3_7': [2]}

['week', 'theme', 'song choice', 'original artist', 'order', 'result']

[['audition', "auditioner 's choice", 'rock with you bohemian rhapsody', 'michael jackson queen', 'n / a', 'advanced'], ['hollywood', 'first solo', "what 's up", '4 non blondes', 'n / a', 'advanced'], ['hollywood', 'group performance', 'some kind of wonderful', 'soul brothers six', 'n / a', 'advanced'], ['hollywood', 'second solo', 'believe', 'cher', 'n / a', 'advanced'], ['top 36 / semi - final 2', 'billboard hot 100 hits to date', "( i ca n't get no ) satisfaction", 'the rolling stones', '12', 'advanced'], ['top 13', 'michael jackson', 'black or white', 'michael jackson', '11', 'safe'], ['top 11', 'grand ole opry', 'ring of fire', 'anita carter', '5', 'safe'], ['top 10', 'motown', 'the tracks of my tears', 'the miracles', '8', 'safe'], ['top 9', 'top downloads', 'play that funky music', 'wild cherry', '8', 'safe'], ['top 8', 'year they were born ( 1982 )', 'mad world', 'tears for fears', '8', 'safe'], ['top 7', 'songs from the cinema', 'born to be wild easy rider', 'steppenwolf', '3', 'safe'], ['top 7', 'disco', "if i ca n't have you", 'yvonne elliman', '5', 'safe']]

1946 vfl season

https://en.wikipedia.org/wiki/1946_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809368-18.html.csv

majority

the majority of venues in the 1946 vfl season drew over 10000 in crowd attendance .

{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10000', 'subset': None}

{'func': 'most_greater', 'args': ['all_rows', 'crowd', '10000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than 10000 .', 'tostr': 'most_greater { all_rows ; crowd ; 10000 } = true'}

most_greater { all_rows ; crowd ; 10000 } = true

for the crowd records of all rows , most of them are greater than 10000 .

1

1

{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '10000_4': 4}

{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '10000_4': '10000'}

{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '10000_4': [0]}

['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']

[['north melbourne', '11.8 ( 74 )', 'south melbourne', '15.19 ( 109 )', 'arden street oval', '7000', '24 august 1946'], ['footscray', '23.27 ( 165 )', 'hawthorn', '8.5 ( 53 )', 'western oval', '12000', '24 august 1946'], ['fitzroy', '9.11 ( 65 )', 'melbourne', '10.9 ( 69 )', 'brunswick street oval', '19000', '24 august 1946'], ['collingwood', '17.26 ( 128 )', 'geelong', '7.11 ( 53 )', 'victoria park', '11000', '24 august 1946'], ['st kilda', '11.9 ( 75 )', 'essendon', '16.20 ( 116 )', 'junction oval', '9000', '24 august 1946'], ['richmond', '16.29 ( 125 )', 'carlton', '13.15 ( 93 )', 'punt road oval', '38000', '24 august 1946']]

utah jazz all - time roster

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11545282-10.html.csv

majority

all of the players on the utah jazz all - time roster have united states nationality .

{'scope': 'all', 'col': '2', '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', 'nationality', 'position', 'years for jazz', 'school / club team']

[['mark jackson', 'united states', 'point guard', '2002 - 03', "st john 's"], ['dave jamerson', 'united states', 'guard - forward', '1993', 'ohio'], ['aaron james', 'united states', 'forward', '1974 - 79', 'grambling state'], ['henry james', 'united states', 'forward', '1993', "st mary 's ( tx )"], ['al jefferson', 'united states', 'forward - center', '2010 - present', 'prentiss high school'], ['eric johnson', 'united states', 'guard', '1989 - 90', 'nebraska'], ['ollie johnson', 'united states', 'forward', '1974 - 75', 'temple'], ['nate johnston', 'united states', 'forward', '1989 - 90', 'tampa'], ['jeff judkins', 'united states', 'guard', '1980 - 81', 'utah']]

f.c. halifax town

https://en.wikipedia.org/wiki/F.C._Halifax_Town

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18443295-5.html.csv

count

for f.c. halifax town , there were three times that lee gregory was the leading scorer .

{'scope': 'all', 'criterion': 'equal', 'value': 'lee gregory', 'result': '3', 'col': '4', 'subset': None}

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

eq { count { filter_eq { all_rows ; leading scorer ; lee gregory } } ; 3 } = true

select the rows whose leading scorer record fuzzily matches to lee gregory . 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, 'leading scorer_5': 5, 'lee gregory_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', 'leading scorer_5': 'leading scorer', 'lee gregory_6': 'lee gregory', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'leading scorer_5': [0], 'lee gregory_6': [0], '3_7': [2]}

['year', 'league', 'position', 'leading scorer', 'fa cup', 'fa trophy']

[['2008 - 09', 'northern premier league division one north', '8 / 21', 'ashley stott ( 20 )', 'qr2', 'pr'], ['2009 - 10', 'northern premier league division one north', '1 / 22 promoted', 'james dean ( 27 )', 'qr4', 'qr3'], ['2010 - 11', 'northern premier league premier division', '1 / 22 promoted', 'jamie vardy ( 25 )', 'qr4', 'qr2'], ['2011 - 12', 'conference north', '3 / 22', 'lee gregory ( 20 )', 'r1', 'qr3'], ['2012 - 13', 'conference north', '5 / 22 promoted', 'lee gregory ( 22 )', 'qr4', 'qf'], ['2013 - 14', 'conference premier', '11 / 24', 'lee gregory ( 8 )', 'r1', 'n / a']]

united states amateur championship ( golf )

https://en.wikipedia.org/wiki/United_States_Amateur_Championship_%28golf%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1510466-2.html.csv

majority

all of the united states amateur golf championships were played in the month of august .

{'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'august', 'subset': None}

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

all_eq { all_rows ; dates ; august } = true

for the dates records of all rows , all of them fuzzily match to august .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'dates_3': 3, 'august_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'dates_3': 'dates', 'august_4': 'august'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'dates_3': [0], 'august_4': [0]}

['year', 'edition', 'course', 'location', 'dates']

[['2013', '113th', 'the country club', 'brookline , massachusetts', 'august 12 - 18'], ['2014', '114th', 'atlanta athletic club , highlands course', 'johns creek , georgia', 'august 11 - 17'], ['2015', '115th', 'olympia fields country club , north course', 'olympia fields , illinois', 'august 17 - 23'], ['2016', '116th', 'oakland hills country club , south course', 'bloomfield township , michigan', 'august 15 - 21'], ['2017', '117th', 'riviera country club', 'pacific palisades , california', 'august 14 - 20'], ['2018', '118th', 'pebble beach golf links', 'pebble beach , california', 'august 13 - 19']]

piano concerto ( scriabin )

https://en.wikipedia.org/wiki/Piano_Concerto_%28Scriabin%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17943770-1.html.csv

comparative

piano concerto was released by rca before it was released by abc classics .

{'row_1': '7', 'row_2': '15', 'col': '4', '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', 'record company', 'rca'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose record company record fuzzily matches to rca .', 'tostr': 'filter_eq { all_rows ; record company ; rca }'}, 'year of recording'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; record company ; rca } ; year of recording }', 'tointer': 'select the rows whose record company record fuzzily matches to rca . take the year of recording record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'record company', 'abc classics'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose record company record fuzzily matches to abc classics .', 'tostr': 'filter_eq { all_rows ; record company ; abc classics }'}, 'year of recording'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; record company ; abc classics } ; year of recording }', 'tointer': 'select the rows whose record company record fuzzily matches to abc classics . take the year of recording record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; record company ; rca } ; year of recording } ; hop { filter_eq { all_rows ; record company ; abc classics } ; year of recording } } = true', 'tointer': 'select the rows whose record company record fuzzily matches to rca . take the year of recording record of this row . select the rows whose record company record fuzzily matches to abc classics . take the year of recording record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; record company ; rca } ; year of recording } ; hop { filter_eq { all_rows ; record company ; abc classics } ; year of recording } } = true

select the rows whose record company record fuzzily matches to rca . take the year of recording record of this row . select the rows whose record company record fuzzily matches to abc classics . take the year of recording 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, 'record company_7': 7, 'rca_8': 8, 'year of recording_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'record company_11': 11, 'abc classics_12': 12, 'year of recording_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', 'record company_7': 'record company', 'rca_8': 'rca', 'year of recording_9': 'year of recording', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'record company_11': 'record company', 'abc classics_12': 'abc classics', 'year of recording_13': 'year of recording'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'record company_7': [0], 'rca_8': [0], 'year of recording_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'record company_11': [1], 'abc classics_12': [1], 'year of recording_13': [3]}

['pianist', 'conductor', 'record company', 'year of recording', 'format']

[['heinrich neuhaus', 'nikolai golovanov', 'russian disc', '1946', 'cd'], ['solomon cutner', 'issay dobrowen', 'emi', '1949', 'cd'], ['samuil feinberg', 'alexander gauk', 'brilliant classics', '1950', 'cd'], ['roland pãntinen', 'leif segerstam', 'bis records', '1989', 'cd'], ['vladimir ashkenazy', 'lorin maazel', 'decca', '1990', 'cd'], ['aleksey nasedkin', 'evgeny svetlanov', 'melodiya', '1990', 'cd'], ['gerhard oppitz', 'dmitri kitaenko', 'rca', '1993', 'cd'], ['nikolai demidenko', 'alexander lazarev', 'hyperion records', '1993', 'cd'], ['michael ponti', 'hans drewanz', 'turnabout', '1994', 'cd'], ['garrick ohlsson', 'libor pesek', 'supraphon', '1996', 'cd'], ['arkady sevidov', 'konstantin krimets', 'arte nova', '1996', 'cd'], ['konstantin scherbakov', 'igor golovchin', 'naxos records', '1996', 'cd'], ['eugeni mikhailov', 'vladimir ponkin', 'vista vera', '1996', 'cd'], ['anatol ugorski', 'pierre boulez', 'deutsche grammophon', '1999', 'cd'], ['roger woodward', 'edo de waart', 'abc classics', '1999', 'cd'], ['andrei korobeinikov', 'mikhail snitko', 'olympia records', '2007', 'cd']]

1960 dallas cowboys season

https://en.wikipedia.org/wiki/1960_Dallas_Cowboys_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17946716-1.html.csv

majority

most of the dallas cowboys games in the 1960 season they lost .

{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None}

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

most_eq { all_rows ; result ; l } = true

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

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'l_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'l_4': 'l'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'l_4': [0]}

['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance']

[['1', 'september 24 , 1960', 'pittsburgh steelers', 'l 28 - 35', 'cotton bowl', '0 - 1', '30000'], ['2', 'september 30 , 1960', 'philadelphia eagles', 'l 25 - 27', 'cotton bowl', '0 - 2', '18500'], ['3', 'october 9 , 1960', 'washington redskins', 'l 14 - 26', 'griffith stadium', '0 - 3', '21142'], ['4', 'october 16 , 1960', 'cleveland browns', 'l 7 - 48', 'cotton bowl', '0 - 4', '28500'], ['5', 'october 23 , 1960', 'st louis cardinals', 'l 10 - 12', 'busch stadium', '0 - 5', '23128'], ['6', 'october 30 , 1960', 'baltimore colts', 'l 7 - 45', 'cotton bowl', '0 - 6', '25500'], ['7', 'november 6 , 1960', 'los angeles rams', 'l 13 - 38', 'cotton bowl', '0 - 7', '16000'], ['8', 'november 13 , 1960', 'green bay packers', 'l 7 - 41', 'lambeau field', '0 - 8', '32294'], ['9', 'november 20 , 1960', 'san francisco 49ers', 'l 14 - 26', 'cotton bowl', '0 - 9', '10000'], ['10', 'november 27 , 1960', 'chicago bears', 'l 7 - 17', 'wrigley field', '0 - 10', '39951'], ['11', 'december 4 , 1960', 'new york giants', 't 31 - 31', 'yankee stadium', '0 - 10 - 1', '55033'], ['12', 'december 11 , 1960', 'detroit lions', 'l 14 - 23', 'briggs stadium', '0 - 11 - 1', '43272'], ['13', '-', '-', '-', '-', '-', '']]

travis parrott

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18149740-3.html.csv

unique

the tournament in valencia , spain was the only tournament travis parrott played on a clay surface .

{'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'clay', 'subset': None}

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

and { only { filter_eq { all_rows ; surface ; clay } } ; eq { hop { filter_eq { all_rows ; surface ; clay } ; tournament } ; valencia , spain } } = true

select the rows whose surface record fuzzily matches to clay . there is only one such row in the table . the tournament record of this unqiue row is valencia , spain .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'clay_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'valencia , spain_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'clay_8': 'clay', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'valencia , spain_10': 'valencia , spain'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'clay_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'valencia , spain_10': [3]}

['date', 'tournament', 'surface', 'partnering', 'opponent in the final', 'score']

[['august 16 , 2004', 'washington , dc , united states', 'hard', 'dmitry tursunov', 'chris haggard robbie koenig', '7 - 6 3 , 6 - 1'], ['july 4 , 2005', 'newport , us', 'grass', 'graydon oliver', 'jordan kerr jim thomas', '7 - 6 5 , 7 - 6 5'], ['april 14 , 2008', 'valencia , spain', 'clay', 'filip polášek', 'máximo gonzález juan mónaco', '7 - 5 , 7 - 5'], ['august 4 , 2008', 'los angeles , us', 'hard', 'dušan vemić', 'rohan bopanna eric butorac', '7 - 6 5 , 7 - 6 5'], ['february 22 , 2009', 'memphis , tennessee , us', 'hard', 'filip polášek', 'mardy fish mark knowles', '7 - 6 7 , 6 - 1'], ['june 19 , 2009', 'eastbourne , united kingdom', 'grass', 'filip polášek', 'mariusz fyrstenberg marcin matkowski', '6 - 4 , 6 - 4']]

mobile network operators of india

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23801721-1.html.csv

unique

only one mobile network company uses wifi as a technology .

{'scope': 'all', 'row': '4', 'col': '3', 'col_other': 'n/a', 'criterion': 'fuzzily_match', 'value': 'wifi', 'subset': None}

{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'technology', 'wifi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose technology record fuzzily matches to wifi .', 'tostr': 'filter_eq { all_rows ; technology ; wifi }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; technology ; wifi } } = true', 'tointer': 'select the rows whose technology record fuzzily matches to wifi . there is only one such row in the table .'}

only { filter_eq { all_rows ; technology ; wifi } } = true

select the rows whose technology record fuzzily matches to wifi . there is only one such row in the table .

2

2

{'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'technology_4': 4, 'wifi_5': 5}

{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'technology_4': 'technology', 'wifi_5': 'wifi'}

{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'technology_4': [0], 'wifi_5': [0]}

['rank', 'operators name', 'technology', 'subscribers ( in millions )', 'ownership', 'market share']

[['2', 'reliance communications', 'cdmaone evdo gsm hspa wimax', '154.11 ( september 2012 )', 'reliance adag ( 67 % ) public ( 26 % )', 'n / a'], ['3', 'vodafone', 'gsm edge hsdpa', '155.5 ( october 2013 )', 'vodafone group ( 100 % )', '22.91 % ( october 2013 )'], ['4', 'idea cellular', 'gsm edge hspa', '127.2 ( q2 2013 )', 'aditya birla ( 49.05 % ) axiata group berhad ( 19.96 % )', '18.74 % ( october 2013 )'], ['5', 'bsnl', 'gsm edge hsdpa hspa + cdmaone evdo wimax wifi', '97.17 ( october 2013 )', 'state - owned', '14.31 % ( october 2013 )'], ['6', 'tata docomo virgin mobile india talk24 / t24', 'cdma evdo gsm edge hspa +', '90.09 ( august 2012 )', 'tata teleservices ( 74 % ) ntt docomo ( 26 % )', 'n / a'], ['7', 'aircel', 'gsm edge hsdpa', '63.20 ( october 2013 )', 'maxis communications ( 74 % ) apollo hospital ( 26 % )', '9.32 % ( october 2013 )'], ['9', 'mts india', 'cdma evdo', '14.01 ( october 2011 )', 'sistema ( 73.71 % ) shyam group ( 23.79 % )', 'n / a'], ['10', 'videocon', 'gsm gprs edge', '3.24 ( october 2013 )', 'videocon', '0.48 % ( october 2013 )'], ['11', 'mtnl', 'gsm hsdpa cdma', '3.61 ( october 2013 )', 'state - owned', '0.53 % ( october 2013 )'], ['12', 'loop mobile', 'gsm edge', '3.02 ( october 2013 )', 'khaitan holding group ( 100 % )', '0.45 % ( october 2013 )']]

wichita - class replenishment oiler

https://en.wikipedia.org/wiki/Wichita-class_replenishment_oiler

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15204876-1.html.csv

ordinal

in the wichita - class replenishment oiler , wichita is the earliest ship to be decommissioned among the ones built by general dynamics , quincy .

{'scope': 'subset', 'row': '1', 'col': '5', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'general dynamics , quincy'}}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'builder', 'general dynamics , quincy'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; builder ; general dynamics , quincy }', 'tointer': 'select the rows whose builder record fuzzily matches to general dynamics , quincy .'}, 'commissioned - decommissioned', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; builder ; general dynamics , quincy } ; commissioned - decommissioned ; 1 }'}, 'ship'], 'result': 'wichita', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; builder ; general dynamics , quincy } ; commissioned - decommissioned ; 1 } ; ship }'}, 'wichita'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; builder ; general dynamics , quincy } ; commissioned - decommissioned ; 1 } ; ship } ; wichita } = true', 'tointer': 'select the rows whose builder record fuzzily matches to general dynamics , quincy . select the row whose commissioned - decommissioned record of these rows is 1st minimum . the ship record of this row is wichita .'}

eq { hop { nth_argmin { filter_eq { all_rows ; builder ; general dynamics , quincy } ; commissioned - decommissioned ; 1 } ; ship } ; wichita } = true

select the rows whose builder record fuzzily matches to general dynamics , quincy . select the row whose commissioned - decommissioned record of these rows is 1st minimum . the ship record of this row is wichita .

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, 'builder_6': 6, 'general dynamics , quincy_7': 7, 'commissioned - decommissioned_8': 8, '1_9': 9, 'ship_10': 10, 'wichita_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', 'builder_6': 'builder', 'general dynamics , quincy_7': 'general dynamics , quincy', 'commissioned - decommissioned_8': 'commissioned - decommissioned', '1_9': '1', 'ship_10': 'ship', 'wichita_11': 'wichita'}

{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'builder_6': [0], 'general dynamics , quincy_7': [0], 'commissioned - decommissioned_8': [1], '1_9': [1], 'ship_10': [2], 'wichita_11': [3]}

['ship', 'hull no', 'builder', 'home port', 'commissioned - decommissioned', 'nvr page']

[['wichita', 'aor - 1', 'general dynamics , quincy', 'oakland', '1969 - 1993', 'aor - 1'], ['milwaukee', 'aor - 2', 'general dynamics , quincy', 'norfolk', '1969 - 1994', 'aor - 2'], ['kansas city', 'aor - 3', 'general dynamics , quincy', 'oakland', '1970 - 1994', 'aor - 3'], ['savannah', 'aor - 4', 'general dynamics , quincy', 'norfolk', '1970 - 1995', 'aor - 4'], ['wabash', 'aor - 5', 'general dynamics , quincy', 'long beach', '1971 - 1994', 'aor - 5'], ['kalamazoo', 'aor - 6', 'general dynamics , quincy', 'norfolk', '1973 - 1996', 'aor - 6'], ['roanoke', 'aor - 7', 'national steel', 'long beach', '1976 - 1995', 'aor - 7']]

1968 formula one season

https://en.wikipedia.org/wiki/1968_Formula_One_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1140095-1.html.csv

majority

in the 1968 season ford was the constructor for most of the winning drivers .

{'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'ford', 'subset': None}

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

most_eq { all_rows ; constructor ; ford } = true

for the constructor records of all rows , most of them fuzzily match to ford .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'constructor_3': 3, 'ford_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'constructor_3': 'constructor', 'ford_4': 'ford'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'constructor_3': [0], 'ford_4': [0]}

['race', 'circuit', 'date', 'pole position', 'fastest lap', 'winning driver', 'constructor', 'tyre', 'report']

[['south african grand prix', 'kyalami', '1 january', 'jim clark', 'jim clark', 'jim clark', 'lotus - ford', 'f', 'report'], ['spanish grand prix', 'jarama', '12 may', 'chris amon', 'jean - pierre beltoise', 'graham hill', 'lotus - ford', 'f', 'report'], ['monaco grand prix', 'monaco', '26 may', 'graham hill', 'richard attwood', 'graham hill', 'lotus - ford', 'f', 'report'], ['belgian grand prix', 'spa - francorchamps', '9 june', 'chris amon', 'john surtees', 'bruce mclaren', 'mclaren - ford', 'g', 'report'], ['dutch grand prix', 'zandvoort', '23 june', 'chris amon', 'jean - pierre beltoise', 'jackie stewart', 'matra - ford', 'd', 'report'], ['french grand prix', 'rouen - les - essarts', '7 july', 'jochen rindt', 'pedro rodríguez', 'jacky ickx', 'ferrari', 'f', 'report'], ['british grand prix', 'brands hatch', '20 july', 'graham hill', 'jo siffert', 'jo siffert', 'lotus - ford', 'f', 'report'], ['german grand prix', 'nürburgring', '4 august', 'jacky ickx', 'jackie stewart', 'jackie stewart', 'matra - ford', 'd', 'report'], ['italian grand prix', 'monza', '8 september', 'john surtees', 'jackie oliver', 'denny hulme', 'mclaren - ford', 'g', 'report'], ['canadian grand prix', 'mont - tremblant', '22 september', 'jochen rindt', 'jo siffert', 'denny hulme', 'mclaren - ford', 'g', 'report'], ['united states grand prix', 'watkins glen', '6 october', 'mario andretti', 'jackie stewart', 'jackie stewart', 'matra - ford', 'd', 'report'], ['mexican grand prix', 'hermanos rodriguez', '3 november', 'jo siffert', 'jo siffert', 'graham hill', 'lotus - ford', 'f', 'report']]

looney tunes and merrie melodies filmography ( 1929 - 39 )

https://en.wikipedia.org/wiki/Looney_Tunes_and_Merrie_Melodies_filmography_%281929%E2%80%9339%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18792938-2.html.csv

superlative

the film titled ' bosko 's fox hunt ' had the highest production number of the 1929-39 looney tunes and merrie melodies films .

{'scope': 'all', 'col_superlative': '4', 'row_superlative': '16', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'production num'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; production num }'}, 'title'], 'result': "bosko 's fox hunt", 'ind': 1, 'tostr': 'hop { argmax { all_rows ; production num } ; title }'}, "bosko 's fox hunt"], 'result': True, 'ind': 2, 'tostr': "eq { hop { argmax { all_rows ; production num } ; title } ; bosko 's fox hunt } = true", 'tointer': "select the row whose production num record of all rows is maximum . the title record of this row is bosko 's fox hunt ."}

eq { hop { argmax { all_rows ; production num } ; title } ; bosko 's fox hunt } = true

select the row whose production num record of all rows is maximum . the title record of this row is bosko 's fox hunt .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'production num_5': 5, 'title_6': 6, "bosko 's fox hunt_7": 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'production num_5': 'production num', 'title_6': 'title', "bosko 's fox hunt_7": "bosko 's fox hunt"}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'production num_5': [0], 'title_6': [1], "bosko 's fox hunt_7": [2]}

['title', 'series', 'characters', 'production num', 'release date']

[['big man from the north', 'lt', 'bosko , honey', '4500', '1931 - 01 - xx'], ["ai n't nature grand !", 'lt', 'bosko', '4626', '1931 - 03 - xx'], ["ups 'n downs", 'lt', 'bosko', '4640', '1931 - 03 - xx'], ['dumb patrol', 'lt', 'bosko , honey', '4664', '1931 - 05 - xx'], ['yodeling yokels', 'lt', 'bosko , honey', '4680', '1931 - 06 - xx'], ["bosko 's holiday", 'lt', 'bosko , honey', '4694', '1931 - 07 - xx'], ["the tree 's knees", 'lt', 'bosko', '4725', '1931 - 07 - xx'], ['lady , play your mandolin !', 'mm', 'animals ( cartoon character ) , foxy , roxy', '4645', '1931 - 08 - xx'], ['smile , darn ya , smile !', 'mm', 'foxy , radio , roxy', '4825', '1931 - 09 - 05'], ['bosko shipwrecked', 'lt', 'bosko', '4666', '1931 - 09 - 19'], ['one more time', 'mm', 'foxy , mugs , roxy', '4851', '1931 - 10 - 03'], ['bosko the doughboy', 'lt', 'bosko', '5017', '1931 - 10 - 17'], ["you do n't know what you 're doin '", 'mm', 'fluffy , piggy , the car', '4977', '1931 - 10 - 31'], ["bosko 's soda fountain", 'lt', 'bosko', '5045', '1931 - 11 - 14'], ["hittin ' the trail for hallelujah land", 'mm', 'banjo player , fluffy', '5025', '11 / 28 / 31'], ["bosko 's fox hunt", 'lt', 'bosko , bruno', '5046', '1931 - 12 - 12'], ['red - headed baby', 'mm', 'red - headed baby , toymaker', '5038', '1931 - 12 - 26']]

pas de peyrol

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18369222-1.html.csv

unique

richard virenque was the only leader at the summit in category 1 .

{'scope': 'all', 'row': '3', 'col': '3', 'col_other': '6', 'criterion': 'equal', 'value': '1', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'category', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; category ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; category ; 1 } }', 'tointer': 'select the rows whose category record is equal to 1 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'category', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; category ; 1 }'}, 'leader at the summit'], 'result': 'richard virenque', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; category ; 1 } ; leader at the summit }'}, 'richard virenque'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; category ; 1 } ; leader at the summit } ; richard virenque }', 'tointer': 'the leader at the summit record of this unqiue row is richard virenque .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; category ; 1 } } ; eq { hop { filter_eq { all_rows ; category ; 1 } ; leader at the summit } ; richard virenque } } = true', 'tointer': 'select the rows whose category record is equal to 1 . there is only one such row in the table . the leader at the summit record of this unqiue row is richard virenque .'}

and { only { filter_eq { all_rows ; category ; 1 } } ; eq { hop { filter_eq { all_rows ; category ; 1 } ; leader at the summit } ; richard virenque } } = true

select the rows whose category record is equal to 1 . there is only one such row in the table . the leader at the summit record of this unqiue row is richard virenque .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'category_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'leader at the summit_9': 9, 'richard virenque_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'category_7': 'category', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'leader at the summit_9': 'leader at the summit', 'richard virenque_10': 'richard virenque'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'category_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'leader at the summit_9': [2], 'richard virenque_10': [3]}

['year', 'stage', 'category', 'start', 'finish', 'leader at the summit']

[['2011', '9', '2', 'issoire', 'st flour', 'thomas voeckler'], ['2008', '7', '2', 'brioude', 'aurillac', 'david de la fuente'], ['2004', '10', '1', 'limoges', 'st flour', 'richard virenque'], ['1985', '15', '2', 'saint - étienne', 'aurillac', 'eduardo chozas'], ['1983', '14', '2', 'aurillac', 'issoire', 'lucien van impe'], ['1975', '14', '3', 'aurillac', 'puy - de - dôme', 'lucien van impe'], ['1968', '17', '3', 'aurillac', 'saint - étienne', 'aurelio gonzalez'], ['1963', '14', '3', 'aurillac', 'saint - étienne', 'federico bahamontes'], ['1959', '14', '2', 'aurillac', 'clermont - ferrand', 'louis bergaud']]

duneland athletic conference

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15090962-1.html.csv

majority

all of the teams in the duneland athletic conference belonged to the 4a ihsaa class .

{'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'equal', 'value': '4a', 'subset': None}

{'func': 'all_str_eq', 'args': ['all_rows', 'ihsaa class', '4a'], 'result': True, 'ind': 0, 'tointer': 'for the ihsaa class records of all rows , all of them fuzzily match to 4a .', 'tostr': 'all_eq { all_rows ; ihsaa class ; 4a } = true'}

all_eq { all_rows ; ihsaa class ; 4a } = true

for the ihsaa class records of all rows , all of them fuzzily match to 4a .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'ihsaa class_3': 3, '4a_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'ihsaa class_3': 'ihsaa class', '4a_4': '4a'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'ihsaa class_3': [0], '4a_4': [0]}

['school', 'location', 'mascot', 'county', 'enrollment 08 - 09', 'ihsaa class', 'ihsaa class football', 'year joined', 'previous conference']

[['chesterton', 'chesterton', 'trojans', '64 porter', '1921', '4a', '6a', '1970', 'calumet'], ['crown point', 'crown point', 'bulldogs', '45 lake', '2426', '4a', '6a', '1993', 'lake suburban'], ['lake central', 'saint john', 'indians', '45 lake', '3141', '4a', '6a', '2003', 'independents'], ['laporte', 'laporte', 'slicers', '46 laporte', '1956', '4a', '5a', '1976', 'northern indiana'], ['merrillville', 'merrillville', 'pirates', '45 lake', '2241', '4a', '6a', '1975', 'lake suburban'], ['michigan city', 'michigan city', 'wolves', '46 laporte', '1919', '4a', '5a', '1995', 'none ( new school )'], ['portage', 'portage', 'indians', '64 porter', '2618', '4a', '6a', '1970', 'calumet'], ['valparaiso', 'valparaiso', 'vikings', '64 porter', '2072', '4a', '6a', '1970', 'independents']]

the apprentice australia

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24501530-1.html.csv

superlative

of the candidates on the apprentice australia , samuel sam hooper was the youngest .

{'scope': 'all', 'col_superlative': '4', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'age'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; age }'}, 'candidate'], 'result': 'samuel sam hooper', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; age } ; candidate }'}, 'samuel sam hooper'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; age } ; candidate } ; samuel sam hooper } = true', 'tointer': 'select the row whose age record of all rows is minimum . the candidate record of this row is samuel sam hooper .'}

eq { hop { argmin { all_rows ; age } ; candidate } ; samuel sam hooper } = true

select the row whose age record of all rows is minimum . the candidate record of this row is samuel sam hooper .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'age_5': 5, 'candidate_6': 6, 'samuel sam hooper_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'age_5': 'age', 'candidate_6': 'candidate', 'samuel sam hooper_7': 'samuel sam hooper'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'age_5': [0], 'candidate_6': [1], 'samuel sam hooper_7': [2]}

['candidate', 'background', 'original team', 'age', 'hometown', 'result']

[['andrew morello morello', 'auctioneer', 'pinnacle', '23', 'melbourne , victoria', 'hired by bouris'], ['heather williams', 'advertising sales consultant', 'eventus', '31', 'maylands , western australia', 'fired 2nd in finale'], ['gavin mcinnes', 'lawyer', 'pinnacle', '33', 'brisbane , queensland', 'fired 1st in finale'], ['mary - anne lowe', 'business owner', 'eventus', '30', 'melbourne , victoria', 'fired in week 9'], ['sabrina houssami', 'university student and miss world australia 2006', 'eventus', '23', 'sydney , new south wales', 'fired in week 8'], ['samuel sam hooper', 'law student', 'pinnacle', '19', 'adelaide , south australia', 'fired in week 7'], ['carmen parnos', 'bankrupt former entrepreneur', 'eventus', '44', 'melbourne , victoria', 'fired in week 6'], ['john van yzerloo', 'unemployed', 'pinnacle', '44', 'romsey , victoria', 'fired in week 5'], ['blake chandler', 'customer service manager', 'pinnacle', '28', 'central coast , new south wales', 'fired in week 4'], ['amy cato', 'business owner', 'eventus', '25', 'adelaide , south australia', 'fired in week 3'], ['lynton pipkorn', 'marketing consultant', 'pinnacle', '30', 'melbourne , victoria', 'fired in week 2']]

rizal

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-232458-1.html.csv

superlative

binangonan is the city of rizal that has the highest number of barangays .

{'scope': 'all', 'col_superlative': '2', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'no of barangays'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; no of barangays }'}, 'city / municipality'], 'result': 'binangonan', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; no of barangays } ; city / municipality }'}, 'binangonan'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; no of barangays } ; city / municipality } ; binangonan } = true', 'tointer': 'select the row whose no of barangays record of all rows is maximum . the city / municipality record of this row is binangonan .'}

eq { hop { argmax { all_rows ; no of barangays } ; city / municipality } ; binangonan } = true

select the row whose no of barangays record of all rows is maximum . the city / municipality record of this row is binangonan .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'no of barangays_5': 5, 'city / municipality_6': 6, 'binangonan_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'no of barangays_5': 'no of barangays', 'city / municipality_6': 'city / municipality', 'binangonan_7': 'binangonan'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'no of barangays_5': [0], 'city / municipality_6': [1], 'binangonan_7': [2]}

['city / municipality', 'no of barangays', 'area ( km square )', 'population ( 2010 census )', 'pop density ( per km square )']

[['angono', '10', '26.22', '102407', '3905.68'], ['antipolo', '16', '306.10', '677741', '2214.12'], ['baras', '10', '84.93', '32609', '383.95'], ['binangonan', '40', '66.34', '249872', '3766.54'], ['cainta', '7', '42.99', '311845', '7253.90'], ['cardona', '18', '28.56', '47414', '1660.15'], ['jalajala', '11', '44.12', '30074', '681.64'], ['morong', '8', '37.58', '52194', '1388.88'], ['pililla', '9', '69.95', '59527', '850.99'], ['rodriguez', '11', '312.70', '280904', '898.32'], ['san mateo', '15', '55.09', '205255', '3725.81'], ['tanay', '19', '200.00', '98879', '494.3'], ['taytay', '5', '38.80', '288956', '7447.32']]

2008 vanderbilt commodores baseball team

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15925327-4.html.csv

majority

all of the 2008 vanderbilt commodores baseball team games were played at the regions field location .

{'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'regions field', 'subset': None}

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

all_eq { all_rows ; location ; regions field } = true

for the location records of all rows , all of them fuzzily match to regions field .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location_3': 3, 'regions field_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location_3': 'location', 'regions field_4': 'regions field'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location_3': [0], 'regions field_4': [0]}

['date', 'opponent', 'location', 'score', 'loss', 'record']

[['may 21', 'florida', 'regions field', '7 - 3', 'keating ( 8 - 1 )', '38 - 18'], ['may 22', '13 lsu', 'regions field', '8 - 2', 'cotham ( 7 - 5 )', '38 - 19'], ['may 23', '23 south carolina', 'regions field', '7 - 5', 'cooper ( 5 - 6 )', '39 - 19'], ['may 24', 'ole miss', 'regions field', '7 - 4', 'mckean ( 4 - 1 )', '40 - 19'], ['may 24', 'ole miss', 'regions field', '8 - 7', 'hayes ( 2 - 1 )', '40 - 20']]

1926 vfl season

https://en.wikipedia.org/wiki/1926_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746808-1.html.csv

superlative

the match played at the brunswick street oval had the highest crowd of all the matches .

{'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '5', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'venue'], 'result': 'brunswick street oval', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; venue }'}, 'brunswick street oval'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; venue } ; brunswick street oval } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the venue record of this row is brunswick street oval .'}

eq { hop { argmax { all_rows ; crowd } ; venue } ; brunswick street oval } = true

select the row whose crowd record of all rows is maximum . the venue record of this row is brunswick street oval .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'venue_6': 6, 'brunswick street oval_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', 'venue_6': 'venue', 'brunswick street oval_7': 'brunswick street oval'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'venue_6': [1], 'brunswick street oval_7': [2]}

['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']

[['melbourne', '13.14 ( 92 )', 'st kilda', '8.15 ( 63 )', 'mcg', '18742', '1 may 1926'], ['essendon', '15.14 ( 104 )', 'north melbourne', '6.17 ( 53 )', 'windy hill', '15000', '1 may 1926'], ['south melbourne', '11.11 ( 77 )', 'richmond', '12.13 ( 85 )', 'lake oval', '20000', '1 may 1926'], ['geelong', '13.15 ( 93 )', 'footscray', '3.9 ( 27 )', 'corio oval', '15000', '1 may 1926'], ['fitzroy', '7.13 ( 55 )', 'collingwood', '14.10 ( 94 )', 'brunswick street oval', '25000', '1 may 1926'], ['hawthorn', '6.14 ( 50 )', 'carlton', '9.16 ( 70 )', 'glenferrie oval', '16000', '1 may 1926']]

scotland national rugby league team match results

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18304748-2.html.csv

superlative

gosford was the scotland national rugby league venue that drew the highest crowd attendance .

{'scope': 'all', 'col_superlative': '5', 'row_superlative': '15', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '4', '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 }'}, 'venue'], 'result': 'gosford', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; venue }'}, 'gosford'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; venue } ; gosford } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the venue record of this row is gosford .'}

eq { hop { argmax { all_rows ; attendance } ; venue } ; gosford } = true

select the row whose attendance record of all rows is maximum . the venue record of this row is gosford .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'venue_6': 6, 'gosford_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', 'venue_6': 'venue', 'gosford_7': 'gosford'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'venue_6': [1], 'gosford_7': [2]}

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

[['29 october 2000', 'scotland 16 - 17 new zealand māori', 'world cup', 'glasgow', '2000'], ['1 november 2000', 'ireland 18 - 6 scotland', 'world cup', 'dublin', '2000'], ['5 november 2000', 'scotland 12 - 20 samoa', 'world cup', 'edinburgh', '2000'], ['3 july 2001', 'france 24 - 40 scotland', 'friendly', 'lezignan', '3000'], ['26 october 2003', 'scotland 22 - 24 ireland', 'european nations cup', 'glasgow', '1000'], ['9 november 2003', 'france 6 - 8 scotland', 'european nations cup', 'narbonne', '2000'], ['24 october 2004', 'scotland 30 - 22 wales', 'european nations cup', 'glasgow', '1000'], ['29 october 2004', 'ireland 43 - 10 scotland', 'european nations cup', 'navan', '600'], ['16 october 2005', 'wales 22 - 14 scotland', 'european nations cup', 'bridgend', '1000'], ['23 october 2005', 'scotland 6 - 12 ireland', 'european nations cup', 'glasgow', '1000'], ['29 october 2006', 'wales 14 - 21 scotland', 'world cup qualification', 'bridgend', '2000'], ['27 october 2007', 'france 46 - 16 scotland', 'friendly', 'perpignan', '7000'], ['4 november 2007', 'scotland 16 - 18 wales', 'world cup qualification', 'glasgow', '1000'], ['26 october 2008', 'scotland 18 - 36 france', 'world cup', 'canberra', '9000'], ['5 november 2008', 'scotland 18 - 16 fiji', 'world cup', 'gosford', '10000'], ['8 november 2008', 'scotland 0 - 48 tonga', 'world cup', 'rockhampton', '6000'], ['17 october 2009', 'italy - 0 - 104 scotland', 'european nations cup', 'padova', '2139'], ['1 november 2009', 'scotland 22 - 10 lebanon', 'european nations cup', 'glasgow', '752'], ['8 november 2009', 'wales 28 - 16 scotland', 'european nations cup', 'bridgend', '1608']]

socialist destourian party

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13746866-2.html.csv

aggregation

the average number of deputies for the social destourian party was 114 .

{'scope': 'all', 'col': '5', 'type': 'average', 'result': '114', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'number of deputies'], 'result': '114', 'ind': 0, 'tostr': 'avg { all_rows ; number of deputies }'}, '114'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; number of deputies } ; 114 } = true', 'tointer': 'the average of the number of deputies record of all rows is 114 .'}

round_eq { avg { all_rows ; number of deputies } ; 114 } = true

the average of the number of deputies record of all rows is 114 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'number of deputies_4': 4, '114_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'number of deputies_4': 'number of deputies', '114_5': '114'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'number of deputies_4': [0], '114_5': [1]}

['election date', 'party leader', 'number of votes received', 'percentage of votes', 'number of deputies']

[['1964', 'habib bourguiba', '1255153', '100 %', '101'], ['1969', 'habib bourguiba', '1363939', '100 %', '101'], ['1974', 'habib bourguiba', '1570954', '100 %', '112'], ['1979', 'habib bourguiba', '1560753', '100 %', '121'], ['1981', 'habib bourguiba', '1828363', '94.2 %', '136']]

1969 italian grand prix

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122409-1.html.csv

unique

jack brabham was the only oil leak failure in the 1969 italian grand prix .

{'scope': 'all', 'row': '14', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'oil leak', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time / retired', 'oil leak'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time / retired record fuzzily matches to oil leak .', 'tostr': 'filter_eq { all_rows ; time / retired ; oil leak }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; time / retired ; oil leak } }', 'tointer': 'select the rows whose time / retired record fuzzily matches to oil leak . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time / retired', 'oil leak'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time / retired record fuzzily matches to oil leak .', 'tostr': 'filter_eq { all_rows ; time / retired ; oil leak }'}, 'driver'], 'result': 'jack brabham', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; time / retired ; oil leak } ; driver }'}, 'jack brabham'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; time / retired ; oil leak } ; driver } ; jack brabham }', 'tointer': 'the driver record of this unqiue row is jack brabham .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; time / retired ; oil leak } } ; eq { hop { filter_eq { all_rows ; time / retired ; oil leak } ; driver } ; jack brabham } } = true', 'tointer': 'select the rows whose time / retired record fuzzily matches to oil leak . there is only one such row in the table . the driver record of this unqiue row is jack brabham .'}

and { only { filter_eq { all_rows ; time / retired ; oil leak } } ; eq { hop { filter_eq { all_rows ; time / retired ; oil leak } ; driver } ; jack brabham } } = true

select the rows whose time / retired record fuzzily matches to oil leak . there is only one such row in the table . the driver record of this unqiue row is jack brabham .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'time / retired_7': 7, 'oil leak_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'jack brabham_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'time / retired_7': 'time / retired', 'oil leak_8': 'oil leak', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'jack brabham_10': 'jack brabham'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'time / retired_7': [0], 'oil leak_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'jack brabham_10': [3]}

['driver', 'constructor', 'laps', 'time / retired', 'grid']

[['jackie stewart', 'matra - ford', '68', '1:39:11.26', '3'], ['jochen rindt', 'lotus - ford', '68', '+ 0.08', '1'], ['jean - pierre beltoise', 'matra - ford', '68', '+ 0.17', '6'], ['bruce mclaren', 'mclaren - ford', '68', '+ 0.19', '5'], ['piers courage', 'brabham - ford', '68', '+ 33.44', '4'], ['pedro rodrã\xadguez', 'ferrari', '66', '+ 2 laps', '12'], ['denny hulme', 'mclaren - ford', '66', '+ 2 laps', '2'], ['jo siffert', 'lotus - ford', '64', 'engine', '8'], ['graham hill', 'lotus - ford', '63', 'halfshaft', '9'], ['jacky ickx', 'brabham - ford', '61', 'out of fuel', '15'], ['john surtees', 'brm', '60', 'not classified', '10'], ['jackie oliver', 'brm', '48', 'oil pressure', '11'], ['silvio moser', 'brabham - ford', '9', 'fuel leak', '13'], ['jack brabham', 'brabham - ford', '6', 'oil leak', '7'], ['john miles', 'lotus - ford', '3', 'engine', '14']]

world tourism rankings

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14752049-4.html.csv

aggregation

the ten top-ranked countries in world tourism had an average of 13.4 million tourist arrivals in 2012 .

{'scope': 'all', 'col': '3', 'type': 'average', 'result': '13.4 million', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'international tourist arrivals ( 2012 )'], 'result': '13.4 million', 'ind': 0, 'tostr': 'avg { all_rows ; international tourist arrivals ( 2012 ) }'}, '13.4 million'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; international tourist arrivals ( 2012 ) } ; 13.4 million } = true', 'tointer': 'the average of the international tourist arrivals ( 2012 ) record of all rows is 13.4 million .'}

round_eq { avg { all_rows ; international tourist arrivals ( 2012 ) } ; 13.4 million } = true

the average of the international tourist arrivals ( 2012 ) record of all rows is 13.4 million .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'international tourist arrivals (2012)_4': 4, '13.4 million_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'international tourist arrivals (2012)_4': 'international tourist arrivals ( 2012 )', '13.4 million_5': '13.4 million'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'international tourist arrivals (2012)_4': [0], '13.4 million_5': [1]}

['rank', 'country', 'international tourist arrivals ( 2012 )', 'international tourist arrivals ( 2011 )', 'change ( 2011 to 2012 )', 'change ( 2010 to 2011 )']

[['1', 'united states', '67.0 million', '62.7 million', '+ 6.8 %', '+ 4.9 %'], ['2', 'mexico', '23.4 million', '23.4 million', '+ 0.0 %', '+ 0.5 %'], ['3', 'canada', '16.3 million', '16.0 million', '+ 1.8 %', '- 1.3 %'], ['4', 'brazil', '5.6 million', '5.4 million', '+ 4.5 %', '+ 5.3 %'], ['5', 'argentina', '5.5 million', '5.7 million', '- 1.9 %', '+ 7.1 %'], ['6', 'dominican republic', '4.5 million', '4.3 million', '+ 5.9 %', '+ 4.4 %'], ['7', 'chile', '3.5 million', '3.1 million', '+ 13.3 %', '+ 12.0 %'], ['8', 'puerto rico', '3.0 million', '3.0 million', '+ 0.7 %', '- 4.3 %'], ['9', 'peru', '2.8 million', '2.5 million', '+ 9.5 %', '+ 13.0 %'], ['10', 'uruguay', '2.6 million', '2.8 million', '- 5.7 %', '+ 21.6 %']]

federal government college ikot ekpene

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11464746-1.html.csv

count

three of the houses of the federal government college ikot ekpene were founded after 1980 .

{'scope': 'all', 'criterion': 'greater_than_eq', 'value': '1980', 'result': '3', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'founded', '1980'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose founded record is greater than or equal to 1980 .', 'tostr': 'filter_greater_eq { all_rows ; founded ; 1980 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; founded ; 1980 } }', 'tointer': 'select the rows whose founded record is greater than or equal to 1980 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; founded ; 1980 } } ; 3 } = true', 'tointer': 'select the rows whose founded record is greater than or equal to 1980 . the number of such rows is 3 .'}

eq { count { filter_greater_eq { all_rows ; founded ; 1980 } } ; 3 } = true

select the rows whose founded record is greater than or equal to 1980 . the number of such rows is 3 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'founded_5': 5, '1980_6': 6, '3_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'founded_5': 'founded', '1980_6': '1980', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'founded_5': [0], '1980_6': [0], '3_7': [2]}

['house name', 'composition', 'named after', 'founded', 'colours']

[['benue', 'coed', 'river benue', '1973', 'yellow'], ['gongola', 'coed', 'gongola river', '1980', 'purple'], ['niger', 'coed', 'river niger', '1973', 'green'], ['rima', 'coed', 'rima river', '1980', 'brown'], ['ogun', 'coed', 'ogun river', '1980', 'blue'], ['cross', 'coed', 'cross river', '1976', 'red']]

atlanta falcons draft history

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15198842-20.html.csv

unique

micah moon was the only player the atlanta falcons drafted from north carolina college .

{'scope': 'all', 'row': '7', 'col': '6', 'col_other': '4', 'criterion': 'equal', 'value': 'north carolina', 'subset': None}

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

and { only { filter_eq { all_rows ; college ; north carolina } } ; eq { hop { filter_eq { all_rows ; college ; north carolina } ; name } ; micah moon } } = true

select the rows whose college record fuzzily matches to north carolina . there is only one such row in the table . the name record of this unqiue row is micah moon .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'college_7': 7, 'north carolina_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'micah moon_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', 'north carolina_8': 'north carolina', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'micah moon_10': 'micah moon'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'college_7': [0], 'north carolina_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'micah moon_10': [3]}

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

[['1', '2', '2', 'bill fralic', 'guard', 'pittsburgh'], ['2', '17', '45', 'mike gann', 'defensive end', 'notre dame'], ['4', '5', '89', 'emile harry', 'wide receiver', 'stanford'], ['6', '12', '152', 'reggie pleasant', 'defensive back', 'clemson'], ['8', '5', '201', 'ashley lee', 'defensive back', 'virginia tech'], ['8', '19', '215', 'ronnie washington', 'linebacker', 'northeast louisiana'], ['9', '4', '228', 'micah moon', 'linebacker', 'north carolina'], ['10', '5', '257', 'brent martin', 'center', 'stanford'], ['11', '4', '284', 'john ayres', 'defensive back', 'illinois'], ['12', '5', '313', 'ken whisenhunt', 'tight end', 'georgia tech']]

2007 tampa bay storm season

https://en.wikipedia.org/wiki/2007_Tampa_Bay_Storm_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11486671-4.html.csv

unique

torrance marshall was the only player to record 17 touchdowns in the 2007 tampa bay storm season .

{'scope': 'all', 'row': '1', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '17', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', "td 's", '17'], 'result': None, 'ind': 0, 'tointer': "select the rows whose td 's record is equal to 17 .", 'tostr': "filter_eq { all_rows ; td 's ; 17 }"}], 'result': True, 'ind': 1, 'tostr': "only { filter_eq { all_rows ; td 's ; 17 } }", 'tointer': "select the rows whose td 's record is equal to 17 . there is only one such row in the table ."}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', "td 's", '17'], 'result': None, 'ind': 0, 'tointer': "select the rows whose td 's record is equal to 17 .", 'tostr': "filter_eq { all_rows ; td 's ; 17 }"}, 'player name'], 'result': 'torrance marshall', 'ind': 2, 'tostr': "hop { filter_eq { all_rows ; td 's ; 17 } ; player name }"}, 'torrance marshall'], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; td 's ; 17 } ; player name } ; torrance marshall }", 'tointer': 'the player name record of this unqiue row is torrance marshall .'}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; td 's ; 17 } } ; eq { hop { filter_eq { all_rows ; td 's ; 17 } ; player name } ; torrance marshall } } = true", 'tointer': "select the rows whose td 's record is equal to 17 . there is only one such row in the table . the player name record of this unqiue row is torrance marshall ."}

and { only { filter_eq { all_rows ; td 's ; 17 } } ; eq { hop { filter_eq { all_rows ; td 's ; 17 } ; player name } ; torrance marshall } } = true

select the rows whose td 's record is equal to 17 . there is only one such row in the table . the player name record of this unqiue row is torrance marshall .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, "td 's_7": 7, '17_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player name_9': 9, 'torrance marshall_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', "td 's_7": "td 's", '17_8': '17', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player name_9': 'player name', 'torrance marshall_10': 'torrance marshall'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], "td 's_7": [0], '17_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player name_9': [2], 'torrance marshall_10': [3]}

['place', 'player name', 'yards', "td 's", 'long']

[['1', 'torrance marshall', '107', '17', '9'], ['2', 'rodney filer', '96', '9', '14'], ['3', 'marvin brown', '43', '1', '23'], ['4', 'tt toliver', '24', '0', '13'], ['5', 'john kaleo', '16', '1', '7'], ['6', 'brett dietz', '7', '2', '4'], ['7', 'stoney case', '4', '2', '3'], ['8', 'clenton crossley', '3', '0', '3'], ['9', 'rod williams', '1', '0', '1'], ['10', 'jarrod penright', '3', '0', '1']]

hong kong first division league

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1908877-2.html.csv

comparative

the blu chun rangers placed higher in the division in 2012 - 2013 than citizen .

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

{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'biu chun rangers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to biu chun rangers .', 'tostr': 'filter_eq { all_rows ; club ; biu chun rangers }'}, 'position in 2012 - 13'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club ; biu chun rangers } ; position in 2012 - 13 }', 'tointer': 'select the rows whose club record fuzzily matches to biu chun rangers . take the position in 2012 - 13 record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'citizen'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to citizen .', 'tostr': 'filter_eq { all_rows ; club ; citizen }'}, 'position in 2012 - 13'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; club ; citizen } ; position in 2012 - 13 }', 'tointer': 'select the rows whose club record fuzzily matches to citizen . take the position in 2012 - 13 record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; club ; biu chun rangers } ; position in 2012 - 13 } ; hop { filter_eq { all_rows ; club ; citizen } ; position in 2012 - 13 } } = true', 'tointer': 'select the rows whose club record fuzzily matches to biu chun rangers . take the position in 2012 - 13 record of this row . select the rows whose club record fuzzily matches to citizen . take the position in 2012 - 13 record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; club ; biu chun rangers } ; position in 2012 - 13 } ; hop { filter_eq { all_rows ; club ; citizen } ; position in 2012 - 13 } } = true

select the rows whose club record fuzzily matches to biu chun rangers . take the position in 2012 - 13 record of this row . select the rows whose club record fuzzily matches to citizen . take the position in 2012 - 13 record of this row . the first record is less than the second record .

5

5

{'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'club_7': 7, 'biu chun rangers_8': 8, 'position in 2012 - 13_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'club_11': 11, 'citizen_12': 12, 'position in 2012 - 13_13': 13}

{'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'club_7': 'club', 'biu chun rangers_8': 'biu chun rangers', 'position in 2012 - 13_9': 'position in 2012 - 13', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'club_11': 'club', 'citizen_12': 'citizen', 'position in 2012 - 13_13': 'position in 2012 - 13'}

{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'club_7': [0], 'biu chun rangers_8': [0], 'position in 2012 - 13_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'club_11': [1], 'citizen_12': [1], 'position in 2012 - 13_13': [3]}

['club', 'position in 2012 - 13', 'first season in top division', 'number of seasons in top division', 'first season of current spell in top division', 'top division titles', 'last top division title']

[['biu chun rangers', '6th', '1965 - 66', '35', '2012 - 13', '1', '1970 - 71'], ['citizen', '8th', '2004 - 05', '9', '2004 - 05', '0', 'n / a'], ['eastern salon', '3rd , second division', '1936 - 37', '59', '2013 - 14', '4', '1994 - 95'], ['happy valley', '2nd , second division', '1959 - 60', '48', '2013 - 14', '6', '2005 - 06'], ['kitchee', '2nd', '1947 - 48', '35', '2003 - 04', '5', '2011 - 12'], ['south china', '1st', '1918 - 19', '93', '1918 - 19', '41', '2012 - 13'], ['southern', '4th', '2011 - 12', '2', '2012 - 13', '0', 'n / a'], ['sun pegasus', '5th', '2008 - 09', '6', '2008 - 09', '0', 'n / a'], ['sunray cave jc sun hei', '7th', '1994 - 95', '20', '1994 - 95', '3', '2004 - 05'], ['tuen mun', '3rd', '2010 - 11', '4', '2010 - 11', '0', 'n / a'], ['yokohama fc hong kong', '9th', '2012 - 13', '2', '2012 - 13', '0', 'n / a']]

1995 u.s. open ( golf )

https://en.wikipedia.org/wiki/1995_U.S._Open_%28golf%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162214-2.html.csv

count

six of the players finished with a score of 69 .

{'scope': 'all', 'criterion': 'equal', 'value': '69', 'result': '6', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'score', '69'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record is equal to 69 .', 'tostr': 'filter_eq { all_rows ; score ; 69 }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; score ; 69 } }', 'tointer': 'select the rows whose score record is equal to 69 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; score ; 69 } } ; 6 } = true', 'tointer': 'select the rows whose score record is equal to 69 . the number of such rows is 6 .'}

eq { count { filter_eq { all_rows ; score ; 69 } } ; 6 } = true

select the rows whose score record is equal to 69 . the number of such rows is 6 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'score_5': 5, '69_6': 6, '6_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'score_5': 'score', '69_6': '69', '6_7': '6'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'score_5': [0], '69_6': [0], '6_7': [2]}

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

[['1', 'nick price', 'zimbabwe', '66', '- 4'], ['2', 'scott simpson', 'united states', '67', '- 3'], ['t3', 'phil mickelson', 'united states', '68', '- 2'], ['t3', 'greg norman', 'australia', '68', '- 2'], ['t5', 'bill glasson', 'united states', '69', '- 1'], ['t5', 'steve lowery', 'united states', '69', '- 1'], ['t5', 'jeff maggert', 'united states', '69', '- 1'], ['t5', 'masashi ozaki', 'japan', '69', '- 1'], ['t5', 'bob tway', 'united states', '69', '- 1'], ['t5', 'fuzzy zoeller', 'united states', '69', '- 1']]

list of locomotives in china

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10285177-5.html.csv

comparative

the top speed of the nd4 is 18 km/h less than the nd5 .

{'row_1': '4', 'row_2': '5', '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', 'model', 'nd4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose model record fuzzily matches to nd4 .', 'tostr': 'filter_eq { all_rows ; model ; nd4 }'}, 'top speed ( in operation ) （ km / h ）'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; model ; nd4 } ; top speed ( in operation ) （ km / h ） }', 'tointer': 'select the rows whose model record fuzzily matches to nd4 . take the top speed ( in operation ) （ km / h ） record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', 'nd5'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose model record fuzzily matches to nd5 .', 'tostr': 'filter_eq { all_rows ; model ; nd5 }'}, 'top speed ( in operation ) （ km / h ）'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; model ; nd5 } ; top speed ( in operation ) （ km / h ） }', 'tointer': 'select the rows whose model record fuzzily matches to nd5 . take the top speed ( in operation ) （ km / h ） record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; model ; nd4 } ; top speed ( in operation ) （ km / h ） } ; hop { filter_eq { all_rows ; model ; nd5 } ; top speed ( in operation ) （ km / h ） } } = true', 'tointer': 'select the rows whose model record fuzzily matches to nd4 . take the top speed ( in operation ) （ km / h ） record of this row . select the rows whose model record fuzzily matches to nd5 . take the top speed ( in operation ) （ km / h ） record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; model ; nd4 } ; top speed ( in operation ) （ km / h ） } ; hop { filter_eq { all_rows ; model ; nd5 } ; top speed ( in operation ) （ km / h ） } } = true

select the rows whose model record fuzzily matches to nd4 . take the top speed ( in operation ) （ km / h ） record of this row . select the rows whose model record fuzzily matches to nd5 . take the top speed ( in operation ) （ km / h ） 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, 'model_7': 7, 'nd4_8': 8, 'top speed (in operation) （km / h）_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'model_11': 11, 'nd5_12': 12, 'top speed (in operation) （km / h）_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', 'model_7': 'model', 'nd4_8': 'nd4', 'top speed (in operation) （km / h）_9': 'top speed ( in operation ) （ km / h ）', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'model_11': 'model', 'nd5_12': 'nd5', 'top speed (in operation) （km / h）_13': 'top speed ( in operation ) （ km / h ）'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'model_7': [0], 'nd4_8': [0], 'top speed (in operation) （km / h）_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'model_11': [1], 'nd5_12': [1], 'top speed (in operation) （km / h）_13': [3]}

['model', 'build year', 'transmission', 'top speed ( in operation ) （ km / h ）', 'power output （ kw ）', 'builder ( family )', 'total production']

[['nd1', '1958 ,1965', 'dc - dc', '80', '440', 'hungary ganz ( hungarian state railways class m44 )', '26'], ['nd2', '1972 - 1987', 'dc - dc', '120', '1280', 'electroputere , romania craiova ( cfr 060da )', '284'], ['nd3', '1985', 'dc - dc', '100', '1540', 'electroputere , romania craiova', '88'], ['nd4', '1973 - 1975', 'ac - dc', '100', '2150', 'alstom , france', '50'], ['nd5', '1984 － 1986', 'ac - dc', '118', '2550', 'ge , usa ( ge c36 - 7 )', '422'], ['nj2', '2005 - 2006', 'ac - dc - ac', '120', '3800', 'ge , usa', '78']]

atlantic city , new jersey

https://en.wikipedia.org/wiki/Atlantic_City%2C_New_Jersey

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-106211-1.html.csv

unique

the golden nugget is the only casino in atlantic city that has a gold rush era theme .

{'scope': 'all', 'row': '5', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'gold rush era', 'subset': None}

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

and { only { filter_eq { all_rows ; theme ; gold rush era } } ; eq { hop { filter_eq { all_rows ; theme ; gold rush era } ; casino } ; golden nugget } } = true

select the rows whose theme record fuzzily matches to gold rush era . there is only one such row in the table . the casino record of this unqiue row is golden nugget .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'theme_7': 7, 'gold rush era_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'casino_9': 9, 'golden nugget_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'theme_7': 'theme', 'gold rush era_8': 'gold rush era', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'casino_9': 'casino', 'golden nugget_10': 'golden nugget'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'theme_7': [0], 'gold rush era_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'casino_9': [2], 'golden nugget_10': [3]}

['casino', 'opening date', 'theme', 'hotel rooms', 'section of atlantic city']

[['atlantic club', 'december 12 , 1980', 'beach resort', '809', 'downbeach'], ["bally 's ᴮ", 'december 29 , 1979', 'modern', '1749', 'midtown'], ['borgata', 'july 2 , 2003', 'tuscany', '2767', 'marina'], ['caesars', 'june 26 , 1979', 'roman empire', '1141', 'midtown'], ['golden nugget', 'june 19 , 1985', 'gold rush era', '727', 'marina'], ["harrah 's", 'november 27 , 1980', 'marina waterfront', '2590', 'marina'], ['resorts', 'may 28 , 1978', 'roaring twenties', '942', 'uptown'], ['revel', 'april 2 , 2012', 'oceanfront', '1399', 'uptown'], ['showboat', 'april 2 , 1987', 'mardi gras', '1329', 'uptown'], ['tropicana', 'november 26 , 1981', 'old havana', '2078', 'downbeach'], ['trump plaza ᴬ', 'may 26 , 1984', 'luxury resort', '906', 'midtown'], ['taj mahal', 'april 2 , 1990', 'taj mahal', '2010', 'uptown']]

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

majority

pierce was the leading scorer most of the time during the season .

{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'pierce', 'subset': None}

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

most_eq { all_rows ; high points ; pierce } = true

for the high points records of all rows , most of them fuzzily match to pierce .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high points_3': 3, 'pierce_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high points_3': 'high points', 'pierce_4': 'pierce'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high points_3': [0], 'pierce_4': [0]}

['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']]

1935 in brazilian football

https://en.wikipedia.org/wiki/1935_in_Brazilian_football

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15358573-1.html.csv

count

three of the teams had at least twenty points .

{'scope': 'all', 'criterion': 'greater_than_eq', 'value': '20', 'result': '3', 'col': '3', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'points', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is greater than or equal to 20 .', 'tostr': 'filter_greater_eq { all_rows ; points ; 20 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; points ; 20 } }', 'tointer': 'select the rows whose points record is greater than or equal to 20 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; points ; 20 } } ; 3 } = true', 'tointer': 'select the rows whose points record is greater than or equal to 20 . the number of such rows is 3 .'}

eq { count { filter_greater_eq { all_rows ; points ; 20 } } ; 3 } = true

select the rows whose points record is greater than or equal to 20 . the number of such rows is 3 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'points_5': 5, '20_6': 6, '3_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'points_5': 'points', '20_6': '20', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'points_5': [0], '20_6': [0], '3_7': [2]}

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

[['1', 'portuguesa', '22', '14', '2', '2', '17', '48'], ['2', 'ypiranga - sp', '22', '14', '0', '3', '33', '17'], ['3', 'estudantes', '20', '14', '2', '3', '16', '31'], ['4', 'ec são caetano', '16', '14', '2', '5', '31', '- 2'], ['5', 'sírio libanês', '12', '12', '2', '5', '31', '- 9'], ['6', 'jardim américa', '7', '13', '1', '9', '39', '- 16'], ['7', 'humberto primo', '7', '14', '1', '10', '48', '- 28'], ['8', 'ordem e progresso', '2', '13', '0', '12', '54', '- 41']]

lara gut

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15556757-2.html.csv

superlative

the earliest race for lara gut happened on february 2nd , in the year 2008 .

{'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': 'n/a', 'subset': None}

{'func': 'eq', 'args': [{'func': 'min', 'args': ['all_rows', 'date'], 'result': '2 feb 2008', 'ind': 0, 'tostr': 'min { all_rows ; date }', 'tointer': 'the minimum date record of all rows is 2 feb 2008 .'}, '2 feb 2008'], 'result': True, 'ind': 1, 'tostr': 'eq { min { all_rows ; date } ; 2 feb 2008 } = true', 'tointer': 'the minimum date record of all rows is 2 feb 2008 .'}

eq { min { all_rows ; date } ; 2 feb 2008 } = true

the minimum date record of all rows is 2 feb 2008 .

2

2

{'eq_1': 1, 'result_2': 2, 'min_0': 0, 'all_rows_3': 3, 'date_4': 4, '2 feb 2008_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'min_0': 'min', 'all_rows_3': 'all_rows', 'date_4': 'date', '2 feb 2008_5': '2 feb 2008'}

{'eq_1': [2], 'result_2': [], 'min_0': [1], 'all_rows_3': [0], 'date_4': [0], '2 feb 2008_5': [1]}

['season', 'date', 'location', 'race', 'place']

[['2008', '2 feb 2008', 'st moritz , switzerland', 'downhill', '3rd'], ['2009', '20 dec 2008', 'st moritz , switzerland', 'super - g', '1st'], ['2009', '28 dec 2008', 'semmering , austria', 'giant slalom', '3rd'], ['2011', '18 dec 2010', "val d'isère , france", 'downhill', '3rd'], ['2011', '9 jan 2011', 'altenmarkt - zauchensee , austria', 'super - g', '1st'], ['2011', '23 jan 2011', "cortina d'ampezzo , italy", 'super - g', '3rd'], ['2011', '16 mar 2011', 'lenzerheide , switzerland', 'downhill', '2nd'], ['2013', '14 dec 2012', "val - d'isère , france", 'downhill', '1st'], ['2013', '17 mar 2013', 'lenzerheide , switzerland', 'giant slalom', '3rd'], ['2014', '26 oct 2013', 'sölden , austria', 'giant slalom', '1st']]

list of white collar episodes

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24319661-5.html.csv

superlative

identity crisis drew the highest us viewership of the season .

{'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'us viewers ( million )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( million ) }'}, 'title'], 'result': 'identity crisis', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us viewers ( million ) } ; title }'}, 'identity crisis'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( million ) } ; title } ; identity crisis } = true', 'tointer': 'select the row whose us viewers ( million ) record of all rows is maximum . the title record of this row is identity crisis .'}

eq { hop { argmax { all_rows ; us viewers ( million ) } ; title } ; identity crisis } = true

select the row whose us viewers ( million ) record of all rows is maximum . the title record of this row is identity crisis .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'us viewers (million)_5': 5, 'title_6': 6, 'identity crisis_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'us viewers (million)_5': 'us viewers ( million )', 'title_6': 'title', 'identity crisis_7': 'identity crisis'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'us viewers (million)_5': [0], 'title_6': [1], 'identity crisis_7': [2]}

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

[['47', '1', 'wanted', 'paul holahan', 'jeff eastin', '3.21', 'july 10 , 2012', 'bcw401'], ['48', '2', 'most wanted', 'paul holahan', 'mark goffman', '2.98', 'july 17 , 2012', 'bcw402'], ['49', '3', 'diminishing returns', 'stefan schwartz', 'jim campolongo', '3.01', 'july 24 , 2012', 'bcw403'], ['50', '4', 'parting shots', 'robert duncan mcneill', 'alexandra mcnally', '2.82', 'july 31 , 2012', 'bcw404'], ['51', '5', 'honor among thieves', 'arlene sanford', 'joe henderson', '2.93', 'august 14 , 2012', 'bcw405'], ['52', '6', 'identity crisis', 'david straiton', 'channing powell', '3.89', 'august 21 , 2012', 'bcw406'], ['53', '7', 'compromising positions', 'paul holahan', 'matthew negrete', '3.36', 'august 28 , 2012', 'bcw407'], ['54', '8', 'ancient history', 'russell lee fine', 'daniel shattuck', '3.38', 'september 4 , 2012', 'bcw408'], ['55', '9', 'gloves off', 'renny harlin', 'mark goffman', '3.80', 'september 11 , 2012', 'bcw409'], ['56', '10', 'vested interest', 'russell lee fine', 'jeff eastin', '3.41', 'september 18 , 2012', 'bcw410'], ['57', '11', 'family business', 'paul holahan', 'joe henderson', '2.77', 'january 22 , 2013', 'bcw411'], ['58', '12', 'brass tacks', 'anton cropper', 'jim campolongo & alexandra mcnally', '2.61', 'january 29 , 2013', 'bcw412'], ['59', '13', 'empire city', 'tim dekay', 'channing powell & daniel shattuck', '2.28', 'february 5 , 2013', 'bcw413'], ['60', '14', 'shoot the moon', 'russell lee fine', 'matthew negrete & bob derosa', '2.42', 'february 19 , 2013', 'bcw414'], ['61', '15', 'the original', 'john kretchmer', 'mark goffman', '2.12', 'february 26 , 2013', 'bcw415']]

anwar robinson

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1620672-1.html.csv

majority

the majority of anwar robin 's song performances resulted in being safe .

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

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

most_eq { all_rows ; result ; safe } = true

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

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'safe_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'safe_4': 'safe'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'safe_4': [0]}

['week', 'theme', 'song choice', 'original artist', 'result']

[['top 24 ( 12 men )', "contestant 's choice", 'moon river', 'andy williams', 'safe'], ['top 20 ( 10 men )', "contestant 's choice", "what 's going on", 'marvin gaye', 'safe'], ['top 16 ( 8 men )', "contestant 's choice", 'what a wonderful world', 'louis armstrong', 'safe'], ['top 12', '1960s', 'a house is not a home', 'dionne warwick', 'safe'], ['top 11', 'billboard number ones', "ai n't nobody", 'chaka khan', 'safe'], ['top 10', '1990s', 'i believe i can fly', 'r kelly', 'bottom 2'], ['top 9', 'classic broadway', 'if ever i would leave you', 'from camelot', 'safe'], ['top 8', 'songs from birth year', "i 'll never love this way again", 'dionne warwick', 'safe'], ['top 7', '1970s dance music', 'september', 'earth , wind & fire', 'eliminated']]

list of countries by intentional homicide rate by decade

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18940307-6.html.csv

comparative

in 1951 the intentional homicide rate per 100,000 inhabitants was higher in japan than in scotland .

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

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'japan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to japan .', 'tostr': 'filter_eq { all_rows ; country ; japan }'}, '1951'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; japan } ; 1951 }', 'tointer': 'select the rows whose country record fuzzily matches to japan . take the 1951 record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'scotland'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to scotland .', 'tostr': 'filter_eq { all_rows ; country ; scotland }'}, '1951'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; country ; scotland } ; 1951 }', 'tointer': 'select the rows whose country record fuzzily matches to scotland . take the 1951 record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; country ; japan } ; 1951 } ; hop { filter_eq { all_rows ; country ; scotland } ; 1951 } } = true', 'tointer': 'select the rows whose country record fuzzily matches to japan . take the 1951 record of this row . select the rows whose country record fuzzily matches to scotland . take the 1951 record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; country ; japan } ; 1951 } ; hop { filter_eq { all_rows ; country ; scotland } ; 1951 } } = true

select the rows whose country record fuzzily matches to japan . take the 1951 record of this row . select the rows whose country record fuzzily matches to scotland . take the 1951 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, 'country_7': 7, 'japan_8': 8, '1951_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'country_11': 11, 'scotland_12': 12, '1951_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', 'country_7': 'country', 'japan_8': 'japan', '1951_9': '1951', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'country_11': 'country', 'scotland_12': 'scotland', '1951_13': '1951'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'country_7': [0], 'japan_8': [0], '1951_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'country_11': [1], 'scotland_12': [1], '1951_13': [3]}

['country', '1951', '1952', '1953', '1954', '1955', '1956', '1957', '1958', '1959']

[['united states', '4.4', '4.6', '4.5', '4.2', '4.1', '4.1', '4.0', '4.8', '4.9'], ['japan', '3.39', '3.35', '3.38', '3.49', '3.40', '2.90', '2.78', '2.92', '2.90'], ['scotland', '0.41', '0.53', '0.80', '0.63', '0.68', '0.57', '0.51', '0.82', '0.66'], ['england , wales', '0.75', '0.91', '0.74', '0.70', '0.63', '0.71', '0.71', '0.58', '0.59'], ['northern ireland', '0.00', '0.22', '0.36', '0.50', '0.21', '0.21', '0.29', '0.50', '0.00']]

1998 major league baseball draft

https://en.wikipedia.org/wiki/1998_Major_League_Baseball_Draft

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18468611-2.html.csv

unique

jeff winchester was the only player who played at the position of c.

{'scope': 'all', 'row': '10', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'c', 'subset': None}

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

and { only { filter_eq { all_rows ; position ; c } } ; eq { hop { filter_eq { all_rows ; position ; c } ; player } ; jeff winchester } } = true

select the rows whose position record fuzzily matches to c . there is only one such row in the table . the player record of this unqiue row is jeff winchester .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'c_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'jeff winchester_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'c_8': 'c', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'jeff winchester_10': 'jeff winchester'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'c_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'jeff winchester_10': [3]}

['pick', 'player', 'team', 'position', 'school']

[['31', 'chris george', 'kansas city royals', 'p', 'klein hs ( klein , tx )'], ['32', 'ben diggins', 'st louis cardinals', 'p', 'bradshaw mountain hs ( prescott valley , az )'], ['33', 'brad wilkerson', 'montreal expos', 'of', 'university of florida'], ['34', 'nate cornejo', 'detroit tigers', 'p', 'wellington hs ( wellington , ks )'], ['35', 'aaron rowand', 'chicago white sox', 'of', 'cal state fullerton university'], ['36', 'raphael freeman', 'colorado rockies', 'of', 'dallas christian school ( mesquite , tx )'], ['37', 'mike nannini', 'houston astros', 'p', 'green valley hs ( henderson , nv )'], ['38', 'chris jones', 'san francisco giants', 'p', 'south mecklenburg hs ( charlotte , nc )'], ['39', 'mamon tucker', 'baltimore orioles', 'of', 'stephen f austin hs ( austin , tx )'], ['40', 'jeff winchester', 'colorado rockies', 'c', 'archbishop rummel hs ( metairie , la )'], ['41', 'jeff urban', 'san francisco giants', 'p', 'ball state university'], ['42', 'eric valent', 'philadelphia phillies', 'of', 'ucla'], ['43', 'mark prior', 'new york yankees', 'p', 'university hs ( san diego , ca )']]

2006 toronto argonauts season

https://en.wikipedia.org/wiki/2006_Toronto_Argonauts_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20649850-1.html.csv

comparative

in the 2006 toronto argonauts season , leron mitchell was picked 4 picks before aaron wagner .

{'row_1': '2', 'row_2': '3', 'col': '1', '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', 'player', 'leron mitchell'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to leron mitchell .', 'tostr': 'filter_eq { all_rows ; player ; leron mitchell }'}, 'pick'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; leron mitchell } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to leron mitchell . take the pick record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'aaron wagner'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to aaron wagner .', 'tostr': 'filter_eq { all_rows ; player ; aaron wagner }'}, 'pick'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; aaron wagner } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to aaron wagner . take the pick record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; leron mitchell } ; pick } ; hop { filter_eq { all_rows ; player ; aaron wagner } ; pick } } = true', 'tointer': 'select the rows whose player record fuzzily matches to leron mitchell . take the pick record of this row . select the rows whose player record fuzzily matches to aaron wagner . take the pick record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; player ; leron mitchell } ; pick } ; hop { filter_eq { all_rows ; player ; aaron wagner } ; pick } } = true

select the rows whose player record fuzzily matches to leron mitchell . take the pick record of this row . select the rows whose player record fuzzily matches to aaron wagner . take the pick 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, 'player_7': 7, 'leron mitchell_8': 8, 'pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'aaron wagner_12': 12, 'pick_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', 'player_7': 'player', 'leron mitchell_8': 'leron mitchell', 'pick_9': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'aaron wagner_12': 'aaron wagner', 'pick_13': 'pick'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'leron mitchell_8': [0], 'pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'aaron wagner_12': [1], 'pick_13': [3]}

['pick', 'cfl team', 'player', 'position', 'college']

[['5', 'toronto argonauts', 'daniel federkeil', 'dl', 'calgary'], ['10', 'toronto argonauts', 'leron mitchell', 'db', 'western ontario'], ['14', 'toronto argonauts', 'aaron wagner', 'lb', 'brigham young'], ['31', 'toronto argonauts', 'obed cetoute', 'wr', 'central florida'], ['39', 'toronto argonauts', 'brian ramsay', 'ol', 'new mexico']]

test matches ( 1991 - 2000 )

https://en.wikipedia.org/wiki/Test_matches_%281991%E2%80%932000%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12410929-7.html.csv

unique

england was the only team to win a match by runs .

{'scope': 'all', 'row': '1', 'col': '5', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'runs', 'subset': None}

{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'runs'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to runs .', 'tostr': 'filter_eq { all_rows ; result ; runs }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; runs } } = true', 'tointer': 'select the rows whose result record fuzzily matches to runs . there is only one such row in the table .'}

only { filter_eq { all_rows ; result ; runs } } = true

select the rows whose result record fuzzily matches to runs . there is only one such row in the table .

2

2

{'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'result_4': 4, 'runs_5': 5}

{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'result_4': 'result', 'runs_5': 'runs'}

{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'result_4': [0], 'runs_5': [0]}

['date', 'home captain', 'away captain', 'venue', 'result']

[['6 , 7 , 8 , 9 , 10 june 1991', 'graham gooch', 'viv richards', 'headingley', 'eng by 115 runs'], ['20 , 21 , 22 , 23 , 24 june 1991', 'graham gooch', 'viv richards', "lord 's", 'draw'], ['4 , 5 , 6 , 8 , 9 july 1991', 'graham gooch', 'viv richards', 'trent bridge', 'wi by 9 wkts'], ['25 , 26 , 27 , 28 july 1991', 'graham gooch', 'viv richards', 'edgbaston', 'wi by 7 wkts'], ['8 , 9 , 10 , 11 , 12 august 1991', 'graham gooch', 'viv richards', 'the oval', 'eng by 5 wkts']]

wru division two west

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12828723-2.html.csv

unique

in wru division two west , when the points is over 60 , the only time the tries for was under 60 was when the club was when the club was kidwelly rfc .

{'scope': 'subset', 'row': '4', 'col': '7', 'col_other': '1', 'criterion': 'less_than', 'value': '60', 'subset': {'col': '11', 'criterion': 'greater_than', 'value': '60'}}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'points', '60'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; points ; 60 }', 'tointer': 'select the rows whose points record is greater than 60 .'}, 'tries for', '60'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose points record is greater than 60 . among these rows , select the rows whose tries for record is less than 60 .', 'tostr': 'filter_less { filter_greater { all_rows ; points ; 60 } ; tries for ; 60 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_less { filter_greater { all_rows ; points ; 60 } ; tries for ; 60 } }', 'tointer': 'select the rows whose points record is greater than 60 . among these rows , select the rows whose tries for record is less than 60 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'points', '60'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; points ; 60 }', 'tointer': 'select the rows whose points record is greater than 60 .'}, 'tries for', '60'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose points record is greater than 60 . among these rows , select the rows whose tries for record is less than 60 .', 'tostr': 'filter_less { filter_greater { all_rows ; points ; 60 } ; tries for ; 60 }'}, 'club'], 'result': 'kidwelly rfc', 'ind': 3, 'tostr': 'hop { filter_less { filter_greater { all_rows ; points ; 60 } ; tries for ; 60 } ; club }'}, 'kidwelly rfc'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_less { filter_greater { all_rows ; points ; 60 } ; tries for ; 60 } ; club } ; kidwelly rfc }', 'tointer': 'the club record of this unqiue row is kidwelly rfc .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_less { filter_greater { all_rows ; points ; 60 } ; tries for ; 60 } } ; eq { hop { filter_less { filter_greater { all_rows ; points ; 60 } ; tries for ; 60 } ; club } ; kidwelly rfc } } = true', 'tointer': 'select the rows whose points record is greater than 60 . among these rows , select the rows whose tries for record is less than 60 . there is only one such row in the table . the club record of this unqiue row is kidwelly rfc .'}

and { only { filter_less { filter_greater { all_rows ; points ; 60 } ; tries for ; 60 } } ; eq { hop { filter_less { filter_greater { all_rows ; points ; 60 } ; tries for ; 60 } ; club } ; kidwelly rfc } } = true

select the rows whose points record is greater than 60 . among these rows , select the rows whose tries for record is less than 60 . there is only one such row in the table . the club record of this unqiue row is kidwelly rfc .

8

6

{'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_less_1': 1, 'filter_greater_0': 0, 'all_rows_7': 7, 'points_8': 8, '60_9': 9, 'tries for_10': 10, '60_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'club_12': 12, 'kidwelly rfc_13': 13}

{'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_less_1': 'filter_less', 'filter_greater_0': 'filter_greater', 'all_rows_7': 'all_rows', 'points_8': 'points', '60_9': '60', 'tries for_10': 'tries for', '60_11': '60', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'club_12': 'club', 'kidwelly rfc_13': 'kidwelly rfc'}

{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_less_1': [2, 3], 'filter_greater_0': [1], 'all_rows_7': [0], 'points_8': [0], '60_9': [0], 'tries for_10': [1], '60_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'club_12': [3], 'kidwelly rfc_13': [4]}

['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'], ['ammanford rfc', '22', '0', '2', '751', '373', '100', '40', '15', '1', '96'], ['tondu rfc', '22', '1', '5', '599', '441', '84', '60', '10', '1', '77'], ['kidwelly rfc', '22', '0', '9', '477', '439', '53', '47', '7', '5', '64'], ['builth wells rfc', '22', '0', '10', '476', '388', '60', '38', '7', '7', '62'], ['loughor rfc', '22', '1', '9', '548', '529', '63', '69', '6', '3', '59'], ['cwmllynfell rfc', '22', '1', '10', '553', '603', '69', '74', '9', '4', '59'], ['aberystwyth rfc', '22', '0', '11', '510', '541', '60', '74', '7', '1', '52'], ['skewen rfc', '22', '1', '10', '443', '413', '58', '51', '4', '2', '52'], ['aberavon quins rfc', '22', '2', '13', '454', '480', '64', '57', '9', '6', '47'], ['newcastle emlyn rfc', '22', '1', '15', '487', '634', '55', '80', '7', '5', '38'], ['bp ( llandarcy ) rfc', '22', '3', '15', '324', '461', '34', '53', '2', '7', '31'], ['pontyberem rfc', '22', '0', '18', '330', '650', '34', '91', '2', '7', '25']]

united states house of representatives elections , 1946

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1946

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342233-17.html.csv

majority

all of the kentucky incumbents in the us house of representatives '46 elections were democratic .

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

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

all_eq { all_rows ; party ; democratic } = true

for the party records of all rows , all of them fuzzily match to democratic .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]}

['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']

[['kentucky 4', 'frank chelf', 'democratic', '1944', 're - elected', 'frank chelf ( d ) 53.1 % don victor drye ( r ) 46.9 %'], ['kentucky 5', 'brent spence', 'democratic', '1930', 're - elected', 'brent spence ( d ) 51.2 % marion w moore ( r ) 48.8 %'], ['kentucky 6', 'virgil chapman', 'democratic', '1930', 're - elected', 'virgil chapman ( d ) 55.0 % w d rogers ( r ) 45.0 %'], ['kentucky 7', 'andrew j may', 'democratic', '1930', 'lost re - election republican gain', 'w howes meade ( r ) 59.3 % andrew j may ( d ) 40.7 %'], ['kentucky 8', 'joe b bates', 'democratic', '1930', 're - elected', 'joe b bates ( d ) 52.6 % ray schmauch ( r ) 47.4 %']]

list of a1 grand prix seasons

https://en.wikipedia.org/wiki/List_of_A1_Grand_Prix_seasons

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12868148-2.html.csv

unique

the 2009-10 season was the only season to be cancelled .

{'scope': 'all', 'row': '5', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'season cancelled', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'season cancelled'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to season cancelled .', 'tostr': 'filter_eq { all_rows ; team ; season cancelled }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; team ; season cancelled } }', 'tointer': 'select the rows whose team record fuzzily matches to season cancelled . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'season cancelled'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to season cancelled .', 'tostr': 'filter_eq { all_rows ; team ; season cancelled }'}, 'season'], 'result': '2009 - 10', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; season cancelled } ; season }'}, '2009 - 10'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; team ; season cancelled } ; season } ; 2009 - 10 }', 'tointer': 'the season record of this unqiue row is 2009 - 10 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; team ; season cancelled } } ; eq { hop { filter_eq { all_rows ; team ; season cancelled } ; season } ; 2009 - 10 } } = true', 'tointer': 'select the rows whose team record fuzzily matches to season cancelled . there is only one such row in the table . the season record of this unqiue row is 2009 - 10 .'}

and { only { filter_eq { all_rows ; team ; season cancelled } } ; eq { hop { filter_eq { all_rows ; team ; season cancelled } ; season } ; 2009 - 10 } } = true

select the rows whose team record fuzzily matches to season cancelled . there is only one such row in the table . the season record of this unqiue row is 2009 - 10 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team_7': 7, 'season cancelled_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'season_9': 9, '2009 - 10_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team_7': 'team', 'season cancelled_8': 'season cancelled', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'season_9': 'season', '2009 - 10_10': '2009 - 10'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'team_7': [0], 'season cancelled_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'season_9': [2], '2009 - 10_10': [3]}

['season', 'team', 'racing team', 'chassis', 'engine', 'tyres', 'drivers', 'wins', 'sprints wins', 'main wins', 'poles', 'fastest laps', 'points']

[['2005 - 06', 'france', 'dams', 'lola', 'zytek', 'cooper avon', 'alexandre prémat nicolas lapierre', '13', '7', '6', '4', '5', '172'], ['2006 - 07', 'germany', 'super nova racing', 'lola', 'zytek', 'cooper avon', 'nico hülkenberg christian vietoris', '9', '3', '6', '3', '3', '128'], ['2007 - 08', 'switzerland', 'max motorsport consulting', 'lola', 'zytek', 'cooper avon', 'neel jani', '4', '2', '2', '5', '5', '168'], ['2008 - 09', 'ireland', 'status grand prix', 'a1 gp', 'ferrari', 'michelin', 'adam carroll', '5', '3', '2', '6', '5', '112'], ['2009 - 10', 'season cancelled', 'season cancelled', 'season cancelled', 'season cancelled', 'season cancelled', 'season cancelled', 'season cancelled', 'season cancelled', 'season cancelled', 'season cancelled', 'season cancelled', 'season cancelled']]

estonia in the eurovision song contest 2002

https://en.wikipedia.org/wiki/Estonia_in_the_Eurovision_Song_Contest_2002

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12676284-1.html.csv

superlative

for estonians in the eurovision song contest in 2002 , the artist with the highest number of votes is sahlene .

{'scope': 'all', 'col_superlative': '4', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'votes'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; votes }'}, 'artist'], 'result': 'sahlene', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; votes } ; artist }'}, 'sahlene'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; votes } ; artist } ; sahlene } = true', 'tointer': 'select the row whose votes record of all rows is maximum . the artist record of this row is sahlene .'}

eq { hop { argmax { all_rows ; votes } ; artist } ; sahlene } = true

select the row whose votes record of all rows is maximum . the artist record of this row is sahlene .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'votes_5': 5, 'artist_6': 6, 'sahlene_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'votes_5': 'votes', 'artist_6': 'artist', 'sahlene_7': 'sahlene'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'votes_5': [0], 'artist_6': [1], 'sahlene_7': [2]}

['draw', 'artist', 'song', 'votes', 'place']

[['1', 'jaanika vilipo', "i 'm falling", '49', '5'], ['2', 'yvetta kadakas & ivo linna', 'computer love', '14', '10'], ['3', 'maarja kivi', 'a dream', '38', '7'], ['4', 'lea liitmaa & jaagup kreem', 'what if i fell', '31', '9'], ['5', 'gerli padar', 'need a little nothing', '60', '3'], ['6', 'hatuna & riina riistop', 'this is ( what luv can do )', '32', '8'], ['7', 'maarja tãµkke', "i 'll never forget", '51', '4'], ['8', 'nightlight duo & cowboys', 'another country song', '65', '2'], ['9', 'sahlene', 'runaway', '85', '1'], ['10', 'julia hillens', "u ca n't", '39', '6']]

gymnastics at the 2008 summer olympics - men 's horizontal bar

https://en.wikipedia.org/wiki/Gymnastics_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_horizontal_bar

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662022-2.html.csv

count

in the men 's horizontal bar competition at the 2008 summer olympics , two of the players with an ' a score ' over 7 had a ' b score ' under 9 .

{'scope': 'subset', 'criterion': 'less_than', 'value': '9', 'result': '1', 'col': '4', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '7'}}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'a score', '7'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; a score ; 7 }', 'tointer': 'select the rows whose a score record is greater than 7 .'}, 'b score', '9'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose a score record is greater than 7 . among these rows , select the rows whose b score record is less than 9 .', 'tostr': 'filter_less { filter_greater { all_rows ; a score ; 7 } ; b score ; 9 }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_less { filter_greater { all_rows ; a score ; 7 } ; b score ; 9 } }', 'tointer': 'select the rows whose a score record is greater than 7 . among these rows , select the rows whose b score record is less than 9 . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_greater { all_rows ; a score ; 7 } ; b score ; 9 } } ; 1 } = true', 'tointer': 'select the rows whose a score record is greater than 7 . among these rows , select the rows whose b score record is less than 9 . the number of such rows is 1 .'}

eq { count { filter_less { filter_greater { all_rows ; a score ; 7 } ; b score ; 9 } } ; 1 } = true

select the rows whose a score record is greater than 7 . among these rows , select the rows whose b score record is less than 9 . the number of such rows is 1 .

4

4

{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'a score_6': 6, '7_7': 7, 'b score_8': 8, '9_9': 9, '1_10': 10}

{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'a score_6': 'a score', '7_7': '7', 'b score_8': 'b score', '9_9': '9', '1_10': '1'}

{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'a score_6': [0], '7_7': [0], 'b score_8': [1], '9_9': [1], '1_10': [3]}

['position', 'gymnast', 'a score', 'b score', 'total']

[['1st', 'fabian hambã ¼ chen ( ger )', '7.000', '9.200', '16.200'], ['2nd', 'igor cassina ( ita )', '6.800', '9.200', '16.000'], ['3rd', 'yann cucherat ( fra )', '6.900', '8.950', '15.850'], ['4th', 'epke zonderland ( ned )', '7.100', '8.650', '15.750'], ['5th', 'zou kai ( chn )', '7.000', '8.600', '15.600'], ['6th', 'jonathan horton ( usa )', '6.400', '9.175', '15.575'], ['7th', 'hiroyuki tomita ( jpn )', '6.600', '8.950', '15.550'], ['8th', 'takuya nakase ( jpn )', '6.600', '8.850', '15.450']]

texas world speedway

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1405704-1.html.csv

majority

most of the winning cars had tires made by goodyear .

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

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

most_eq { all_rows ; tires ; goodyear } = true

for the tires records of all rows , most of them fuzzily match to goodyear .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'tires_3': 3, 'goodyear_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'tires_3': 'tires', 'goodyear_4': 'goodyear'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'tires_3': [0], 'goodyear_4': [0]}

['season', 'race name', 'winning driver', 'chassis', 'engine', 'tires', 'team']

[['1973', 'texas 200', 'al unser', 'parnelli', 'offenhauser', 'firestone', 'vels parnelli jones'], ['1976', 'texas 150', 'aj foyt', 'coyote', 'foyt', 'goodyear', 'gilmore racing'], ['1976', 'benihana world series of auto racing', 'johnny rutherford', 'mclaren', 'offenhauser', 'goodyear', 'team mclaren'], ['1977', 'texas grand prix', 'tom sneva', 'mclaren', 'cosworth', 'goodyear', 'team penske'], ['1977', 'american parts 200', 'johnny rutherford', 'mclaren', 'cosworth', 'goodyear', 'team mclaren'], ['1978', 'coors 200', 'danny ongais', 'parnelli', 'cosworth', 'goodyear', 'interscope racing'], ['1978', 'texas grand prix', 'aj foyt', 'coyote', 'foyt', 'goodyear', 'gilmore racing'], ['1979', 'coors 200', 'aj foyt', 'coyote', 'foyt', 'goodyear', 'gilmore racing'], ['1979', 'lubriloln grand prix', 'aj foyt', 'parnelli', 'cosworth', 'goodyear', 'gilmore racing']]

1924 in brazilian football

https://en.wikipedia.org/wiki/1924_in_Brazilian_football

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15387537-1.html.csv

aggregation

winners of brazilian football that were in 1st through 5th place scored an average of 22 points .

{'scope': 'subset', 'col': '3', 'type': 'average', 'result': '22', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '5'}}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'position', '5'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; position ; 5 }', 'tointer': 'select the rows whose position record is less than or equal to 5 .'}, 'points'], 'result': '22', 'ind': 1, 'tostr': 'avg { filter_less_eq { all_rows ; position ; 5 } ; points }'}, '22'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_less_eq { all_rows ; position ; 5 } ; points } ; 22 } = true', 'tointer': 'select the rows whose position record is less than or equal to 5 . the average of the points record of these rows is 22 .'}

round_eq { avg { filter_less_eq { all_rows ; position ; 5 } ; points } ; 22 } = true

select the rows whose position record is less than or equal to 5 . the average of the points record of these rows is 22 .

3

3

{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, '5_6': 6, 'points_7': 7, '22_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', '5_6': '5', 'points_7': 'points', '22_8': '22'}

{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], '5_6': [0], 'points_7': [1], '22_8': [2]}

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

[['1', 'corinthians', '25', '17', '1', '4', '23', '23'], ['2', 'paulistano', '23', '17', '3', '4', '15', '16'], ['3', 'aa são bento', '22', '17', '4', '4', '20', '10'], ['4', 'santos', '21', '17', '3', '5', '29', '15'], ['5', 'ypiranga - sp', '20', '17', '2', '6', '24', '5'], ['6', 'sírio', '17', '17', '5', '6', '26', '3'], ['7', 'brás', '10', '16', '4', '9', '41', '- 17'], ['8', 'portuguesa', '8', '16', '2', '11', '39', '- 21']]

césar cielo

https://en.wikipedia.org/wiki/C%C3%A9sar_Cielo

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12627202-1.html.csv

unique

the only event where césar cielo did the butterfly , was in rio de janeiro .

{'scope': 'all', 'row': '4', 'col': '1', 'col_other': '3', 'criterion': 'fuzzily_match', 'value': 'butterfly', 'subset': None}

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

and { only { filter_eq { all_rows ; event ; butterfly } } ; eq { hop { filter_eq { all_rows ; event ; butterfly } ; venue } ; rio de janeiro } } = true

select the rows whose event record fuzzily matches to butterfly . there is only one such row in the table . the venue record of this unqiue row is rio de janeiro .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'event_7': 7, 'butterfly_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'venue_9': 9, 'rio de janeiro_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'event_7': 'event', 'butterfly_8': 'butterfly', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'venue_9': 'venue', 'rio de janeiro_10': 'rio de janeiro'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'event_7': [0], 'butterfly_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'venue_9': [2], 'rio de janeiro_10': [3]}

['event', 'time', 'venue', 'date', 'notes']

[['50 m freestyle', '20.91', 'são paulo', 'december 18 , 2009', 'wr'], ['100 m freestyle', '46.91', 'rome', 'july 30 , 2009', 'wr'], ['50 m freestyle', '21.30', 'beijing', 'august 16 , 2008', 'or'], ['50 m butterfly', '22.76', 'rio de janeiro', 'april 26 , 2012', 'am'], ['450 m freestyle', '1:26.12', 'são paulo', 'december 19 , 2009', 'sa'], ['4100 m freestyle', '3:10.80', 'rome', 'july 26 , 2009', 'sa'], ['4100 m medley', '3:29.16', 'rome', 'august 2 , 2009', 'sa']]