Datasets:

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logic2text

like 0

2011 british gt season

https://en.wikipedia.org/wiki/2011_British_GT_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30062172-3.html.csv

count

there were twelve occasions where the length was sixty minutes .

{'scope': 'all', 'criterion': 'equal', 'value': '60 mins', 'result': '12', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'length', '60 mins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose length record fuzzily matches to 60 mins .', 'tostr': 'filter_eq { all_rows ; length ; 60 mins }'}], 'result': '12', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; length ; 60 mins } }', 'tointer': 'select the rows whose length record fuzzily matches to 60 mins . the number of such rows is 12 .'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; length ; 60 mins } } ; 12 } = true', 'tointer': 'select the rows whose length record fuzzily matches to 60 mins . the number of such rows is 12 .'}

eq { count { filter_eq { all_rows ; length ; 60 mins } } ; 12 } = true

select the rows whose length record fuzzily matches to 60 mins . the number of such rows is 12 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'length_5': 5, '60 mins_6': 6, '12_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'length_5': 'length', '60 mins_6': '60 mins', '12_7': '12'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'length_5': [0], '60 mins_6': [0], '12_7': [2]}

['round', 'circuit', 'date', 'length', 'pole position', 'gt3 winner', 'gt4 winner']

[['1', 'oulton park', '25 april', '60 mins', 'no 5 scuderia vittoria', 'no 1 trackspeed', 'no 44 abg motorsport'], ['1', 'oulton park', '25 april', '60 mins', 'charles bateman michael lyons', 'david ashburn richard westbrook', 'peter belshaw marcus clutton'], ['2', 'oulton park', '25 april', '60 mins', 'no 1 trackspeed', 'no 5 scuderia vittoria', 'no 42 century motorsport'], ['2', 'oulton park', '25 april', '60 mins', 'david ashburn richard westbrook', 'charles bateman michael lyons', 'jake rattenbury josh wakefield'], ['3', 'snetterton 300', '15 may', '120 mins', 'no 10 crs racing', 'no 23 united autosports', 'no 44 abg motorsport'], ['3', 'snetterton 300', '15 may', '120 mins', 'glynn geddie jim geddie', 'matt bell michael guasch', 'peter belshaw marcus clutton'], ['4', 'brands hatch', '19 june', '120 mins', 'no 21 mtech', 'no 2 trackspeed', 'no 44 abg motorsport'], ['4', 'brands hatch', '19 june', '120 mins', 'duncan cameron matt griffin', 'tim bridgman gregor fisken', 'peter belshaw marcus clutton'], ['5', 'spa - francorchamps', '9 july', '60 mins', 'no 59 mclaren gt', 'no 1 trackspeed', 'no 50 scuderia vittoria'], ['5', 'spa - francorchamps', '9 july', '60 mins', 'chris goodwin andrew kirkaldy', 'david ashburn richard westbrook', 'dan denis david mcdonald'], ['6', 'spa - francorchamps', '9 july', '60 mins', 'no 1 trackspeed', 'no 21 mtech', 'no 48 lotus sport uk'], ['6', 'spa - francorchamps', '9 july', '60 mins', 'david ashburn richard westbrook', 'duncan cameron matt griffin', 'phil glew ollie jackson'], ['7', 'rockingham', '4 september', '60 mins', 'no 23 united autosports', 'no 7 beechdean motorsport', 'no 50 scuderia vittoria'], ['7', 'rockingham', '4 september', '60 mins', 'matt bell michael guasch', 'jonathan adam andrew howard', 'dan denis david mcdonald'], ['8', 'rockingham', '4 september', '60 mins', 'no 2 trackspeed', 'no 11 crs racing', 'no 50 scuderia vittoria'], ['8', 'rockingham', '4 september', '60 mins', 'tim bridgman gregor fisken', 'alex mortimer andrew tate', 'dan denis david mcdonald'], ['9', 'donington park', '25 september', '180 mins', 'no 1 trackspeed', 'no 5 scuderia vittoria', 'no 48 lotus sport uk'], ['9', 'donington park', '25 september', '180 mins', 'david ashburn stephen jelley', 'charles bateman michael lyons', 'phil glew james nash'], ['10', 'silverstone arena', '8 october', '120 mins', 'no 7 beechdean motorsport', 'no 7 beechdean motorsport', 'no 48 lotus sport uk']]

list of cities , towns and villages in vojvodina

https://en.wikipedia.org/wiki/List_of_cities%2C_towns_and_villages_in_Vojvodina

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2562572-12.html.csv

unique

pivnice is the only settlement in vojvodina with slovaks as the largest ethnic group .

{'scope': 'all', 'row': '11', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'slovaks', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'largest ethnic group ( 2002 )', 'slovaks'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose largest ethnic group ( 2002 ) record fuzzily matches to slovaks .', 'tostr': 'filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } }', 'tointer': 'select the rows whose largest ethnic group ( 2002 ) record fuzzily matches to slovaks . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'largest ethnic group ( 2002 )', 'slovaks'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose largest ethnic group ( 2002 ) record fuzzily matches to slovaks .', 'tostr': 'filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks }'}, 'settlement'], 'result': 'pivnice', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } ; settlement }'}, 'pivnice'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } ; settlement } ; pivnice }', 'tointer': 'the settlement record of this unqiue row is pivnice .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } } ; eq { hop { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } ; settlement } ; pivnice } } = true', 'tointer': 'select the rows whose largest ethnic group ( 2002 ) record fuzzily matches to slovaks . there is only one such row in the table . the settlement record of this unqiue row is pivnice .'}

and { only { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } } ; eq { hop { filter_eq { all_rows ; largest ethnic group ( 2002 ) ; slovaks } ; settlement } ; pivnice } } = true

select the rows whose largest ethnic group ( 2002 ) record fuzzily matches to slovaks . there is only one such row in the table . the settlement record of this unqiue row is pivnice .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'largest ethnic group (2002)_7': 7, 'slovaks_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'settlement_9': 9, 'pivnice_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'largest ethnic group (2002)_7': 'largest ethnic group ( 2002 )', 'slovaks_8': 'slovaks', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'settlement_9': 'settlement', 'pivnice_10': 'pivnice'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'largest ethnic group (2002)_7': [0], 'slovaks_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'settlement_9': [2], 'pivnice_10': [3]}

['settlement', 'cyrillic name other names', 'type', 'population ( 2011 )', 'largest ethnic group ( 2002 )', 'dominant religion ( 2002 )']

[['bačka palanka', 'бачка паланка', 'town', '28239', 'serbs', 'orthodox christianity'], ['čelarevo', 'челарево', 'village', '4831', 'serbs', 'orthodox christianity'], ['despotovo', 'деспотово', 'village', '1853', 'serbs', 'orthodox christianity'], ['gajdobra', 'гајдобра', 'village', '2578', 'serbs', 'orthodox christianity'], ['karađorđevo', 'карађорђево', 'village', '738', 'serbs', 'orthodox christianity'], ['mladenovo', 'младеново', 'village', '2679', 'serbs', 'orthodox christianity'], ['neštin', 'нештин', 'village', '794', 'serbs', 'orthodox christianity'], ['nova gajdobra', 'нова гајдобра', 'village', '1220', 'serbs', 'orthodox christianity'], ['obrovac', 'обровац', 'village', '2944', 'serbs', 'orthodox christianity'], ['parage', 'параге', 'village', '921', 'serbs', 'orthodox christianity'], ['pivnice', 'пивнице ( slovak : pivnice )', 'village', '3337', 'slovaks', 'protestantism'], ['silbaš', 'силбаш', 'village', '2467', 'serbs', 'orthodox christianity'], ['tovariševo', 'товаришево', 'village', '2657', 'serbs', 'orthodox christianity']]

mannar district

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24574438-1.html.csv

ordinal

chilawathurai had the 2nd lowest population density among main towns in the mannar district .

{'row': '4', 'col': '11', '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', 'population density ( / km 2 )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; population density ( / km 2 ) ; 2 }'}, 'main town'], 'result': 'chilawathurai', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; population density ( / km 2 ) ; 2 } ; main town }'}, 'chilawathurai'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; population density ( / km 2 ) ; 2 } ; main town } ; chilawathurai } = true', 'tointer': 'select the row whose population density ( / km 2 ) record of all rows is 2nd minimum . the main town record of this row is chilawathurai .'}

eq { hop { nth_argmin { all_rows ; population density ( / km 2 ) ; 2 } ; main town } ; chilawathurai } = true

select the row whose population density ( / km 2 ) record of all rows is 2nd minimum . the main town record of this row is chilawathurai .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'population density ( / km 2 )_5': 5, '2_6': 6, 'main town_7': 7, 'chilawathurai_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', 'population density ( / km 2 )_5': 'population density ( / km 2 )', '2_6': '2', 'main town_7': 'main town', 'chilawathurai_8': 'chilawathurai'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'population density ( / km 2 )_5': [0], '2_6': [0], 'main town_7': [1], 'chilawathurai_8': [2]}

['ds division', 'main town', 'gn divisions', 'area ( km 2 )', 'sri lankan tamil', 'sri lankan moors', 'sinhalese', 'indian tamil', 'other', 'total', 'population density ( / km 2 )']

[['madhu', 'madhu', '17', '553', '6793', '559', '273', '5', '1', '7631', '14'], ['mannar', 'mannar', '49', '212', '40865', '8982', '953', '131', '6', '50937', '240'], ['manthai west', 'adampan', '36', '608', '12993', '1123', '337', '177', '0', '14630', '24'], ['musali', 'chilawathurai', '20', '475', '3042', '4818', '147', '2', '0', '8009', '17'], ['nanaddan', 'nanaddan', '31', '148', '16875', '605', '251', '79', '34', '17844', '121']]

fiba eurobasket 2007 squads

https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12962773-16.html.csv

superlative

the oldest player in the fiba eurobasket 2007 squads was adam wójcik .

{'scope': 'all', 'col_superlative': '4', 'row_superlative': '7', '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', 'year born'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; year born }'}, 'player'], 'result': 'adam wójcik', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; year born } ; player }'}, 'adam wójcik'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; year born } ; player } ; adam wójcik } = true', 'tointer': 'select the row whose year born record of all rows is minimum . the player record of this row is adam wójcik .'}

eq { hop { argmin { all_rows ; year born } ; player } ; adam wójcik } = true

select the row whose year born record of all rows is minimum . the player record of this row is adam wójcik .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'year born_5': 5, 'player_6': 6, 'adam wójcik_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'year born_5': 'year born', 'player_6': 'player', 'adam wójcik_7': 'adam wójcik'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'year born_5': [0], 'player_6': [1], 'adam wójcik_7': [2]}

['player', 'height', 'position', 'year born', 'current club']

[['bartłomiej wołoszyn', '1.97', 'forward', '1986', 'anwil wloclawek'], ['andrzej pluta', '1.81', 'guard', '1974', 'anwil wloclawek'], ['robert skibniewski', '1.82', 'guard', '1983', 'bot turów'], ['robert witka', '2.06', 'forward', '1981', 'bot turów'], ['filip dylewicz', '2.02', 'forward', '1980', 'prokom trefl sopot'], ['radosław hyży', '2.00', 'forward', '1977', 'śląsk wrocław'], ['adam wójcik', '2.08', 'forward', '1970', "upea capo d'orlando"], ['kamil pietras', '2.04', 'forward', '1988', 'olimpija ljubljana'], ['szymon szewczyk', '2.09', 'center', '1982', 'lokomotiv rostov'], ['iwo kitzinger', '1.88', 'guard', '1985', 'bot turów'], ['przemysław frasunkiewicz', '2.01', 'forward', '1979', 'energa czarni'], ['łukasz koszarek', '1.87', 'guard', '1984', 'anwil wloclawek']]

bwf super series masters finals

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20361783-1.html.csv

unique

zhou mi only played in one bwf super series masters finals tournament .

{'scope': 'all', 'row': '5', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'zhou mi', 'subset': None}

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

only { filter_eq { all_rows ; womens singles ; zhou mi } } = true

select the rows whose womens singles record fuzzily matches to zhou mi . 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, 'womens singles_4': 4, 'zhou mi_5': 5}

{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'womens singles_4': 'womens singles', 'zhou mi_5': 'zhou mi'}

{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'womens singles_4': [0], 'zhou mi_5': [0]}

['year', 'mens singles', 'womens singles', 'mens doubles', 'womens doubles', 'mixed doubles']

[['2012', 'chen long', 'li xuerui', 'mathias boe carsten mogensen', 'wang xiaoli yu yang', 'joachim fischer nielsen christinna pedersen'], ['2011', 'lin dan', 'wang yihan', 'mathias boe carsten mogensen', 'wang xiaoli yu yang', 'zhang nan zhao yunlei'], ['2010', 'lee chong wei', 'wang shixian', 'mathias boe carsten mogensen', 'wang xiaoli yu yang', 'zhang nan zhao yunlei'], ['2009', 'lee chong wei', 'wong mew choo', 'jung jae - sung lee yong - dae', 'wong pei tty chin eei hui', 'joachim fischer nielsen christinna pedersen'], ['2008', 'lee chong wei', 'zhou mi', 'koo kien keat tan boon heong', 'wong pei tty chin eei hui', 'thomas laybourn kamilla rytter juhl']]

2007 - 08 rangers f.c. season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11221038-3.html.csv

unique

filip šebo was the only player of slovakian nationality that left rangers f.c. during the 2007 - 08 season .

{'scope': 'all', 'row': '14', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': 'slovakia', 'subset': None}

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

and { only { filter_eq { all_rows ; nat ; slovakia } } ; eq { hop { filter_eq { all_rows ; nat ; slovakia } ; name } ; filip šebo } } = true

select the rows whose nat record fuzzily matches to slovakia . there is only one such row in the table . the name record of this unqiue row is filip šebo .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nat_7': 7, 'slovakia_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'filip šebo_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nat_7': 'nat', 'slovakia_8': 'slovakia', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'filip šebo_10': 'filip šebo'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nat_7': [0], 'slovakia_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'filip šebo_10': [3]}

['nat', 'name', 'moving to', 'type', 'transfer window', 'transfer fee']

[['sco', 'martin ure', "queen 's park", 'end of contract', 'summer', 'n / a'], ['sco', 'scott hadden', 'ross county', 'end of contract', 'summer', 'n / a'], ['sco', 'steven campbell', 'free agent', 'end of contract', 'summer', 'n / a'], ['england', 'joe sagar', 'free agent', 'end of contract', 'summer', 'n / a'], ['sen', "makhtar n'diaye", 'free agent', 'end of contract', 'summer', 'n / a'], ['fra', 'antoine ponroy', 'free agent', 'end of contract', 'summer', 'n / a'], ['ger', 'stefan klos', 'retired', 'end of contract', 'summer', 'n / a'], ['croatia', 'dado pršo', 'retired', 'end of contract', 'summer', 'n / a'], ['sco', 'gavin rae', 'cardiff city', 'end of contract', 'summer', 'n / a'], ['sco', 'brian gilmour', 'queen of the south', 'end of contract', 'summer', 'n / a'], ['swe', 'karl svensson', 'caen', 'transfer', 'summer', '0.7 m'], ['eng', 'lee robinson', 'greenock morton', 'loan', 'summer', 'n / a'], ['cze', 'libor sionko', 'copenhagen', 'transfer', 'summer', '0.09 m'], ['slovakia', 'filip šebo', 'valenciennes', 'loan', 'summer', 'n / a'], ['sco', 'ian murray', 'norwich city', 'transfer', 'summer', 'free'], ['eng', 'ugo ehiogu', 'sheffield united', 'transfer', 'winter', 'free'], ['sco', 'alan hutton', 'tottenham hotspur', 'transfer', 'winter', '9 m'], ['nir', 'roy carroll', 'derby county', 'transfer', 'winter', 'free']]

élie bayol

https://en.wikipedia.org/wiki/%C3%89lie_Bayol

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1228323-1.html.csv

aggregation

between 1952 and 1956 , elie bayol scored a total of 2 points .

{'scope': 'all', 'col': '5', 'type': 'sum', 'result': '2', 'subset': None}

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

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

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

2

2

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

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '2_5': '2'}

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

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

[['1952', 'élie bayol', 'osca 20', 'osca straight - 6', '0'], ['1953', 'élie bayol', 'osca 20', 'osca straight - 6', '0'], ['1953', 'osca', 'osca 20', 'osca straight - 6', '0'], ['1954', 'equipe gordini', 'gordini type 16', 'gordini straight - 6', '2'], ['1955', 'equipe gordini', 'gordini type 16', 'gordini straight - 6', '0'], ['1956', 'gordini', 'gordini type 32', 'gordini straight - 8', '0']]

raman vasilyuk

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17373851-1.html.csv

majority

raman vasilyuk scored most of his international goals at the 2002 world cup qualifier .

{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '2002 world cup qualifier', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'competition', '2002 world cup qualifier'], 'result': True, 'ind': 0, 'tointer': 'for the competition records of all rows , most of them fuzzily match to 2002 world cup qualifier .', 'tostr': 'most_eq { all_rows ; competition ; 2002 world cup qualifier } = true'}

most_eq { all_rows ; competition ; 2002 world cup qualifier } = true

for the competition records of all rows , most of them fuzzily match to 2002 world cup qualifier .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, '2002 world cup qualifier_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', '2002 world cup qualifier_4': '2002 world cup qualifier'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], '2002 world cup qualifier_4': [0]}

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

[['16 august 2000', 'skonto stadium , riga , latvia', '1 - 0', '1 - 0', 'friendly'], ['28 march 2001', 'dynama stadium ( minsk ) , belarus', '2 - 1', '2 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '1 - 0', '4 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '2 - 0', '4 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '3 - 0', '4 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '4 - 0', '4 - 1', '2002 world cup qualifier'], ['10 september 2003', 'sheriff stadium , tiraspol , moldova', '1 - 2', '1 - 2', 'euro 2004 qualifier'], ['6 june 2007', 'vasil levski national stadium , sofia , bulgaria', '1 - 0', '1 - 2', 'euro 2008 qualifier'], ['22 august 2007', 'dynama stadium ( minsk ) , belarus', '1 - 0', '2 - 1', 'friendly'], ['2 february 2008', "ta ' qali national stadium , attard , malta", '1 - 0', '2 - 0', 'malta international football tournament']]

slovak national badminton championships

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15740721-1.html.csv

ordinal

1994 was the second year that juraj brestovský won the men 's singles in the slovak national badminton championships .

{'row': '2', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None}

{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'year', '2'], 'result': '1994', 'ind': 0, 'tostr': 'nth_min { all_rows ; year ; 2 }', 'tointer': 'the 2nd minimum year record of all rows is 1994 .'}, '1994'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; year ; 2 } ; 1994 }', 'tointer': 'the 2nd minimum year record of all rows is 1994 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '2'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; year ; 2 }'}, "men 's singles"], 'result': 'juraj brestovský', 'ind': 3, 'tostr': "hop { nth_argmin { all_rows ; year ; 2 } ; men 's singles }"}, 'juraj brestovský'], 'result': True, 'ind': 4, 'tostr': "eq { hop { nth_argmin { all_rows ; year ; 2 } ; men 's singles } ; juraj brestovský }", 'tointer': "the men 's singles record of the row with 2nd minimum year record is juraj brestovský ."}], 'result': True, 'ind': 5, 'tostr': "and { eq { nth_min { all_rows ; year ; 2 } ; 1994 } ; eq { hop { nth_argmin { all_rows ; year ; 2 } ; men 's singles } ; juraj brestovský } } = true", 'tointer': "the 2nd minimum year record of all rows is 1994 . the men 's singles record of the row with 2nd minimum year record is juraj brestovský ."}

and { eq { nth_min { all_rows ; year ; 2 } ; 1994 } ; eq { hop { nth_argmin { all_rows ; year ; 2 } ; men 's singles } ; juraj brestovský } } = true

the 2nd minimum year record of all rows is 1994 . the men 's singles record of the row with 2nd minimum year record is juraj brestovský .

6

6

{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'year_8': 8, '2_9': 9, '1994_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'year_12': 12, '2_13': 13, "men 's singles_14": 14, 'juraj brestovský_15': 15}

{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'year_8': 'year', '2_9': '2', '1994_10': '1994', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'year_12': 'year', '2_13': '2', "men 's singles_14": "men 's singles", 'juraj brestovský_15': 'juraj brestovský'}

{'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'year_8': [0], '2_9': [0], '1994_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'year_12': [2], '2_13': [2], "men 's singles_14": [3], 'juraj brestovský_15': [4]}

['year', "men 's singles", "women 's singles", "men 's doubles", "women 's doubles", 'mixed doubles']

[['1993', 'juraj brestovský', 'ľuba hanzušová', 'juraj brestovský igor novák', 'ľuba hanzušová aurita hirková', 'peter púdela martina švecová'], ['1994', 'juraj brestovský', 'ľuba hanzušová', 'róbert cyprian peter púdela', 'ľuba hanzušová daniela tomášová', 'peter púdela martina švecová'], ['1995', 'igor novák', 'ľuba hanzušová', 'róbert cyprian peter púdela', 'katarína pokorná alexandra felgrová', 'peter púdela alexandra felgrová'], ['1996', 'marián šulko', 'alexandra felgrová', 'juraj brestovský igor novák', 'radka majorská barbora bobrovská', 'jaroslav heleš katarína pokorná'], ['1997', 'pavel mečár', 'kvetoslava orlovská', 'marián šulko marek navrátil', 'barbora bobrovská radka majorská', 'juraj brestovský zuzana kenížová'], ['1998', 'pavel mečár', 'kvetoslava orlovská', 'pavel mečár jaroslav marek', 'kvetoslava orlovská gabriela zabavníková', 'pavel mečár barbora bobrovská'], ['1999', 'marián šulko', 'kvetoslava orlovská', 'pavel mečár marián šulko', 'barbora bobrovská alexandra felgrová', 'pavel mečár barbora bobrovská'], ['2000', 'marián šulko', 'gabriela zabavníková', 'marián šulko pavel mečár', 'kvetoslava orlovská gabriela zabavníková', 'pavel mečár barbora bobrovská'], ['2001', 'marián šulko', 'gabriela zabavníková', 'marián šulko pavel mečár', 'barbora bobrovská eva sládeková', 'pavel mečár barbora bobrovská'], ['2002', 'lukáš klačanský', 'kvetoslava orlovská', 'marián šulko pavel mečár', 'kvetoslava orlovská gabriela zabavníková', 'pavel mečár barbora bobrovská'], ['2003', 'marián šulko', 'gabriela zabavníková', 'marián šulko pavel mečár', 'zuzana orlovská gabriela zabavníková', 'pavel mečár barbora bobrovská'], ['2004', 'marián šulko', 'kvetoslava orlovská', 'marián šulko pavel mečár', 'barbora bobrovská eva sládeková', 'pavel mečár barbora bobrovská'], ['2005', 'michal matejka', 'eva sládeková', 'marián šulko pavel mečár', 'alexandra felgrová kristína ludíková', 'pavel mečár barbora bobrovská'], ['2006', 'marián šulko', 'kristína ludíková', 'michal matejka marián šulko', 'alexandra felgrová kristína ludíková', 'ladislav tomčko kvetoslava orlovská'], ['2007', 'marián šulko', 'eva sládeková', 'vladimír závada marián smrek', 'kvetoslava orlovská zuzana orlovská', 'vladimír turlík gabriela zabavníková'], ['2008', 'marián šulko', 'kvetoslava orlovská', 'vladimír závada marián smrek', 'júlia turzáková gabriela zabavníková', 'marián smrek kvetoslava orlovská'], ['2009', 'michal matejka', 'monika fašungová', 'vladimír závada marián smrek', 'barbora bobrovská zuzana orlovská', 'vladimír závada zuzana orlovská'], ['2010', 'michal matejka', 'ivana kubíková', 'marián šulko pavel mečár', 'barbora bobrovská zuzana orlovská', 'vladimír závada zuzana orlovská']]

little league world series ( mid - atlantic region )

https://en.wikipedia.org/wiki/Little_League_World_Series_%28Mid-Atlantic_Region%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13012165-1.html.csv

ordinal

the 2nd to last year for the little league world series ( mid - atlantic region ) was when the new jersey team was paramus ll paramus .

{'row': '11', 'col': '1', 'order': '2', 'col_other': '4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

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

eq { hop { nth_argmax { all_rows ; year ; 2 } ; new jersey } ; paramus ll paramus } = true

select the row whose year record of all rows is 2nd maximum . the new jersey record of this row is paramus ll paramus .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'new jersey_7': 7, 'paramus ll paramus_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', 'year_5': 'year', '2_6': '2', 'new jersey_7': 'new jersey', 'paramus ll paramus_8': 'paramus ll paramus'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'new jersey_7': [1], 'paramus ll paramus_8': [2]}

['year', 'delaware', 'maryland', 'new jersey', 'new york', 'pennsylvania', 'washington , dc']

[['2001', 'midway ll wilmington', 'easton ll easton', 'randolph west ll randolph', 'rolando paulino ll bronx', 'state college american ll state college', 'capitol city ll'], ['2002', 'lower sussex ll frankford', 'south caroline ll preston', 'nottingham ll hamilton square', 'harlem ll manhattan', 'lehigh ll bethlehem', 'capitol city ll'], ['2003', 'naamans ll wilmington', 'west salisbury ll salisbury', 'freehold township american ll freehold', 'ramapo ll ramapo', 'lower perkiomen ll collegeville', 'capitol city ll'], ['2004', 'capitol ll wilmington', 'south caroline ll preston', 'htrba ll hamilton', 'colonie ll colonie', 'deep run valley ll hilltown', 'capitol city ll'], ['2005', 'canal ll bear', 'thurmont ll thurmont', 'toms river american ll toms river', 'merrick - north merrick ll merrick', 'council rock newtown ll newtown', 'no tournament'], ['2006', 'naamans ll wilmington', 'south caroline ll preston', 'livingston american ll livingston', 'mid - island ll staten island', 'butler township ll butler township', 'capitol city ll'], ['2007', 'mot ll middletown', 'west salisbury ll salisbury', 'randolph east ll randolph', 'maine - endwell ll endwell', 'council rock northampton ll northampton township', 'capitol city ll'], ['2008', 'mot ll middletown', 'hagerstown federal ll hagerstown', 'bordentown ll bordentown', 'haverstraw ll haverstraw', 'devon strafford ll devon', 'capitol city ll'], ['2009', 'mot ll middletown', 'conococheague ll williamsport', 'somerset hills ll bernardsville', 'south shore national ll staten island', 'moon township ll moon township', 'northwest washington ll'], ['2010', 'brandywine ll wilmington', 'railroaders ll brunswick', 'toms river national ll toms river', 'stony point ll stony point', 'council rock newtown ll newtown', 'capitol city ll'], ['2011', 'newark national ll newark', 'conocoheague ll williamsport', 'paramus ll paramus', 'great kills american ll staten island', 'keystone ll beech creek', 'northwest washington ll'], ['2012', 'newark national ll newark', 'west salisbury ll salisbury', 'par - troy east ll parsippany', 'stony point ll stony point', 'collier township athletic association collier', 'northwest washington ll']]

list of people in playboy 2000 - 09

https://en.wikipedia.org/wiki/List_of_people_in_Playboy_2000%E2%80%9309

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1566852-4.html.csv

comparative

tobey maguire appeared in playboy later than mike piazza in 2003 .

{'row_1': '8', 'row_2': '6', 'col': '1', 'col_other': '4', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'interview subject', 'tobey maguire'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose interview subject record fuzzily matches to tobey maguire .', 'tostr': 'filter_eq { all_rows ; interview subject ; tobey maguire }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; interview subject ; tobey maguire } ; date }', 'tointer': 'select the rows whose interview subject record fuzzily matches to tobey maguire . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'interview subject', 'mike piazza'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose interview subject record fuzzily matches to mike piazza .', 'tostr': 'filter_eq { all_rows ; interview subject ; mike piazza }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; interview subject ; mike piazza } ; date }', 'tointer': 'select the rows whose interview subject record fuzzily matches to mike piazza . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; interview subject ; tobey maguire } ; date } ; hop { filter_eq { all_rows ; interview subject ; mike piazza } ; date } } = true', 'tointer': 'select the rows whose interview subject record fuzzily matches to tobey maguire . take the date record of this row . select the rows whose interview subject record fuzzily matches to mike piazza . take the date record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; interview subject ; tobey maguire } ; date } ; hop { filter_eq { all_rows ; interview subject ; mike piazza } ; date } } = true

select the rows whose interview subject record fuzzily matches to tobey maguire . take the date record of this row . select the rows whose interview subject record fuzzily matches to mike piazza . take the date record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'interview subject_7': 7, 'tobey maguire_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'interview subject_11': 11, 'mike piazza_12': 12, 'date_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'interview subject_7': 'interview subject', 'tobey maguire_8': 'tobey maguire', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'interview subject_11': 'interview subject', 'mike piazza_12': 'mike piazza', 'date_13': 'date'}

{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'interview subject_7': [0], 'tobey maguire_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'interview subject_11': [1], 'mike piazza_12': [1], 'date_13': [3]}

['date', 'cover model', 'centerfold model', 'interview subject', '20 questions']

[['1 - 03', 'tia carrere', 'rebecca anne ramos', 'halle berry', 'ron insana'], ['2 - 03', 'alison eastwood', 'charis boyle', 'jimmy kimmel', 'bernie mac'], ['3 - 03', 'dorismar', 'pennelope jimenez', 'colin farrell', 'juliette lewis'], ['4 - 03', 'carmen electra', 'carmella decesare', 'jay - z', 'andy richter'], ['5 - 03', 'torrie wilson', 'laurie fetter', 'billy bob thornton', 'jorja fox'], ['6 - 03', 'sarah kozer', 'tailor james', 'mike piazza', 'nelly'], ['7 - 03', 'nikki ziering', 'marketa janska', 'lisa marie presley', 'rachel weisz'], ['8 - 03', 'jenna morasca , heidi strobel', 'colleen marie', 'tobey maguire', 'charles rangel'], ['9 - 03', 'signe nordli', 'luci victoria', 'jon gruden', 'nicolas cage'], ['10 - 03', 'lauren hill', 'audra lynn', 'oj simpson', 'joe rogan'], ['11 - 03', 'daryl hannah', 'divini rae', 'quentin tarantino', 'bill murray'], ['12 - 03', 'shannen doherty', 'deisy teles and sarah teles', 'john cusack', 'william h macy']]

1972 miami dolphins season

https://en.wikipedia.org/wiki/1972_Miami_Dolphins_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14202514-1.html.csv

ordinal

the miami dolphins ' match against detroit lions was the earliest of the 1972 season games .

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

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

eq { hop { nth_argmin { all_rows ; week ; 1 } ; opponent } ; detroit lions } = true

select the row whose week record of all rows is 1st minimum . the opponent record of this row is detroit lions .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'week_5': 5, '1_6': 6, 'opponent_7': 7, 'detroit lions_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'week_5': 'week', '1_6': '1', 'opponent_7': 'opponent', 'detroit lions_8': 'detroit lions'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'week_5': [0], '1_6': [0], 'opponent_7': [1], 'detroit lions_8': [2]}

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

[['1', 'august 5 , 1972', 'detroit lions', 'l 23 - 31', '0 - 1'], ['2', 'august 12 , 1972', 'green bay packers', 'l 13 - 14', '0 - 2'], ['3', 'august 19 , 1972', 'cincinnati bengals', 'w 35 - 17', '1 - 2'], ['4', 'august 25 , 1972', 'atlanta falcons', 'w 24 - 10', '2 - 2'], ['5', 'august 31 , 1972', 'washington redskins', 'l 24 - 27', '2 - 3'], ['6', 'september 10 , 1972', 'minnesota vikings', 'w 21 - 19', '3 - 3']]

1943 vfl season

https://en.wikipedia.org/wiki/1943_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10808346-13.html.csv

count

of the games in the 1943 vfl season that had a crowd over 10000 people , two of the away teams had a final score in the double digits .

{'scope': 'subset', 'criterion': 'greater_than_eq', 'value': '10', 'result': '2', 'col': '4', 'subset': {'col': '6', 'criterion': 'greater_than', 'value': '10000'}}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '10000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; crowd ; 10000 }', 'tointer': 'select the rows whose crowd record is greater than 10000 .'}, 'away team score', '10'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose crowd record is greater than 10000 . among these rows , select the rows whose away team score record is greater than or equal to 10 .', 'tostr': 'filter_greater_eq { filter_greater { all_rows ; crowd ; 10000 } ; away team score ; 10 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater_eq { filter_greater { all_rows ; crowd ; 10000 } ; away team score ; 10 } }', 'tointer': 'select the rows whose crowd record is greater than 10000 . among these rows , select the rows whose away team score record is greater than or equal to 10 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater_eq { filter_greater { all_rows ; crowd ; 10000 } ; away team score ; 10 } } ; 2 } = true', 'tointer': 'select the rows whose crowd record is greater than 10000 . among these rows , select the rows whose away team score record is greater than or equal to 10 . the number of such rows is 2 .'}

eq { count { filter_greater_eq { filter_greater { all_rows ; crowd ; 10000 } ; away team score ; 10 } } ; 2 } = true

select the rows whose crowd record is greater than 10000 . among these rows , select the rows whose away team score record is greater than or equal to 10 . the number of such rows is 2 .

4

4

{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'crowd_6': 6, '10000_7': 7, 'away team score_8': 8, '10_9': 9, '2_10': 10}

{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_eq_1': 'filter_greater_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'crowd_6': 'crowd', '10000_7': '10000', 'away team score_8': 'away team score', '10_9': '10', '2_10': '2'}

{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'crowd_6': [0], '10000_7': [0], 'away team score_8': [1], '10_9': [1], '2_10': [3]}

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

[['melbourne', '9.6 ( 60 )', 'south melbourne', '21.13 ( 139 )', 'punt road oval', '14000', '7 august 1943'], ['footscray', '7.17 ( 59 )', 'richmond', '19.19 ( 133 )', 'western oval', '9000', '7 august 1943'], ['essendon', '11.24 ( 90 )', 'fitzroy', '8.8 ( 56 )', 'windy hill', '14000', '7 august 1943'], ['collingwood', '14.24 ( 108 )', 'north melbourne', '7.8 ( 50 )', 'victoria park', '5250', '7 august 1943'], ['carlton', '13.19 ( 97 )', 'hawthorn', '10.15 ( 75 )', 'princes park', '15000', '7 august 1943']]

2007 eneco tour

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12608303-1.html.csv

superlative

the longest distance of the 2007 eneco tour was stage two .

{'scope': 'all', 'col_superlative': '3', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

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

eq { hop { argmax { all_rows ; distance } ; stage } ; 2 } = true

select the row whose distance record of all rows is maximum . the stage record of this row is 2 .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'distance_5': 5, 'stage_6': 6, '2_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'distance_5': 'distance', 'stage_6': 'stage', '2_7': '2'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'distance_5': [0], 'stage_6': [1], '2_7': [2]}

['stage', 'route', 'distance', 'date', 'winner']

[['p', 'hasselt - hasselt', '5.1 km', 'wednesday , august 22', 'michiel elijzen'], ['1', 'waremme - eupen', '189.5 km', 'thursday , august 23', 'nick nuyens'], ['2', 'antwerp - knokke - heist', '199.1 km', 'friday , august 24', 'mark cavendish'], ['3', 'knokke - heist - putte', '170.8 km', 'saturday , august 25', 'robbie mcewen'], ['4', 'maldegem - terneuzen', '182.7 km', 'sunday , august 26', 'wouter weylandt'], ['5', 'terneuzen - nieuwegein', '179.9 km', 'monday , august 27', 'luciano pagliarini'], ['6', 'beek - landgraaf', '177.4 km', 'tuesday , august 28', 'pablo lastras'], ['7 ( itt )', 'sittard - geleen', '29.6 km', 'wednesday , august 29', 'sébastien rosseler']]

2004 amsterdam admirals season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24951872-2.html.csv

superlative

the waldstadion was the first game site used by the amsterdam admirals in the 2004 season .

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

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

eq { hop { argmin { all_rows ; date } ; game site } ; waldstadion } = true

select the row whose date record of all rows is minimum . the game site record of this row is waldstadion .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'game site_6': 6, 'waldstadion_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'game site_6': 'game site', 'waldstadion_7': 'waldstadion'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'game site_6': [1], 'waldstadion_7': [2]}

['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance']

[['1', 'saturday , april 3', '7:00 pm', 'frankfurt galaxy', 'l 11 - 34', '0 - 1', 'waldstadion', '21269'], ['2', 'saturday , april 10', '7:00 pm', 'berlin thunder', 'l 17 - 28', '0 - 2', 'amsterdam arena', '10763'], ['3', 'sunday , april 18', '2:00 pm', 'scottish claymores', 'w 3 - 0', '1 - 2', 'hampden park', '10971'], ['4', 'sunday , april 25', '3:00 pm', 'frankfurt galaxy', 'w 21 - 17 ot', '2 - 2', 'amsterdam arena', '10684'], ['5', 'sunday , may 2', '4:00 pm', 'berlin thunder', 'l 29 - 33', '2 - 3', 'olympic stadium', '12909'], ['6', 'sunday , may 9', '4:00 pm', 'rhein fire', 'l 13 - 20', '2 - 4', 'arena aufschalke', '18790'], ['7', 'saturday , may 15', '7:00 pm', 'cologne centurions', 'w 17 - 10', '3 - 4', 'amsterdam arena', '14437'], ['8', 'friday , may 21', '8:00 pm', 'scottish claymores', 'l 17 - 19', '3 - 5', 'amsterdam arena', '10738'], ['9', 'sunday , may 30', '4:00 pm', 'cologne centurions', 'w 23 - 18', '4 - 5', 'rheinenergiestadion', '9056']]

list of nascar teams

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1266602-2.html.csv

ordinal

the team that participated in the highest number of rounds was phil parsons racing .

{'row': '6', 'col': '7', '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', 'rounds', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; rounds ; 1 }'}, 'team'], 'result': 'phil parsons racing', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; rounds ; 1 } ; team }'}, 'phil parsons racing'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; rounds ; 1 } ; team } ; phil parsons racing } = true', 'tointer': 'select the row whose rounds record of all rows is 1st maximum . the team record of this row is phil parsons racing .'}

eq { hop { nth_argmax { all_rows ; rounds ; 1 } ; team } ; phil parsons racing } = true

select the row whose rounds record of all rows is 1st maximum . the team record of this row is phil parsons racing .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'rounds_5': 5, '1_6': 6, 'team_7': 7, 'phil parsons racing_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', 'rounds_5': 'rounds', '1_6': '1', 'team_7': 'team', 'phil parsons racing_8': 'phil parsons racing'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'rounds_5': [0], '1_6': [0], 'team_7': [1], 'phil parsons racing_8': [2]}

['team', 'car ( s )', 'driver ( s )', 'primary sponsor ( s )', 'owner ( s )', 'crew chief', 'rounds']

[['circle sport', 'chevrolet ss', 'tony raines', "little joe 's auto", 'joe falk', 'john rahlf', '25'], ['go green racing', 'ford fusion', 'brian keselowski', 'my 3 sons vending', 'bob keselowski', 'ben leslie', '7'], ['hillman racing', 'chevrolet ss', 'landon cassill', 'crc brakleen', 'mike hillman', 'mike abner', '9'], ['humphrey smith racing', 'chevrolet ss', 'mike bliss', 'n / a', 'randy humphrey', 'peter sospenzo', '22'], ['leavine family racing', 'ford fusion', 'reed sorenson', 'n / a', 'bob leavine', 'wally rogers', '16'], ['phil parsons racing', 'ford fusion', 'michael mcdowell', 'k - love / curb records', 'mike curb', 'gene nead', '26'], ['richard childress racing', 'chevrolet ss', 'austin dillon', 'advocare', 'richard childress', 'scott naset', '4'], ['wood brothers racing', 'ford fusion', 'trevor bayne', 'motorcraft / quick lane', 'glen wood', 'donnie wingo', '8'], ['xxxtreme motorsport', 'ford fusion', 'scott riggs', 'no label watches', 'john cohen', 'walter giles', '10']]

colts - patriots rivalry

https://en.wikipedia.org/wiki/Colts%E2%80%93Patriots_rivalry

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13342861-3.html.csv

majority

in the majority of games between new england patriots and the baltimore colts both teams score .

{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '0', 'subset': None}

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

most_greater { all_rows ; result ; 0 } = true

for the result records of all rows , most of them are greater than 0 .

1

1

{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, '0_4': 4}

{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', '0_4': '0'}

{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], '0_4': [0]}

['year', 'date', 'winner', 'result', 'loser', 'location']

[['1970', 'october 4', 'baltimore colts', '14 - 6', 'boston patriots', 'harvard stadium'], ['1970', 'october 25', 'baltimore colts', '27 - 3', 'boston patriots', 'memorial stadium ( baltimore )'], ['1971', 'october 3', 'baltimore colts', '23 - 3', 'new england patriots', 'schaefer stadium'], ['1971', 'december 19', 'new england patriots', '21 - 17', 'baltimore colts', 'memorial stadium ( baltimore )'], ['1972', 'november 6', 'baltimore colts', '24 - 17', 'new england patriots', 'schaefer stadium'], ['1972', 'november 26', 'baltimore colts', '31 - 0', 'new england patriots', 'memorial stadium ( baltimore )'], ['1973', 'october 7', 'new england patriots', '24 - 16', 'baltimore colts', 'schaefer stadium'], ['1973', 'december 16', 'baltimore colts', '18 - 13', 'new england patriots', 'memorial stadium ( baltimore )'], ['1974', 'october 6', 'new england patriots', '42 - 3', 'baltimore colts', 'schaefer stadium'], ['1974', 'november 24', 'new england patriots', '27 - 17', 'baltimore colts', 'memorial stadium ( baltimore )'], ['1975', 'october 19', 'new england patriots', '21 - 10', 'baltimore colts', 'schaefer stadium'], ['1975', 'december 21', 'baltimore colts', '34 - 21', 'new england patriots', 'memorial stadium ( baltimore )'], ['1976', 'september 12', 'baltimore colts', '27 - 13', 'new england patriots', 'schaefer stadium'], ['1976', 'november 14', 'new england patriots', '21 - 14', 'baltimore colts', 'memorial stadium ( baltimore )'], ['1977', 'october 23', 'new england patriots', '17 - 3', 'baltimore colts', 'schaefer stadium'], ['1977', 'december 18', 'baltimore colts', '30 - 24', 'new england patriots', 'memorial stadium ( baltimore )'], ['1978', 'september 18', 'baltimore colts', '34 - 27', 'new england patriots', 'schaefer stadium'], ['1978', 'november 26', 'new england patriots', '35 - 14', 'baltimore colts', 'memorial stadium ( baltimore )'], ['1979', 'october 28', 'baltimore colts', '31 - 26', 'new england patriots', 'memorial stadium ( baltimore )'], ['1979', 'november 18', 'new england patriots', '50 - 21', 'baltimore colts', 'schaefer stadium']]

list of garfield and friends episodes

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1852270-8.html.csv

comparative

the episode daydream doctor aired before the episode deja vu did .

{'row_1': '8', 'row_2': '14', 'col': '5', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'us acres episode', 'daydream doctor'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us acres episode record fuzzily matches to daydream doctor .', 'tostr': 'filter_eq { all_rows ; us acres episode ; daydream doctor }'}, 'original airdate'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; us acres episode ; daydream doctor } ; original airdate }', 'tointer': 'select the rows whose us acres episode record fuzzily matches to daydream doctor . take the original airdate record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'us acres episode', 'deja vu'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose us acres episode record fuzzily matches to deja vu .', 'tostr': 'filter_eq { all_rows ; us acres episode ; deja vu }'}, 'original airdate'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; us acres episode ; deja vu } ; original airdate }', 'tointer': 'select the rows whose us acres episode record fuzzily matches to deja vu . take the original airdate record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; us acres episode ; daydream doctor } ; original airdate } ; hop { filter_eq { all_rows ; us acres episode ; deja vu } ; original airdate } } = true', 'tointer': 'select the rows whose us acres episode record fuzzily matches to daydream doctor . take the original airdate record of this row . select the rows whose us acres episode record fuzzily matches to deja vu . take the original airdate record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; us acres episode ; daydream doctor } ; original airdate } ; hop { filter_eq { all_rows ; us acres episode ; deja vu } ; original airdate } } = true

select the rows whose us acres episode record fuzzily matches to daydream doctor . take the original airdate record of this row . select the rows whose us acres episode record fuzzily matches to deja vu . take the original airdate 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, 'us acres episode_7': 7, 'daydream doctor_8': 8, 'original airdate_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'us acres episode_11': 11, 'deja vu_12': 12, 'original airdate_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', 'us acres episode_7': 'us acres episode', 'daydream doctor_8': 'daydream doctor', 'original airdate_9': 'original airdate', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'us acres episode_11': 'us acres episode', 'deja vu_12': 'deja vu', 'original airdate_13': 'original airdate'}

{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'us acres episode_7': [0], 'daydream doctor_8': [0], 'original airdate_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'us acres episode_11': [1], 'deja vu_12': [1], 'original airdate_13': [3]}

['episode', 'garfield episode 1', 'us acres episode', 'garfield episode 2', 'original airdate']

[['show 106', 'the legend of johnny ragweedseed', 'grape expectations ( part 1 )', "catch as cats ca n't", 'september 17 , 1994'], ['show 107', 'a matter of conscience', 'grape expectations ( part 2 )', 'top ten', 'september 17 , 1994'], ['show 108', 'change of mind', 'temp trouble', 'the perfect match', 'september 24 , 1994'], ['show 109', 'my fair feline', 'double trouble talk', 'half - baked alaska', 'september 24 , 1994'], ['show 110', 'puss in high - tops', 'egg over easy ( part 1 )', 'the beast from beyond', 'october 1 , 1994'], ['show 111', 'model behavior', 'egg over easy ( part 2 )', 'another ant episode', 'october 1 , 1994'], ['show 112', 'the guy of her dreams', 'the discount of monte cristo', 'the fairy dogmother', 'october 8 , 1994'], ['show 113', 'the stand - up mouse', 'daydream doctor', 'happy garfield day', 'october 8 , 1994'], ['show 114', 'sit on it', 'kiddy korner', 'brainware broadcast', 'october 15 , 1994'], ['show 115', 'suburban jungle', 'the thing in the box', 'the feline philosopher', 'october 22 , 1994'], ['show 116', 'thoroughly mixed - up mouse', 'the old man of the mountain', 'food fighter', 'october 29 , 1994'], ['show 117', 'the jelly roger', 'the farmyard feline philosopher', 'dogmother 2', 'november 5 , 1994'], ['show 118', 'alley katta and the 40 thieves', "if it 's tuesday this must be alpha centauri", 'clash of the titans', 'november 19 , 1994'], ['show 119', 'canned laughter', 'deja vu', 'the man who hated cats', 'november 26 , 1994'], ['show 120', 'the horror hostess ( part 1 )', 'newsworthy wade', 'the horror hostess ( part 2 )', 'december 3 , 1994']]

united states house of representatives elections , 1822

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1822

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668298-19.html.csv

comparative

weldon n edwards has a first elected year which is earlier than that of romulus m saunders ' .

{'row_1': '4', 'row_2': '6', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'weldon n edwards'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to weldon n edwards .', 'tostr': 'filter_eq { all_rows ; incumbent ; weldon n edwards }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; weldon n edwards } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to weldon n edwards . take the first elected record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'romulus m saunders'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to romulus m saunders .', 'tostr': 'filter_eq { all_rows ; incumbent ; romulus m saunders }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; romulus m saunders } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to romulus m saunders . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; weldon n edwards } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; romulus m saunders } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to weldon n edwards . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to romulus m saunders . take the first elected record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; incumbent ; weldon n edwards } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; romulus m saunders } ; first elected } } = true

select the rows whose incumbent record fuzzily matches to weldon n edwards . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to romulus m saunders . take the first elected record of this row . the first record is less than the second record .

5

5

{'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'weldon n edwards_8': 8, 'first elected_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'romulus m saunders_12': 12, 'first elected_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', 'incumbent_7': 'incumbent', 'weldon n edwards_8': 'weldon n edwards', 'first elected_9': 'first elected', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'romulus m saunders_12': 'romulus m saunders', 'first elected_13': 'first elected'}

{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'weldon n edwards_8': [0], 'first elected_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'romulus m saunders_12': [1], 'first elected_13': [3]}

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

[['north carolina 2', 'hutchins g burton', 'democratic - republican', '1819', 're - elected', 'hutchins g burton ( c - dr ) jesse a dawson'], ['north carolina 4', 'william s blackledge', 'democratic - republican', '1821', 'retired democratic - republican hold', 'richard dobbs spaight , jr ( c - dr )'], ['north carolina 5', 'charles hooks', 'democratic - republican', '1816 ( special ) 1819', 're - elected', 'charles hooks ( c - dr ) john d jones'], ['north carolina 6', 'weldon n edwards', 'democratic - republican', '1816 ( special )', 're - elected', 'weldon n edwards ( c - dr ) 100 %'], ['north carolina 7', 'archibald mcneill', 'federalist', '1821', 'retired federalist hold', 'john culpepper ( a - f ) 50.9 % alexander mcneill 49.1 %'], ['north carolina 9', 'romulus m saunders', 'democratic - republican', '1821', 're - elected', 'romulus m saunders ( c - dr ) 100 %'], ['north carolina 10', 'john long', 'democratic - republican', '1821', 're - elected', 'john long ( c - dr ) 66.9 % john macclelland 33.1 %']]

portuguese legislative election , 2005

https://en.wikipedia.org/wiki/Portuguese_legislative_election%2C_2005

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1463383-1.html.csv

aggregation

the socialist party had an average poll rating of about 45 % . in 2005 .

{'scope': 'all', 'col': '3', 'type': 'average', 'result': '45 %', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'socialist'], 'result': '45 %', 'ind': 0, 'tostr': 'avg { all_rows ; socialist }'}, '45 %'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; socialist } ; 45 % } = true', 'tointer': 'the average of the socialist record of all rows is 45 % .'}

round_eq { avg { all_rows ; socialist } ; 45 % } = true

the average of the socialist record of all rows is 45 % .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'socialist_4': 4, '45%_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'socialist_4': 'socialist', '45%_5': '45 %'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'socialist_4': [0], '45%_5': [1]}

['date released', 'polling institute', 'socialist', 'social democratic', 'peoples party', 'green - communist', 'left bloc', 'lead']

[['february 20 , 2005', 'election results', '45.0 % 121 seats', '28.8 % 75 seats', '7.2 % 12 seats', '7.5 % 14 seats', '6.4 % 8 seats', '16.2 %'], ['february 18 , 2005', 'aximage', '46.8 %', '29.6 %', '7.3 %', '7.0 %', '5.5 %', '17.2 %'], ['february 18 , 2005', 'marktest', '46.0 %', '26.8 %', '7.5 %', '8.9 %', '7.7 %', '19.2 %'], ['february 18 , 2005', 'eurosondagem', '45.0 %', '30.6 %', '7.7 %', '7.7 %', '5.7 %', '14.4 %'], ['february 18 , 2005', 'ipom', '46.0 %', '30.0 %', '8.0 %', '6.0 %', '7.0 %', '16.0 %'], ['february 18 , 2005', 'intercampus', '45.9 %', '30.3 %', '7.1 %', '7.6 %', '5.2 %', '15.6 %'], ['february 17 , 2005', 'tns / euroteste', '39.0 %', '28.0 %', '7.0 %', '6.0 %', '6.0 %', '11.0 %'], ['february 17 , 2005', 'universidade católica', '46.0 %', '31.0 %', '6.0 %', '7.0 %', '7.0 %', '15.0 %'], ['february 12 , 2005', 'eurosondagem', '44.4 %', '31.3 %', '7.4 %', '6.9 %', '6.4 %', '13.1 %'], ['february 11 , 2005', 'aximage', '44.7 %', '27.4 %', '6.4 %', '7.1 %', '4.8 %', '17.3 %'], ['february 4 , 2005', 'ipom', '49.0 %', '31.0 %', '8.0 %', '6.0 %', '5.0 %', '18.0 %'], ['february 4 , 2005', 'aximage', '43.5 %', '29.3 %', '7.0 %', '5.6 %', '3.5 %', '14.2 %'], ['february 3 , 2005', 'intercampus', '46.5 %', '31.6 %', '4.8 %', '8.1 %', '4.5 %', '14.9 %'], ['january 29 , 2005', 'eurosondagem', '46.1 %', '32.1 %', '7.0 %', '6.6 %', '4.6 %', '14.0 %'], ['january 28 , 2005', 'marktest', '45.1 %', '27.7 %', '6.3 %', '7.7 %', '8.1 %', '17.5 %'], ['january 28 , 2005', 'aximage', '43.3 %', '27.4 %', '6.3 %', '5.8 %', '5.0 %', '15.9 %'], ['january 28 , 2005', 'universidade católica', '46.0 %', '28.0 %', '6.0 %', '8.0 %', '8.0 %', '18.0 %'], ['january 27 , 2005', 'tns / euroteste', '40.0 %', '32.0 %', '6.0 %', '4.0 %', '5.0 %', '8.0 %'], ['january 21 , 2005', 'axiamge', '42.8 %', '28.7 %', '7.1 %', '6.2 %', '4.3 %', '14.1 %']]

1998 st. louis rams season

https://en.wikipedia.org/wiki/1998_St._Louis_Rams_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10689097-1.html.csv

aggregation

the 1998 st. louis rams season has a total of 881037 attendance .

{'scope': 'all', 'col': '5', 'type': 'sum', 'result': '881037', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'attendance'], 'result': '881037', 'ind': 0, 'tostr': 'sum { all_rows ; attendance }'}, '881037'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; attendance } ; 881037 } = true', 'tointer': 'the sum of the attendance record of all rows is 881037 .'}

round_eq { sum { all_rows ; attendance } ; 881037 } = true

the sum of the attendance record of all rows is 881037 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '881037_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '881037_5': '881037'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '881037_5': [1]}

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

[['1', 'new orleans saints', 'l 17 - 24', '0 - 1', '56943'], ['2', 'minnesota vikings', 'l 31 - 38', '0 - 2', '56234'], ['3', 'buffalo bills', 'w 34 - 33', '1 - 2', '65199'], ['4', 'arizona cardinals', 'l 17 - 20', '1 - 3', '55832'], ['6', 'new york jets', 'w 30 - 10', '2 - 3', '55938'], ['7', 'miami dolphins', 'l 0 - 14', '2 - 4', '65418'], ['8', 'san francisco 49ers', 'l 10 - 28', '2 - 5', '58563'], ['9', 'atlanta falcons', 'l 15 - 37', '2 - 6', '37996'], ['10', 'chicago bears', 'w 20 - 12', '3 - 6', '50263'], ['11', 'new orleans saints', 'l 3 - 24', '3 - 7', '46430'], ['12', 'carolina panthers', 'l 20 - 24', '3 - 8', '50716'], ['13', 'atlanta falcons', 'l 10 - 21', '3 - 9', '47971'], ['14', 'philadelphia eagles', 'l 14 - 17', '3 - 10', '66155'], ['15', 'new england patriots', 'w 32 - 18', '4 - 10', '48946'], ['16', 'carolina panthers', 'l 13 - 20', '4 - 11', '50047'], ['17', 'san francisco 49ers', 'l 19 - 38', '4 - 12', '68386']]

athletics at the 1986 central american and caribbean games

https://en.wikipedia.org/wiki/Athletics_at_the_1986_Central_American_and_Caribbean_Games

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10258265-3.html.csv

ordinal

colombia was the country that recorded the second most bronze medals in athletics at the 1986 central american and caribbean games .

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

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

eq { hop { nth_argmax { all_rows ; bronze ; 2 } ; nation } ; colombia } = true

select the row whose bronze record of all rows is 2nd maximum . the nation record of this row is colombia .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'bronze_5': 5, '2_6': 6, 'nation_7': 7, 'colombia_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', 'bronze_5': 'bronze', '2_6': '2', 'nation_7': 'nation', 'colombia_8': 'colombia'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'bronze_5': [0], '2_6': [0], 'nation_7': [1], 'colombia_8': [2]}

['rank', 'nation', 'gold', 'silver', 'bronze', 'total']

[['1', 'cuba', '27', '16', '8', '51'], ['2', 'mexico', '6', '9', '6', '21'], ['3', 'colombia', '3', '1', '7', '11'], ['4', 'bahamas', '2', '4', '3', '9'], ['5', 'puerto rico', '2', '3', '6', '11'], ['6', 'jamaica', '1', '3', '3', '7'], ['7', 'us virgin islands', '1', '0', '1', '2'], ['8', 'guyana', '1', '0', '0', '1'], ['9', 'dominican republic', '0', '4', '2', '6'], ['10', 'trinidad and tobago', '0', '2', '1', '3'], ['10', 'venezuela', '0', '2', '1', '3'], ['12', 'barbados', '0', '0', '2', '2'], ['13', 'haiti', '0', '0', '1', '1'], ['13', 'panama', '0', '0', '1', '1']]

list of la femme nikita episodes

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10910712-5.html.csv

count

there were two episodes of la femme nikita that were written by david wolkove .

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

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

eq { count { filter_eq { all_rows ; written by ; david wolkove } } ; 2 } = true

select the rows whose written by record fuzzily matches to david wolkove . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'written by_5': 5, 'david wolkove_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'written by_5': 'written by', 'david wolkove_6': 'david wolkove', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'written by_5': [0], 'david wolkove_6': [0], '2_7': [2]}

['episode', 'title', 'directed by', 'written by', 'original airdate']

[['89 ( 1 )', 'déjà vu all over again', 'jon cassar', 'robert cochran', 'january 7 , 2001'], ['90 ( 2 )', "a girl who was n't there", 'terry ingram', 'lawrence hertzog', 'january 14 , 2001'], ['91 ( 3 )', 'in through the out door', 'rené bonnière', 'david wolkove', 'january 21 , 2001'], ['92 ( 4 )', "all the world 's a stage", 'joel surnow', 'david wolkove', 'february 4 , 2001'], ['93 ( 5 )', 'the man behind the curtain', 'rené bonnière', 'lawrence hertzog', 'february 11 , 2001'], ['94 ( 6 )', 'the evil that men do', 'roy dupuis', 'andy horne & katherine tomlinson', 'february 18 , 2001'], ['95 ( 7 )', 'let no man put asunder', 'rené bonnière', 'lawrence hertzog', 'february 25 , 2001'], ['96 ( 8 )', 'a time for every purpose', 'brad turner', 'michael loceff', 'march 4 , 2001']]

patty schnyder

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1547798-2.html.csv

majority

most of patty schnyder 's matches were played on a hard surface .

{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None}

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

most_eq { all_rows ; surface ; hard } = true

for the surface records of all rows , most of them fuzzily match to hard .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]}

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

[['18 january 1998', 'hobart , australia', 'hard', 'dominique van roost', '6 - 3 , 6 - 2'], ['22 february 1998', 'hannover , germany', 'carpet ( i )', 'jana novotná', '6 - 0 , 3 - 6 , 7 - 5'], ['24 may 1998', 'madrid , spain', 'clay', 'dominique van roost', '3 - 6 , 6 - 4 , 6 - 0'], ['12 july 1998', 'maria lankowitz , austria', 'clay', 'gala león garcía', '6 - 2 , 4 - 6 , 6 - 3'], ['19 july 1998', 'palermo , italy', 'clay', 'barbara schett', '6 - 1 , 5 - 7 , 6 - 2'], ['10 january 1999', 'gold coast , australia', 'hard', 'mary pierce', '4 - 6 , 7 - 6 ( 5 ) , 6 - 2'], ['11 november 2001', 'pattaya city , thailand', 'hard', 'henrieta nagyová', '6 - 0 , 6 - 4'], ['20 october 2002', 'zürich , switzerland', 'carpet ( i )', 'lindsay davenport', '6 - 7 ( 5 ) , 7 - 6 ( 8 ) , 6 - 3'], ['8 january 2005', 'gold coast , australia', 'hard', 'samantha stosur', '1 - 6 , 6 - 3 , 7 - 5'], ['24 july 2005', 'cincinnati , usa', 'hard', 'akiko morigami', '6 - 4 , 6 - 0'], ['8 september 2008', 'bali , indonesia', 'hard', 'tamira paszek', '6 - 3 , 6 - 0']]

2008 - 09 portland trail blazers season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17058178-11.html.csv

unique

the portland trailblazers only loss came was on april 5 .

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

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

and { only { filter_eq { all_rows ; score ; l } } ; eq { hop { filter_eq { all_rows ; score ; l } ; date } ; april 5 } } = true

select the rows whose score record fuzzily matches to l . there is only one such row in the table . the date record of this unqiue row is april 5 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score_7': 7, 'l_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'april 5_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score_7': 'score', 'l_8': 'l', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'april 5_10': 'april 5'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], 'l_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'april 5_10': [3]}

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

[['75', 'april 3', 'oklahoma city', 'w 107 - 72 ( ot )', 'lamarcus aldridge ( 35 )', 'lamarcus aldridge ( 18 )', 'steve blake ( 10 )', 'ford center 19136', '48 - 27'], ['76', 'april 5', 'houston', 'l 88 - 102 ( ot )', 'lamarcus aldridge , brandon roy ( 22 )', 'lamarcus aldridge ( 9 )', 'brandon roy ( 6 )', 'toyota center 18214', '48 - 28'], ['77', 'april 7', 'memphis', 'w 96 - 93 ( ot )', 'brandon roy ( 24 )', 'lamarcus aldridge ( 8 )', 'brandon roy ( 4 )', 'fedexforum 10089', '49 - 28'], ['78', 'april 8', 'san antonio', 'w 95 - 83 ( ot )', 'brandon roy ( 26 )', 'joel przybilla ( 17 )', 'steve blake ( 7 )', 'at & t center 18797', '50 - 28'], ['79', 'april 10', 'la lakers', 'w 106 - 98 ( ot )', 'brandon roy ( 24 )', 'joel przybilla ( 13 )', 'brandon roy ( 8 )', 'rose garden 20681', '51 - 28'], ['80', 'april 11', 'la clippers', 'w 87 - 72 ( ot )', 'lamarcus aldridge ( 21 )', 'joel przybilla ( 14 )', 'steve blake ( 5 )', 'staples center 18321', '52 - 28'], ['81', 'april 13', 'oklahoma city', 'w 113 - 83 ( ot )', 'travis outlaw ( 21 )', 'joel przybilla ( 12 )', 'sergio rodríguez ( 8 )', 'rose garden 20655', '53 - 28']]

list of england national rugby union team results 1970 - 79

https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1970%E2%80%9379

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178924-2.html.csv

count

england played against scotland in rugby tournaments in 1971 two times .

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

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

eq { count { filter_eq { all_rows ; opposing teams ; scotland } } ; 2 } = true

select the rows whose opposing teams record fuzzily matches to scotland . 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, 'opposing teams_5': 5, 'scotland_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', 'opposing teams_5': 'opposing teams', 'scotland_6': 'scotland', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opposing teams_5': [0], 'scotland_6': [0], '2_7': [2]}

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

[['wales', '3', '16 / 01 / 1971', 'cardiff arms park , cardiff', 'five nations'], ['ireland', '6', '13 / 02 / 1971', 'lansdowne road , dublin', 'five nations'], ['france', '14', '27 / 02 / 1971', 'twickenham , london', 'five nations'], ['scotland', '16', '20 / 03 / 1971', 'twickenham , london', 'five nations'], ['scotland', '26', '27 / 03 / 1971', 'murrayfield , edinburgh', 'rfu centenary match'], ["rfu president 's xv", '28', '17 / 04 / 1971', 'twickenham , london', 'rfu centenary match']]

1990 - 91 atlanta hawks season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27882867-6.html.csv

unique

in the 1990-91 atlanta hawks season , the only game that took place at chicago stadium was on january 11 .

{'scope': 'all', 'row': '5', 'col': '8', 'col_other': '2', 'criterion': 'equal', 'value': 'chicago stadium', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'chicago stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to chicago stadium .', 'tostr': 'filter_eq { all_rows ; location attendance ; chicago stadium }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location attendance ; chicago stadium } }', 'tointer': 'select the rows whose location attendance record fuzzily matches to chicago stadium . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'chicago stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to chicago stadium .', 'tostr': 'filter_eq { all_rows ; location attendance ; chicago stadium }'}, 'date'], 'result': 'january 11', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location attendance ; chicago stadium } ; date }'}, 'january 11'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location attendance ; chicago stadium } ; date } ; january 11 }', 'tointer': 'the date record of this unqiue row is january 11 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location attendance ; chicago stadium } } ; eq { hop { filter_eq { all_rows ; location attendance ; chicago stadium } ; date } ; january 11 } } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to chicago stadium . there is only one such row in the table . the date record of this unqiue row is january 11 .'}

and { only { filter_eq { all_rows ; location attendance ; chicago stadium } } ; eq { hop { filter_eq { all_rows ; location attendance ; chicago stadium } ; date } ; january 11 } } = true

select the rows whose location attendance record fuzzily matches to chicago stadium . there is only one such row in the table . the date record of this unqiue row is january 11 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location attendance_7': 7, 'chicago stadium_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'january 11_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location attendance_7': 'location attendance', 'chicago stadium_8': 'chicago stadium', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'january 11_10': 'january 11'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location attendance_7': [0], 'chicago stadium_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'january 11_10': [3]}

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

[['29', 'january 2', 'la clippers', 'w 120 - 107', 'd wilkins ( 35 )', 'd wilkins ( 16 )', 'g rivers ( 11 )', 'omni coliseum 8733', '16 - 13'], ['30', 'january 4', 'indiana', 'w 111 - 96', 'd wilkins ( 36 )', 'm malone ( 11 )', 'g rivers , r robinson ( 5 )', 'omni coliseum 10124', '17 - 13'], ['31', 'january 5', 'minnesota', 'w 117 - 112 ( ot )', 'j battle ( 27 )', 'k willis ( 19 )', 'j koncak ( 7 )', 'omni coliseum 10988', '18 - 13'], ['32', 'january 8', 'san antonio', 'w 109 - 98', 'd wilkins ( 40 )', 'k willis ( 9 )', 'g rivers ( 10 )', 'omni coliseum 12608', '19 - 13'], ['33', 'january 11', 'chicago', 'l 96 - 99', 'd wilkins ( 23 )', 'd wilkins ( 12 )', 'j battle ( 7 )', 'chicago stadium 18676', '19 - 14'], ['34', 'january 12', 'new york', 'l 92 - 99', 'd wilkins ( 22 )', 'g rivers ( 8 )', 'g rivers , r robinson ( 6 )', 'madison square garden 17457', '19 - 15'], ['35', 'january 14', 'new york', 'w 96 - 82', 'd wilkins ( 26 )', 'd wilkins ( 16 )', 'j battle , s moncrief ( 4 )', 'omni coliseum 12612', '20 - 15'], ['36', 'january 15', 'indiana', 'w 117 - 106', 'd wilkins ( 28 )', 'd wilkins ( 12 )', 'j battle ( 8 )', 'market square arena 9531', '21 - 15'], ['37', 'january 18', 'chicago', 'w 114 - 105', 'd wilkins ( 34 )', 'm malone ( 12 )', 'g rivers ( 5 )', 'omni coliseum 16390', '22 - 15'], ['38', 'january 19', 'new jersey', 'w 114 - 84', 'k willis ( 24 )', 'k willis ( 17 )', 'a webb ( 6 )', 'omni coliseum 15758', '23 - 15'], ['39', 'january 22', 'miami', 'w 118 - 107', 'k willis ( 29 )', 'k willis ( 10 )', 'g rivers , a webb , d wilkins ( 7 )', 'omni coliseum 10440', '24 - 15'], ['40', 'january 23', 'washington', 'l 99 - 104', 'd wilkins ( 27 )', 'd wilkins ( 13 )', 'g rivers ( 7 )', 'capital centre 9830', '24 - 16'], ['41', 'january 26', 'seattle', 'l 102 - 103', 'd wilkins ( 43 )', 'd wilkins ( 10 )', 'a webb ( 9 )', 'seattle center coliseum 12792', '24 - 17'], ['42', 'january 28', 'portland', 'l 111 - 116', 'd wilkins ( 34 )', 'k willis ( 10 )', 'a webb ( 11 )', 'memorial coliseum 12884', '24 - 18'], ['43', 'january 29', 'utah', 'l 105 - 116', 'd wilkins ( 24 )', 'd wilkins ( 14 )', 'a webb ( 4 )', 'salt palace 12616', '24 - 19']]

zorro ( musical )

https://en.wikipedia.org/wiki/Zorro_%28musical%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17143308-1.html.csv

count

zorro ( musical ) had a record result of been nominated 4 times .

{'scope': 'all', 'criterion': 'equal', 'value': 'nominated', 'result': '4', 'col': '5', 'subset': None}

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

eq { count { filter_eq { all_rows ; result ; nominated } } ; 4 } = true

select the rows whose result record fuzzily matches to nominated . 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, 'result_5': 5, 'nominated_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', 'result_5': 'result', 'nominated_6': 'nominated', '4_7': '4'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'nominated_6': [0], '4_7': [2]}

['year', 'award', 'category', 'nominee', 'result']

[['2009', 'laurence olivier award', 'best new musical', 'best new musical', 'nominated'], ['2009', 'laurence olivier award', 'best actor in a musical', 'matt rawle', 'nominated'], ['2009', 'laurence olivier award', 'best actress in a musical', 'emma williams', 'nominated'], ['2009', 'laurence olivier award', 'best performance in a supporting role in a musical', 'lesli margherita', 'won'], ['2009', 'laurence olivier award', 'best theatre choreographer', 'rafael amargo', 'nominated']]

1996 senior pga tour

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11621873-4.html.csv

superlative

lee trevino had the highest earnings of any player in the 1996 senior pga tour .

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

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

eq { hop { argmax { all_rows ; earnings } ; player } ; lee trevino } = true

select the row whose earnings record of all rows is maximum . the player record of this row is lee trevino .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'earnings_5': 5, 'player_6': 6, 'lee trevino_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'earnings_5': 'earnings', 'player_6': 'player', 'lee trevino_7': 'lee trevino'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'earnings_5': [0], 'player_6': [1], 'lee trevino_7': [2]}

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

[['1', 'lee trevino', 'united states', '6715649', '27'], ['2', 'bob charles', 'new zealand', '6621207', '23'], ['3', 'jim colbert', 'united states', '6570797', '18'], ['4', 'dave stockton', 'united states', '5781417', '13'], ['5', 'chi chi rodriguez', 'puerto rico', '5696544', '22']]

2008 - 09 phoenix suns season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17340355-5.html.csv

count

during november of the 2008 - 09 season , the phoenix suns played 2 games against portland .

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

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

eq { count { filter_eq { all_rows ; team ; portland } } ; 2 } = true

select the rows whose team record fuzzily matches to portland . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'portland_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'portland_6': 'portland', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'portland_6': [0], '2_7': [2]}

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

[['3', 'november 1', 'portland', 'w 107 - 96 ( ot )', "amar ' e stoudemire ( 23 )", "amar ' e stoudemire ( 13 )", 'steve nash ( 7 )', 'us airways center 18422', '2 - 1'], ['4', 'november 4', 'new jersey', 'w 114 - 86 ( ot )', 'raja bell ( 22 )', 'matt barnes ( 7 )', 'steve nash ( 11 )', 'izod center 15230', '3 - 1'], ['5', 'november 5', 'indiana', 'w 113 - 103 ( ot )', "amar ' e stoudemire ( 49 )", "amar ' e stoudemire ( 11 )", "amar ' e stoudemire , steve nash ( 6 )", 'conseco fieldhouse 11660', '4 - 1'], ['6', 'november 7', 'chicago', 'l 83 - 100 ( ot )', "amar ' e stoudemire ( 26 )", "robin lopez , amar ' e stoudemire ( 7 )", 'steve nash ( 5 )', 'united center 21967', '4 - 2'], ['7', 'november 8', 'milwaukee', 'w 104 - 96 ( ot )', "shaquille o'neal ( 29 )", "shaquille o'neal , grant hill ( 11 )", 'steve nash ( 7 )', 'bradley center 17935', '5 - 2'], ['8', 'november 10', 'memphis', 'w 107 - 102 ( ot )', 'leandro barbosa ( 27 )', 'matt barnes ( 8 )', 'steve nash ( 6 )', 'us airways center 18422', '6 - 2'], ['9', 'november 12', 'houston', 'l 82 - 94 ( ot )', "leandro barbosa , shaquille o'neal ( 18 )", "shaquille o'neal ( 13 )", "shaquille o'neal , steve nash ( 3 )", 'us airways center 18422', '6 - 3'], ['10', 'november 14', 'sacramento', 'w 97 - 95 ( ot )', "shaquille o'neal ( 29 )", "shaquille o'neal ( 13 )", "shaquille o'neal ( 6 )", 'arco arena 12810', '7 - 3'], ['11', 'november 16', 'detroit', 'w 104 - 86 ( ot )', "amar ' e stoudemire ( 29 )", "amar ' e stoudemire ( 11 )", 'steve nash ( 7 )', 'us airways center 18422', '8 - 3'], ['12', 'november 17', 'utah', 'l 97 - 109 ( ot )', "amar ' e stoudemire ( 30 )", "amar ' e stoudemire ( 8 )", 'steve nash ( 8 )', 'energysolutions arena 19911', '8 - 4'], ['13', 'november 20', 'la lakers', 'l 92 - 105 ( ot )', "amar ' e stoudemire ( 21 )", "shaquille o'neal ( 9 )", 'steve nash ( 10 )', 'us airways center 18422', '8 - 5'], ['14', 'november 22', 'portland', 'w 102 - 92 ( ot )', "shaquille o'neal ( 19 )", "shaquille o'neal ( 17 )", 'steve nash ( 7 )', 'us airways center 18422', '9 - 5'], ['15', 'november 25', 'oklahoma city', 'w 99 - 98 ( ot )', "amar ' e stoudemire ( 22 )", 'steve nash ( 8 )', 'steve nash ( 15 )', 'ford center 19136', '10 - 5'], ['16', 'november 26', 'minnesota', 'w 110 - 102 ( ot )', 'steve nash ( 20 )', "shaquille o'neal ( 10 )", 'steve nash ( 6 )', 'target center 11708', '11 - 5'], ['17', 'november 28', 'miami', 'l 92 - 107 ( ot )', 'leandro barbosa ( 20 )', "shaquille o'neal ( 9 )", 'leandro barbosa ( 5 )', 'us airways center 18422', '11 - 6'], ['18', 'november 30', 'new jersey', 'l 109 - 117 ( ot )', 'steve nash ( 26 )', "amar ' e stoudemire ( 12 )", 'steve nash ( 9 )', 'us airways center 18422', '11 - 7']]

2008 oafl season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15764352-3.html.csv

ordinal

the kangaroos scored the most points at humber college north on 5-31-08 in the 2008 oafl season .

{'row': '2', 'col': '5', 'order': '1', 'col_other': '6', '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', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; score ; 1 }'}, 'ground'], 'result': 'humber college north', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; score ; 1 } ; ground }'}, 'humber college north'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; score ; 1 } ; ground } ; humber college north } = true', 'tointer': 'select the row whose score record of all rows is 1st maximum . the ground record of this row is humber college north .'}

eq { hop { nth_argmax { all_rows ; score ; 1 } ; ground } ; humber college north } = true

select the row whose score record of all rows is 1st maximum . the ground record of this row is humber college north .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, '1_6': 6, 'ground_7': 7, 'humber college north_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', '1_6': '1', 'ground_7': 'ground', 'humber college north_8': 'humber college north'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], '1_6': [0], 'ground_7': [1], 'humber college north_8': [2]}

['date', 'time', 'home', 'away', 'score', 'ground']

[['2008 - 05 - 31', '10:00', 'toronto downtown dingos', 'broadview hawks', '34 - 86', 'humber college north'], ['2008 - 05 - 31', '11:00', 'hamilton wildcats', 'etobicoke kangaroos', '52 - 110', 'humber college north'], ['2008 - 05 - 31', '14:00', 'ottawa swans', 'high park demons', '20 - 99', 'rideau carleton raceway'], ['2008 - 05 - 31', '14:00', 'guelph gargoyles', 'central blues', '65 - 19', 'magaret green park'], ['2008 - 05 - 31', '14:00', 'toronto eagles', 'toronto rebels', '106 - 35', 'humber college north']]

gilbert aldana

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17441930-2.html.csv

majority

the majority of gilbert aldana 's fights ended in wins for gilbert aldana .

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

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

most_eq { all_rows ; res ; win } = true

for the res records of all rows , most of them fuzzily match to win .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'res_3': 3, 'win_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'res_3': 'res', 'win_4': 'win'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'res_3': [0], 'win_4': [0]}

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

[['win', '6 - 2', 'rich beecroft', 'submission ( kimura )', 'ritc 90 - rage in the cage', '1', '0:26', 'arizona , united states'], ['loss', '5 - 2', 'cheick kongo', 'tko ( doctor stoppage )', 'ufc 61', '1', '4:13', 'nevada , united states'], ['loss', '5 - 1', 'paul buentello', 'tko ( strikes )', 'ufc 57', '2', '2:27', 'nevada , united states'], ['win', '5 - 0', 'chad armstrong', 'tko', 'ritc 75 - friday night fights', '1', '1:00', 'arizona , united states'], ['win', '4 - 0', 'melville calabaca', 'ko', 'ritc 70 - rage in the cage 70', '1', '0:30', 'arizona , united states'], ['win', '3 - 0', 'tim mcmullen', 'ko', 'ritc 65 - rage in the cage 65', '1', '0:15', 'arizona , united states'], ['win', '2 - 0', 'karl perkins', 'ko', 'ritc 62 - more punishment', '1', '1:55', 'arizona , united states'], ['win', '1 - 0', 'herb garcia', 'ko', 'ritc 61 - relentless', '1', '0:03', 'arizona , united states']]

jordi arrese

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1727920-2.html.csv

comparative

jordi arrese won a tennis tournament in bordeaux , france earlier than he won in san marino .

{'row_1': '2', 'row_2': '4', 'col': '2', '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', 'tournament', 'bordeaux , france'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to bordeaux , france .', 'tostr': 'filter_eq { all_rows ; tournament ; bordeaux , france }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; bordeaux , france } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to bordeaux , france . take the date record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'san marino'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to san marino .', 'tostr': 'filter_eq { all_rows ; tournament ; san marino }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; san marino } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to san marino . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; tournament ; bordeaux , france } ; date } ; hop { filter_eq { all_rows ; tournament ; san marino } ; date } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to bordeaux , france . take the date record of this row . select the rows whose tournament record fuzzily matches to san marino . take the date record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; tournament ; bordeaux , france } ; date } ; hop { filter_eq { all_rows ; tournament ; san marino } ; date } } = true

select the rows whose tournament record fuzzily matches to bordeaux , france . take the date record of this row . select the rows whose tournament record fuzzily matches to san marino . take the date record of this row . the first record is less than the second record .

5

5

{'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tournament_7': 7, 'bordeaux , france_8': 8, 'date_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'tournament_11': 11, 'san marino_12': 12, 'date_13': 13}

{'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'tournament_7': 'tournament', 'bordeaux , france_8': 'bordeaux , france', 'date_9': 'date', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tournament', 'san marino_12': 'san marino', 'date_13': 'date'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'tournament_7': [0], 'bordeaux , france_8': [0], 'date_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'tournament_11': [1], 'san marino_12': [1], 'date_13': [3]}

['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents in the final', 'score in the final']

[['runner - up', '1985', 'bologna , italy', 'clay', 'alberto tous', 'paolo canè simone colombo', '5 - 7 , 4 - 6'], ['winner', '1986', 'bordeaux , france', 'clay', 'david de miguel', 'ronald agénor mansour bahrami', '7 - 5 , 6 - 4'], ['winner', '1989', 'prague , czechoslovakia', 'clay', 'horst skoff', 'petr korda tomáš šmíd', '6 - 4 , 6 - 4'], ['winner', '1991', 'san marino', 'clay', 'carlos costa', 'christian miniussi diego pérez', '6 - 3 , 3 - 6 , 6 - 3'], ['runner - up', '1993', 'umag , croatia', 'clay', 'francisco roig', 'filip dewulf tom vanhoudt', '4 - 6 , 5 - 7'], ['runner - up', '1994', 'san marino', 'clay', 'renzo furlan', 'neil broad greg van emburgh', '4 - 6 , 6 - 7'], ['runner - up', '1994', 'bucharest , romania', 'clay', 'jose antonio conde', 'wayne arthurs simon youl', '4 - 6 , 4 - 6'], ['runner - up', '1995', 'oporto , portugal', 'clay', 'àlex corretja', 'tomás carbonell francisco roig', '3 - 6 , 6 - 7'], ['runner - up', '1995', 'kitzbühel , austria', 'clay', 'wayne arthurs', 'francisco montana greg van emburgh', '7 - 6 , 3 - 6 , 6 - 7'], ['winner', '1995', 'san marino', 'clay', 'andrew kratzmann', 'pablo albano federico mordegan', '7 - 6 , 3 - 6 , 6 - 2']]

zhang chunhui

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11409274-2.html.csv

ordinal

the 2nd to last competition for zhang chunhui was when the venue was at olympic stadium in japan .

{'row': '7', 'col': '1', 'order': '7', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '7'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 7 }'}, 'venue'], 'result': 'olympic stadium , tokyo , japan', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 7 } ; venue }'}, 'olympic stadium , tokyo , japan'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 7 } ; venue } ; olympic stadium , tokyo , japan } = true', 'tointer': 'select the row whose date record of all rows is 7th minimum . the venue record of this row is olympic stadium , tokyo , japan .'}

eq { hop { nth_argmin { all_rows ; date ; 7 } ; venue } ; olympic stadium , tokyo , japan } = true

select the row whose date record of all rows is 7th minimum . the venue record of this row is olympic stadium , tokyo , japan .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '7_6': 6, 'venue_7': 7, 'olympic stadium , tokyo , japan_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '7_6': '7', 'venue_7': 'venue', 'olympic stadium , tokyo , japan_8': 'olympic stadium , tokyo , japan'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '7_6': [0], 'venue_7': [1], 'olympic stadium , tokyo , japan_8': [2]}

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

[['14 january 2009', 'hong kong stadium , hong kong', '2 - 1', '0', 'friendly'], ['21 january 2009', 'hong kong stadium , hong kong', '1 - 3', '0', '2011 afc asian cup qualification'], ['28 january 2009', "ali muhesen stadium , sana'a , yemen", '0 - 1', '0', '2011 afc asian cup qualification'], ['27 august 2009', 'world games stadium , kaohsiung , taiwan', '12 - 0', '0', '2010 east asian football championship semi - final'], ['9 october 2009', 'outsourcing stadium , shizuoka , japan', '0 - 6', '0', '2011 afc asian cup qualification'], ['18 november 2009', 'hong kong stadium , hong kong', '0 - 4', '0', '2011 afc asian cup qualification'], ['7 february 2010', 'olympic stadium , tokyo , japan', '0 - 5', '0', '2010 east asian football championship'], ['17 november 2010', 'hong kong stadium , hong kong', '0 - 7', '0', 'friendly']]

1960 - 61 segunda división

https://en.wikipedia.org/wiki/1960%E2%80%9361_Segunda_Divisi%C3%B3n

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17715861-2.html.csv

ordinal

in the 1960-61 segunda división , among teams with 15 or more losses , cd tarrasa had the highest difference between goals for and goals against .

{'scope': 'subset', 'row': '16', 'col': '10', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '7', 'criterion': 'greater_than_eq', 'value': '15'}}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'losses', '15'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; losses ; 15 }', 'tointer': 'select the rows whose losses record is greater than or equal to 15 .'}, 'goal difference', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_greater_eq { all_rows ; losses ; 15 } ; goal difference ; 1 }'}, 'club'], 'result': 'cd tarrasa', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_greater_eq { all_rows ; losses ; 15 } ; goal difference ; 1 } ; club }'}, 'cd tarrasa'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_greater_eq { all_rows ; losses ; 15 } ; goal difference ; 1 } ; club } ; cd tarrasa } = true', 'tointer': 'select the rows whose losses record is greater than or equal to 15 . select the row whose goal difference record of these rows is 1st minimum . the club record of this row is cd tarrasa .'}

eq { hop { nth_argmin { filter_greater_eq { all_rows ; losses ; 15 } ; goal difference ; 1 } ; club } ; cd tarrasa } = true

select the rows whose losses record is greater than or equal to 15 . select the row whose goal difference record of these rows is 1st minimum . the club record of this row is cd tarrasa .

4

4

{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'losses_6': 6, '15_7': 7, 'goal difference_8': 8, '1_9': 9, 'club_10': 10, 'cd tarrasa_11': 11}

{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'losses_6': 'losses', '15_7': '15', 'goal difference_8': 'goal difference', '1_9': '1', 'club_10': 'club', 'cd tarrasa_11': 'cd tarrasa'}

{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'losses_6': [0], '15_7': [0], 'goal difference_8': [1], '1_9': [1], 'club_10': [2], 'cd tarrasa_11': [3]}

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

[['1', 'ca osasuna', '30', '46', '21', '4', '5', '83', '25', '+ 58'], ['2', 'rc celta de vigo', '30', '40', '17', '6', '7', '56', '30', '+ 26'], ['3', 'deportivo la coruña', '30', '36', '15', '6', '9', '68', '47', '+ 21'], ['4', 'cd orense', '30', '36', '14', '8', '8', '45', '36', '+ 9'], ['5', 'pontevedra cf', '30', '31', '11', '9', '10', '39', '40', '- 1'], ['6', 'cd sabadell cf', '30', '31', '11', '9', '10', '30', '40', '- 10'], ['7', 'cultural leonesa', '30', '30', '11', '8', '11', '39', '42', '- 3'], ['8', 'cd basconia', '30', '29', '14', '1', '15', '41', '57', '- 16'], ['9', 'san sebastián cf', '30', '29', '11', '7', '12', '51', '50', '+ 1'], ['10', 'ud salamanca', '30', '29', '11', '7', '12', '42', '36', '+ 6'], ['11', 'sd indauchu', '30', '27', '12', '3', '15', '46', '59', '- 13'], ['12', 'cd condal 1', '30', '26', '8', '10', '12', '44', '49', '- 5'], ['13', 'real gijón', '30', '25', '10', '5', '15', '41', '53', '- 12'], ['14', 'club sestao', '30', '24', '8', '8', '14', '35', '51', '- 16'], ['15', 'baracaldo ah', '30', '22', '7', '8', '15', '33', '51', '- 18'], ['16', 'cd tarrasa', '30', '19', '5', '9', '16', '33', '60', '- 27']]

ednilson

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17226452-1.html.csv

count

ednilson played in teams in portugal for 5 consecutive years .

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

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'portugal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to portugal .', 'tostr': 'filter_eq { all_rows ; country ; portugal }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; portugal } }', 'tointer': 'select the rows whose country record fuzzily matches to portugal . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; portugal } } ; 5 } = true', 'tointer': 'select the rows whose country record fuzzily matches to portugal . the number of such rows is 5 .'}

eq { count { filter_eq { all_rows ; country ; portugal } } ; 5 } = true

select the rows whose country record fuzzily matches to portugal . the number of such rows is 5 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'portugal_6': 6, '5_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'portugal_6': 'portugal', '5_7': '5'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'portugal_6': [0], '5_7': [2]}

['season', 'team', 'country', 'division', 'apps', 'goals']

[['1999 - 00', 'roma', 'italy', '1', '1', '0'], ['2000 - 01', 'benfica', 'portugal', '1', '13', '0'], ['2001 - 02', 'benfica', 'portugal', '1', '22', '0'], ['2002 - 03', 'benfica', 'portugal', '1', '8', '0'], ['2003 - 04', 'vitória guimarães', 'portugal', '1', '8', '0'], ['2004 - 05', 'gil vicente', 'portugal', '1', '20', '0'], ['2005 - 06', 'ofi crete', 'greece', '1', '4', '0'], ['2006 - 07', 'ofi crete', 'greece', '1', '13', '0'], ['2007 - 08', 'partizan', 'serbia', '1', '14', '0'], ['2008 - 09', 'aek larnaca', 'cyprus', '1', '5', '0'], ['2009 - 10', 'dinamo tbilisi', 'georgia', '1', '29', '0']]

acc - big ten challenge

https://en.wikipedia.org/wiki/ACC%E2%80%93Big_Ten_Challenge

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1672976-1.html.csv

superlative

the georgia tech yellow jackets have the highest amount of losses in the acc - big ten challenge .

{'scope': 'all', 'col_superlative': '3', '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', 'loss'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; loss }'}, 'institution'], 'result': 'georgia tech yellow jackets', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; loss } ; institution }'}, 'georgia tech yellow jackets'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; loss } ; institution } ; georgia tech yellow jackets } = true', 'tointer': 'select the row whose loss record of all rows is maximum . the institution record of this row is georgia tech yellow jackets .'}

eq { hop { argmax { all_rows ; loss } ; institution } ; georgia tech yellow jackets } = true

select the row whose loss record of all rows is maximum . the institution record of this row is georgia tech yellow jackets .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'loss_5': 5, 'institution_6': 6, 'georgia tech yellow jackets_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'loss_5': 'loss', 'institution_6': 'institution', 'georgia tech yellow jackets_7': 'georgia tech yellow jackets'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'loss_5': [0], 'institution_6': [1], 'georgia tech yellow jackets_7': [2]}

['institution', 'wins', 'loss', 'home wins', 'home losses', 'away wins', 'away losses', 'neutral wins', 'neutral losses']

[['boston college eagles', '6', '1', '3', '1', '3', '0', '0', '0'], ['clemson tigers', '9', '5', '4', '3', '5', '2', '0', '0'], ['duke blue devils', '12', '2', '5', '0', '3', '2', '4', '0'], ['florida state seminoles', '6', '8', '4', '3', '2', '5', '0', '0'], ['georgia tech yellow jackets', '4', '9', '3', '2', '1', '6', '0', '1'], ['maryland terrapins', '10', '4', '5', '1', '4', '1', '1', '2'], ['miami hurricanes', '2', '4', '2', '1', '0', '3', '0', '0'], ['north carolina tar heels', '7', '7', '3', '3', '2', '4', '2', '0'], ['nc state wolfpack', '5', '8', '4', '2', '1', '6', '0', '0'], ['notre dame fighting irish', '0', '0', '0', '0', '0', '0', '0', '0'], ['pitt panthers', '0', '0', '0', '0', '0', '0', '0', '0'], ['syracuse orange', '0', '0', '0', '0', '0', '0', '0', '0'], ['virginia cavaliers', '8', '5', '5', '1', '3', '4', '0', '0'], ['virginia tech hokies', '3', '5', '2', '2', '1', '3', '0', '0'], ['wake forest demon deacons', '10', '3', '6', '1', '4', '2', '0', '0'], ['overall', '82', '61', '46', '20', '29', '38', '7', '3']]

1990 u.s. open ( golf )

https://en.wikipedia.org/wiki/1990_U.S._Open_%28golf%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17129548-4.html.csv

aggregation

the average number of strokes to par at the 1990 u.s. open was -5.6 .

{'scope': 'all', 'col': '5', 'type': 'average', 'result': '-5.6', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'to par'], 'result': '-5.6', 'ind': 0, 'tostr': 'avg { all_rows ; to par }'}, '-5.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; to par } ; -5.6 } = true', 'tointer': 'the average of the to par record of all rows is -5.6 .'}

round_eq { avg { all_rows ; to par } ; -5.6 } = true

the average of the to par record of all rows is -5.6 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'to par_4': 4, '-5.6_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'to par_4': 'to par', '-5.6_5': '-5.6'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'to par_4': [0], '-5.6_5': [1]}

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

[['1', 'tim simpson', 'united states', '66 + 69 = 135', '- 9'], ['2', 'jeff sluman', 'united states', '66 + 70 = 136', '- 8'], ['3', 'mike donald', 'united states', '67 + 70 = 137', '- 7'], ['4', 'mark brooks', 'united states', '68 + 70 = 138', '- 6'], ['t5', 'hale irwin', 'united states', '69 + 70 = 139', '- 5'], ['t5', 'scott simpson', 'united states', '66 + 73 = 139', '- 5'], ['t7', 'billy ray brown', 'united states', '69 + 71 = 140', '- 4'], ['t7', 'jim gallagher , jr', 'united states', '71 + 69 = 140', '- 4'], ['t7', 'john huston', 'united states', '68 + 72 = 140', '- 4'], ['t7', 'ian woosnam', 'wales', '70 + 70 = 140', '- 4']]

lt & sr 37 class

https://en.wikipedia.org/wiki/LT%26SR_37_Class

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20391799-1.html.csv

unique

the shoeburyness lt & sr 37 class locomotive was the only one withdrawn in 1952 .

{'scope': 'all', 'row': '9', 'col': '8', 'col_other': '2', 'criterion': 'equal', 'value': '1952', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'withdrawn', '1952'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose withdrawn record is equal to 1952 .', 'tostr': 'filter_eq { all_rows ; withdrawn ; 1952 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; withdrawn ; 1952 } }', 'tointer': 'select the rows whose withdrawn record is equal to 1952 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'withdrawn', '1952'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose withdrawn record is equal to 1952 .', 'tostr': 'filter_eq { all_rows ; withdrawn ; 1952 }'}, 'ltsr name'], 'result': 'shoeburyness', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; withdrawn ; 1952 } ; ltsr name }'}, 'shoeburyness'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; withdrawn ; 1952 } ; ltsr name } ; shoeburyness }', 'tointer': 'the ltsr name record of this unqiue row is shoeburyness .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; withdrawn ; 1952 } } ; eq { hop { filter_eq { all_rows ; withdrawn ; 1952 } ; ltsr name } ; shoeburyness } } = true', 'tointer': 'select the rows whose withdrawn record is equal to 1952 . there is only one such row in the table . the ltsr name record of this unqiue row is shoeburyness .'}

and { only { filter_eq { all_rows ; withdrawn ; 1952 } } ; eq { hop { filter_eq { all_rows ; withdrawn ; 1952 } ; ltsr name } ; shoeburyness } } = true

select the rows whose withdrawn record is equal to 1952 . there is only one such row in the table . the ltsr name record of this unqiue row is shoeburyness .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'withdrawn_7': 7, '1952_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'ltsr name_9': 9, 'shoeburyness_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'withdrawn_7': 'withdrawn', '1952_8': '1952', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'ltsr name_9': 'ltsr name', 'shoeburyness_10': 'shoeburyness'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'withdrawn_7': [0], '1952_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'ltsr name_9': [2], 'shoeburyness_10': [3]}

['ltsr no', 'ltsr name', 'builder', 'built', 'mr no', 'lms 1930 no', 'br no', 'withdrawn']

[['37', 'woodgrange', 'ss 4245', '1897', '2146', '2135', '41953', '1951'], ['38', 'westcliff', 'ss 4246', '1897', '2147', '2136', '41954', '1951'], ['39', 'forest gate', 'ss 4247', '1897', '2148', '2137', '41955', '1951'], ['40', 'benfleet', 'ss 4248', '1897', '2149', '2138', '41956', '1951'], ['41', 'leytonstone', 'ss 4249', '1897', '2150', '2139', '41957', '1951'], ['42', 'east horndon', 'ss 4250', '1897', '2151', '2140', '41958', '1951'], ['43', 'great ilford', 'dübs 3666', '1898', '2152', '2141', '41959', '1951'], ['44', 'prittlewell', 'dübs 3667', '1898', '2153', '2142', '41960', '1951'], ['45', 'shoeburyness', 'dübs 3668', '1898', '2154', '2143', '41961', '1952'], ['46', 'southchurch', 'dübs 3669', '1898', '2155', '2144', '41962', '1951'], ['47', 'stratford', 'dübs 3670', '1898', '2156', '2145', '41963', '1951']]

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

comparative

sírio libanês played one less game than jardim américa .

{'row_1': '5', 'row_2': '6', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None}

{'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'sírio libanês'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to sírio libanês .', 'tostr': 'filter_eq { all_rows ; team ; sírio libanês }'}, 'played'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; sírio libanês } ; played }', 'tointer': 'select the rows whose team record fuzzily matches to sírio libanês . take the played record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'jardim américa'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to jardim américa .', 'tostr': 'filter_eq { all_rows ; team ; jardim américa }'}, 'played'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; jardim américa } ; played }', 'tointer': 'select the rows whose team record fuzzily matches to jardim américa . take the played record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; hop { filter_eq { all_rows ; team ; jardim américa } ; played } }', 'tointer': 'select the rows whose team record fuzzily matches to sírio libanês . take the played record of this row . select the rows whose team record fuzzily matches to jardim américa . take the played record of this row . the first record is less than the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'sírio libanês'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to sírio libanês .', 'tostr': 'filter_eq { all_rows ; team ; sírio libanês }'}, 'played'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; sírio libanês } ; played }', 'tointer': 'select the rows whose team record fuzzily matches to sírio libanês . take the played record of this row .'}, '12'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; 12 }', 'tointer': 'the played record of the first row is 12 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'jardim américa'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to jardim américa .', 'tostr': 'filter_eq { all_rows ; team ; jardim américa }'}, 'played'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; jardim américa } ; played }', 'tointer': 'select the rows whose team record fuzzily matches to jardim américa . take the played record of this row .'}, '13'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; team ; jardim américa } ; played } ; 13 }', 'tointer': 'the played record of the second row is 13 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; 12 } ; eq { hop { filter_eq { all_rows ; team ; jardim américa } ; played } ; 13 } }', 'tointer': 'the played record of the first row is 12 . the played record of the second row is 13 .'}], 'result': True, 'ind': 8, 'tostr': 'and { less { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; hop { filter_eq { all_rows ; team ; jardim américa } ; played } } ; and { eq { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; 12 } ; eq { hop { filter_eq { all_rows ; team ; jardim américa } ; played } ; 13 } } } = true', 'tointer': 'select the rows whose team record fuzzily matches to sírio libanês . take the played record of this row . select the rows whose team record fuzzily matches to jardim américa . take the played record of this row . the first record is less than the second record . the played record of the first row is 12 . the played record of the second row is 13 .'}

and { less { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; hop { filter_eq { all_rows ; team ; jardim américa } ; played } } ; and { eq { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; 12 } ; eq { hop { filter_eq { all_rows ; team ; jardim américa } ; played } ; 13 } } } = true

select the rows whose team record fuzzily matches to sírio libanês . take the played record of this row . select the rows whose team record fuzzily matches to jardim américa . take the played record of this row . the first record is less than the second record . the played record of the first row is 12 . the played record of the second row is 13 .

13

9

{'and_8': 8, 'result_9': 9, 'less_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'team_11': 11, 'sírio libanês_12': 12, 'played_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'team_15': 15, 'jardim américa_16': 16, 'played_17': 17, 'and_7': 7, 'eq_5': 5, '12_18': 18, 'eq_6': 6, '13_19': 19}

{'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'sírio libanês_12': 'sírio libanês', 'played_13': 'played', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'team_15': 'team', 'jardim américa_16': 'jardim américa', 'played_17': 'played', 'and_7': 'and', 'eq_5': 'eq', '12_18': '12', 'eq_6': 'eq', '13_19': '13'}

{'and_8': [9], 'result_9': [], 'less_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'team_11': [0], 'sírio libanês_12': [0], 'played_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'team_15': [1], 'jardim américa_16': [1], 'played_17': [3], 'and_7': [8], 'eq_5': [7], '12_18': [5], 'eq_6': [7], '13_19': [6]}

['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']]

list of australian football league pre - season and night series premiers

https://en.wikipedia.org/wiki/List_of_Australian_Football_League_pre-season_and_night_series_premiers

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1139835-9.html.csv

unique

the geelong premier was the only time that the venue was etihad stadium .

{'scope': 'all', 'row': '11', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'etihad stadium', 'subset': None}

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

and { only { filter_eq { all_rows ; venue ; etihad stadium } } ; eq { hop { filter_eq { all_rows ; venue ; etihad stadium } ; premier } ; geelong } } = true

select the rows whose venue record fuzzily matches to etihad stadium . there is only one such row in the table . the premier record of this unqiue row is geelong .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'etihad stadium_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'premier_9': 9, 'geelong_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'etihad stadium_8': 'etihad stadium', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'premier_9': 'premier', 'geelong_10': 'geelong'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'etihad stadium_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'premier_9': [2], 'geelong_10': [3]}

['season', 'premier', 'runner up', 'score', 'venue', 'attendance', 'premiership']

[['1984', 'essendon', 'sydney swans', '13.11 ( 89 ) - 5.8 ( 38 )', 'waverley park', '30824', 'night series'], ['1984', 'essendon', 'hawthorn', '14.21 ( 105 ) - 12.9 ( 81 )', 'mcg', '92685', 'vfl grand final'], ['1986', 'hawthorn', 'carlton', '9.12 ( 66 ) - 5.6 ( 36 )', 'waverley park', '19627', 'night series'], ['1986', 'hawthorn', 'carlton', '16.14 ( 110 ) - 9.14 ( 68 )', 'mcg', '101861', 'vfl grand final'], ['1988', 'hawthorn', 'geelong', '10.10 ( 70 ) - 9.13 ( 67 )', 'waverley park', '35803', 'pre - season cup'], ['1988', 'hawthorn', 'melbourne', '22.20 ( 152 ) - 6.20 ( 56 )', 'mcg', '93754', 'vfl grand final'], ['1993', 'essendon', 'richmond', '14.18 ( 102 ) - 11.13 ( 79 )', 'waverley park', '75533', 'pre - season cup'], ['1993', 'essendon', 'carlton carlton', '20.13 ( 133 ) - 13.11 ( 89 )', 'mcg', '96862', 'afl grand final'], ['2000', 'essendon', 'north melbourne', '16.21 ( 117 ) - 11.10 ( 76 )', 'mcg', '56720', 'pre - season cup'], ['2000', 'essendon', 'melbourne', '19.21 ( 135 ) - 11.9 ( 75 )', 'mcg', '96249', 'afl grand final'], ['2009', 'geelong', 'collingwood', '0.18.19 ( 127 ) - 1.6.6 ( 51 )', 'etihad stadium', '37277', 'pre - season cup']]

three rivers conference ( indiana )

https://en.wikipedia.org/wiki/Three_Rivers_Conference_%28Indiana%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15176211-2.html.csv

comparative

triton joined the three rivers conference before oak hill joined the conference .

{'row_1': '3', 'row_2': '5', 'col': '5', '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', 'school', 'triton'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to triton .', 'tostr': 'filter_eq { all_rows ; school ; triton }'}, 'year joined'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school ; triton } ; year joined }', 'tointer': 'select the rows whose school record fuzzily matches to triton . take the year joined record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'oak hill'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose school record fuzzily matches to oak hill .', 'tostr': 'filter_eq { all_rows ; school ; oak hill }'}, 'year joined'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; school ; oak hill } ; year joined }', 'tointer': 'select the rows whose school record fuzzily matches to oak hill . take the year joined record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; school ; triton } ; year joined } ; hop { filter_eq { all_rows ; school ; oak hill } ; year joined } } = true', 'tointer': 'select the rows whose school record fuzzily matches to triton . take the year joined record of this row . select the rows whose school record fuzzily matches to oak hill . take the year joined record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; school ; triton } ; year joined } ; hop { filter_eq { all_rows ; school ; oak hill } ; year joined } } = true

select the rows whose school record fuzzily matches to triton . take the year joined record of this row . select the rows whose school record fuzzily matches to oak hill . take the year joined 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, 'school_7': 7, 'triton_8': 8, 'year joined_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'school_11': 11, 'oak hill_12': 12, 'year joined_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', 'school_7': 'school', 'triton_8': 'triton', 'year joined_9': 'year joined', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'school_11': 'school', 'oak hill_12': 'oak hill', 'year joined_13': 'year joined'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'school_7': [0], 'triton_8': [0], 'year joined_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'school_11': [1], 'oak hill_12': [1], 'year joined_13': [3]}

['school', 'location', 'mascot', 'county', 'year joined', 'previous conference', 'year left', 'new conference']

[['caston', 'fulton', 'comets', '25 fulton', '1971', 'independents', '1978', 'joined midwest'], ['culver community', 'culver', 'cavaliers', '50 marshall', '1971', 'independents', '1976', 'independents'], ['triton', 'bourbon', 'trojans', '50 marshall', '1971', 'independent', '1980', 'joined northern state'], ['eastern ( greentown )', 'greentown', 'comets', '34 howard', '1980', 'mid - indiana', '1987', 'joined mid - indiana'], ['oak hill', 'converse', 'golden eagles', '27 grant', '1980', 'mid - indiana', '2006', 'joined central indiana']]

united states house of representatives elections , 1974

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1974

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341690-20.html.csv

majority

all of the maryland incumbents in the 1974 united states house of representatives elections were re-elected .

{'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 're-elected', 'subset': None}

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

all_eq { all_rows ; result ; re-elected } = true

for the result records of all rows , all of them fuzzily match to re-elected .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 're-elected_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 're-elected_4': 're-elected'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 're-elected_4': [0]}

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

[['maryland 1', 'robert bauman', 'republican', '1973', 're - elected', 'robert bauman ( r ) 53.0 % thomas j hatem ( d ) 47.0 %'], ['maryland 2', 'clarence long', 'democratic', '1962', 're - elected', 'clarence long ( d ) 77.1 % john m seney ( r ) 22.9 %'], ['maryland 4', 'marjorie holt', 'republican', '1972', 're - elected', 'marjorie holt ( r ) 58.1 % fred l wineland ( d ) 41.9 %'], ['maryland 6', 'goodloe byron', 'democratic', '1970', 're - elected', 'goodloe byron ( d ) 73.7 % elton r wampler ( r ) 26.3 %'], ['maryland 7', 'parren mitchell', 'democratic', '1970', 're - elected', 'parren mitchell ( d ) unopposed']]

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

comparative

merrillville joined the duneland athletic conference before laporte did .

{'row_1': '5', 'row_2': '4', 'col': '8', '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', 'school', 'merrillville'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to merrillville .', 'tostr': 'filter_eq { all_rows ; school ; merrillville }'}, 'year joined'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school ; merrillville } ; year joined }', 'tointer': 'select the rows whose school record fuzzily matches to merrillville . take the year joined record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'laporte'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose school record fuzzily matches to laporte .', 'tostr': 'filter_eq { all_rows ; school ; laporte }'}, 'year joined'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; school ; laporte } ; year joined }', 'tointer': 'select the rows whose school record fuzzily matches to laporte . take the year joined record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; school ; merrillville } ; year joined } ; hop { filter_eq { all_rows ; school ; laporte } ; year joined } } = true', 'tointer': 'select the rows whose school record fuzzily matches to merrillville . take the year joined record of this row . select the rows whose school record fuzzily matches to laporte . take the year joined record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; school ; merrillville } ; year joined } ; hop { filter_eq { all_rows ; school ; laporte } ; year joined } } = true

select the rows whose school record fuzzily matches to merrillville . take the year joined record of this row . select the rows whose school record fuzzily matches to laporte . take the year joined 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, 'school_7': 7, 'merrillville_8': 8, 'year joined_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'school_11': 11, 'laporte_12': 12, 'year joined_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', 'school_7': 'school', 'merrillville_8': 'merrillville', 'year joined_9': 'year joined', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'school_11': 'school', 'laporte_12': 'laporte', 'year joined_13': 'year joined'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'school_7': [0], 'merrillville_8': [0], 'year joined_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'school_11': [1], 'laporte_12': [1], 'year joined_13': [3]}

['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']]

virginia wade

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-177273-2.html.csv

count

virginia wade participated in the us open tournament six times .

{'scope': 'all', 'criterion': 'equal', 'value': 'us open', 'result': '6', 'col': '3', 'subset': None}

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

eq { count { filter_eq { all_rows ; championship ; us open } } ; 6 } = true

select the rows whose championship record fuzzily matches to us open . 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, 'championship_5': 5, 'us open_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', 'championship_5': 'championship', 'us open_6': 'us open', '6_7': '6'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'championship_5': [0], 'us open_6': [0], '6_7': [2]}

['outcome', 'year', 'championship', 'surface', 'partner', 'opponents', 'score']

[['runner - up', '1969', 'us open', 'grass', 'margaret court', 'françoise dürr darlene hard', '0 - 6 , 6 - 4 , 6 - 4'], ['runner - up', '1970', 'wimbledon', 'grass', 'françoise dürr', 'rosie casals billie jean king', '6 - 2 , 6 - 3'], ['runner - up', '1970', 'us open', 'grass', 'rosie casals', 'margaret court judy tegart dalton', '6 - 3 , 6 - 4'], ['runner - up', '1972', 'us open', 'grass', 'margaret court', 'françoise dürr betty stöve', '6 - 3 , 1 - 6 , 6 - 3'], ['winner', '1973', 'australian open', 'grass', 'margaret court', 'kerry harris kerry melville', '6 - 4 , 6 - 4'], ['winner', '1973', 'french open', 'clay', 'margaret court', 'françoise dürr betty stöve', '6 - 2 , 6 - 3'], ['winner', '1973', 'us open', 'grass', 'margaret court', 'rosie casals billie jean king', '2 - 6 , 6 - 3 , 7 - 5'], ['winner', '1975', 'us open', 'clay', 'margaret court', 'rosie casals billie jean king', '7 - 5 , 2 - 6 , 7 - 6 ( 5 )'], ['runner - up', '1976', 'us open', 'clay', 'olga morozova', 'linky boshoff ilana kloss', '6 - 1 , 6 - 4'], ['runner - up', '1979', 'french open', 'clay', 'françoise dürr', 'betty stöve wendy turnbull', '3 - 6 , 7 - 5 , 6 - 4']]

fiba oceania championship for women

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13150131-4.html.csv

superlative

in the fiba oceania championship for women , the highest number of gold medals was won by the holder of rank 1 .

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

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

eq { hop { argmax { all_rows ; gold } ; rank } ; 1 } = true

select the row whose gold record of all rows is maximum . the rank record of this row is 1 .

3

3

{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'gold_5': 5, 'rank_6': 6, '1_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'gold_5': 'gold', 'rank_6': 'rank', '1_7': '1'}

{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'gold_5': [0], 'rank_6': [1], '1_7': [2]}

['rank', 'gold', 'silver', 'bronze', 'total']

[['1', '3', '0', '0', '3'], ['2', '1', '3', '1', '5'], ['3', '1', '0', '0', '1'], ['5', '0', '2', '4', '6'], ['6', '0', '1', '1', '2']]

marc girardelli

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1376129-1.html.csv

majority

marc giradielli finished top 10 in season ranking for most of his career .

{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10', 'subset': None}

{'func': 'most_less', 'args': ['all_rows', 'overall', '10'], 'result': True, 'ind': 0, 'tointer': 'for the overall records of all rows , most of them are less than 10 .', 'tostr': 'most_less { all_rows ; overall ; 10 } = true'}

most_less { all_rows ; overall ; 10 } = true

for the overall records of all rows , most of them are less than 10 .

1

1

{'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'overall_3': 3, '10_4': 4}

{'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'overall_3': 'overall', '10_4': '10'}

{'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'overall_3': [0], '10_4': [0]}

['season', 'overall', 'slalom', 'giant slalom', 'super g', 'downhill', 'combined']

[['1980', '84', '-', '32', 'not run', '-', '-'], ['1981', '26', '15', '23', 'not run', '-', '-'], ['1982', '6', '8', '3', 'not run', '-', '-'], ['1983', '4', '7', '6', 'not awarded', '-', '3'], ['1984', '3', '1', '4', 'not awarded', '-', '34'], ['1985', '1', '1', '1', 'not awarded', '19', '-'], ['1986', '1', '11', '5', '3', '4', '2'], ['1987', '2', '28', '5', '2', '10', '-'], ['1988', '5', '23', '13', '4', '7', '-'], ['1989', '1', '3', '5', '5', '1', '1'], ['1990', '25', '15', '12', '-', '-', '-'], ['1991', '1', '1', '3', '10', '28', '1'], ['1992', '3', '12', '7', '2', '13', '11'], ['1993', '1', '13', '3', '5', '6', '1'], ['1994', '2', '29', '19', '2', '1', '-'], ['1995', '4', '9', '18', '10', '24', '1'], ['1996', '22', '20', '23', '51', '47', '2'], ['1997', '115', '58', '49', '-', '-', '-']]

2008 - 09 croatian cup

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18828647-1.html.csv

count

two of the rounds had 16 as the number of fixtures .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': '16', 'result': '2', 'col': '3', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'number of fixtures', '16'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose number of fixtures record fuzzily matches to 16 .', 'tostr': 'filter_eq { all_rows ; number of fixtures ; 16 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; number of fixtures ; 16 } }', 'tointer': 'select the rows whose number of fixtures record fuzzily matches to 16 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; number of fixtures ; 16 } } ; 2 } = true', 'tointer': 'select the rows whose number of fixtures record fuzzily matches to 16 . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; number of fixtures ; 16 } } ; 2 } = true

select the rows whose number of fixtures record fuzzily matches to 16 . 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, 'number of fixtures_5': 5, '16_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', 'number of fixtures_5': 'number of fixtures', '16_6': '16', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'number of fixtures_5': [0], '16_6': [0], '2_7': [2]}

['round', 'main date', 'number of fixtures', 'clubs', 'new entries this round']

[['preliminary round', '27 august 2008', '16', '48 → 32', 'none'], ['first round', '23 and 24 september 2008', '16', '32 → 16', '16'], ['second round', '29 october 2008', '8', '16 → 8', 'none'], ['quarter - finals', '12 and 26 november 2008', '8', '8 → 4', 'none'], ['semi - finals', '4 and 18 march 2009', '4', '4 → 2', 'none'], ['final', '13 and 28 may 2009', '2', '2 → 1', 'none']]

2006 sydney roosters season

https://en.wikipedia.org/wiki/2006_Sydney_Roosters_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18838673-1.html.csv

unique

the game against the north queensland cowboys was the only one played at dairy farmers stadium .

{'scope': 'all', 'row': '8', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'dairy farmers stadium', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'dairy farmers stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to dairy farmers stadium .', 'tostr': 'filter_eq { all_rows ; venue ; dairy farmers stadium }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; dairy farmers stadium } }', 'tointer': 'select the rows whose venue record fuzzily matches to dairy farmers stadium . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'dairy farmers stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to dairy farmers stadium .', 'tostr': 'filter_eq { all_rows ; venue ; dairy farmers stadium }'}, 'opponent'], 'result': 'north queensland cowboys', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; dairy farmers stadium } ; opponent }'}, 'north queensland cowboys'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; dairy farmers stadium } ; opponent } ; north queensland cowboys }', 'tointer': 'the opponent record of this unqiue row is north queensland cowboys .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; venue ; dairy farmers stadium } } ; eq { hop { filter_eq { all_rows ; venue ; dairy farmers stadium } ; opponent } ; north queensland cowboys } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to dairy farmers stadium . there is only one such row in the table . the opponent record of this unqiue row is north queensland cowboys .'}

and { only { filter_eq { all_rows ; venue ; dairy farmers stadium } } ; eq { hop { filter_eq { all_rows ; venue ; dairy farmers stadium } ; opponent } ; north queensland cowboys } } = true

select the rows whose venue record fuzzily matches to dairy farmers stadium . there is only one such row in the table . the opponent record of this unqiue row is north queensland cowboys .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'dairy farmers stadium_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'opponent_9': 9, 'north queensland cowboys_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'dairy farmers stadium_8': 'dairy farmers stadium', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opponent_9': 'opponent', 'north queensland cowboys_10': 'north queensland cowboys'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'dairy farmers stadium_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'opponent_9': [2], 'north queensland cowboys_10': [3]}

['round', 'opponent', 'result', 'opp', 'venue']

[['1', 'south sydney rabbitohs', 'win', '22', 'aussie stadium'], ['2', 'melbourne storm', 'loss', '16', 'sfs'], ['3', 'canberra raiders', 'win', '26', 'sfs'], ['4', 'manly sea eagles', 'loss', '30', 'brookvale oval'], ['5', 'cronulla sharks', 'win', '24', 'toyota park'], ['6', 'brisbane broncos', 'loss', '24', 'sfs'], ['7', 'st george - illawarra dragons', 'loss', '22', 'aussie stadium'], ['8', 'north queensland cowboys', 'win', '18', 'dairy farmers stadium']]

peruvian segunda división

https://en.wikipedia.org/wiki/Peruvian_Segunda_Divisi%C3%B3n

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12335018-1.html.csv

count

7 teams started their current spell in the segunda division in 2013 .

{'scope': 'all', 'criterion': 'equal', 'value': '2013', 'result': '7', 'col': '5', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'first season of current spell in segunda división', '2013'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first season of current spell in segunda división record is equal to 2013 .', 'tostr': 'filter_eq { all_rows ; first season of current spell in segunda división ; 2013 }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; first season of current spell in segunda división ; 2013 } }', 'tointer': 'select the rows whose first season of current spell in segunda división record is equal to 2013 . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; first season of current spell in segunda división ; 2013 } } ; 7 } = true', 'tointer': 'select the rows whose first season of current spell in segunda división record is equal to 2013 . the number of such rows is 7 .'}

eq { count { filter_eq { all_rows ; first season of current spell in segunda división ; 2013 } } ; 7 } = true

select the rows whose first season of current spell in segunda división record is equal to 2013 . the number of such rows is 7 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'first season of current spell in segunda división_5': 5, '2013_6': 6, '7_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'first season of current spell in segunda división_5': 'first season of current spell in segunda división', '2013_6': '2013', '7_7': '7'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'first season of current spell in segunda división_5': [0], '2013_6': [0], '7_7': [2]}

['team', 'city', 'founded', 'first season in segunda división', 'first season of current spell in segunda división', 'stadium', 'capacity', 'field', 'top division titles', 'last top division title']

[['alfonso ugarte', 'puno', '1928', '2006', '2013', 'enrique torres belón', '20000', 'grass', '0', '-'], ['alianza universidad', 'huánuco', '1939', '2012', '2012', 'heraclio tapia', '15000', 'grass', '0', '-'], ['atlético minero', 'matucana', '1997', '2006', '2009', 'municipal de matucana', '5000', 'grass', '0', '-'], ['atlético torino', 'talara', '1946', '2009', '2009', 'campeonísimo', '8000', 'grass', '0', '-'], ['defensor san alejandro', 'aguaytía', '1969', '2013', '2013', 'aliardo soria pérez', '13000', 'grass', '0', '-'], ['deportivo coopsol', 'chancay', '1964', '1999', '1999', 'rómulo shaw cisneros', '13000', 'grass', '1', '2000'], ['deportivo municipal', 'lima', '1935', '1968', '2013', 'miguel grau', '15000', 'grass', '2', '2006'], ['sport boys', 'callao', '1927', '1988', '2013', 'miguel grau', '15000', 'grass', '2', '2009'], ['sport victoria', 'ica', '1919', '2013', '2013', 'max augustín', '24576', 'grass', '0', '-'], ['sportivo huracán', 'arequipa', '1927', '2013', '2013', 'mariano melgar', '20000', 'grass', '0', '-'], ['walter ormeño', 'cañete', '1950', '1988', '2013', 'oscar ramos cabieses', '8000', 'grass', '0', '-']]

2009 - 10 pittsburgh panthers men 's basketball team

https://en.wikipedia.org/wiki/2009%E2%80%9310_Pittsburgh_Panthers_men%27s_basketball_team

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24925945-3.html.csv

aggregation

for the 2009 - 10 pittsburgh panthers men 's basketball team , the average weight for the players was 212.14 .

{'scope': 'all', 'col': '5', 'type': 'average', 'result': '212.14', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'weight ( lb )'], 'result': '212.14', 'ind': 0, 'tostr': 'avg { all_rows ; weight ( lb ) }'}, '212.14'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; weight ( lb ) } ; 212.14 } = true', 'tointer': 'the average of the weight ( lb ) record of all rows is 212.14 .'}

round_eq { avg { all_rows ; weight ( lb ) } ; 212.14 } = true

the average of the weight ( lb ) record of all rows is 212.14 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'weight ( lb )_4': 4, '212.14_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'weight ( lb )_4': 'weight ( lb )', '212.14_5': '212.14'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'weight ( lb )_4': [0], '212.14_5': [1]}

['name', '-', 'position', 'height', 'weight ( lb )', 'year', 'hometown', 'previous school']

[['chase adams', '3', 'guard', 'ft10in ( m )', '190', '2 senior', 'baltimore , md', 'centenary / mount saint joseph hs'], ['gilbert brown', '5', 'guard / forward', 'ft6in ( m )', '200', '2 junior ( rs )', 'harrisburg , pa', 'south kent school'], ['jermaine dixon', '24', 'guard', 'ft3in ( m )', '200', '3 senior , transfer', 'baltimore , md', 'tallahassee cc / maine central inst / blake hs'], ['tim frye', '44', 'guard', 'ft4in ( m )', '205', '2 junior', 'mars , pa', 'mars area hs'], ['ashton gibbs', '12', 'guard', 'ft2in ( m )', '190', '1 sophomore', 'scotch plains , nj', 'seton hall prep'], ['gary mcghee', '52', 'center', 'ft10in ( m )', '250', '2 junior', 'anderson , in', 'highland hs'], ['dwight miller', '25', 'forward', 'ft8in ( m )', '240', '1 freshman ( rs )', 'nassau , bahamas', 'st pius x hs'], ['lamar patterson', '21', 'guard / forward', 'ft5in ( m )', '220', '1 freshman', 'lancaster , pa', "st benedict 's prep / jp mccaskey hs"], ['jj richardson', '55', 'forward', 'ft7in ( m )', '235', '1 freshman', 'missouri city , tx', 'fort bend hightower hs'], ['nick rivers', '14', 'guard', 'ft0in ( m )', '180', '1 junior', 'phoenix , az', 'brophy college prep'], ['nasir robinson', '35', 'forward', 'ft5in ( m )', '220', '1 sophomore', 'chester , pa', 'chester hs'], ['dante taylor', '11', 'forward', 'ft9in ( m )', '240', '1 freshman', 'greenburgh , ny', 'national christian academy ( md )'], ['brad wanamaker', '22', 'guard', 'ft4in ( m )', '210', '2 junior', 'philadelphia , pa', 'roman catholic hs'], ['travon woodall', '1', 'guard', 'ft11in ( m )', '190', '1 freshman ( rs )', 'brooklyn , ny', 'st anthony hs']]

list of radio station callsigns in the northern territory

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14155573-2.html.csv

count

there are 6 areas served of radio stations in the northern territory .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '2', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'area served'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose area served record is arbitrary .', 'tostr': 'filter_all { all_rows ; area served }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; area served } }', 'tointer': 'select the rows whose area served record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; area served } } ; 6 } = true', 'tointer': 'select the rows whose area served record is arbitrary . the number of such rows is 6 .'}

eq { count { filter_all { all_rows ; area served } } ; 6 } = true

select the rows whose area served record is arbitrary . the number of such rows is 6 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'area served_5': 5, '6_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'area served_5': 'area served', '6_6': '6'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'area served_5': [0], '6_6': [2]}

['callsign', 'area served', 'frequency', 'band', 'freq currently', 'purpose']

[['5al', 'alice springs', '1530', 'am', '8al ( 783 khz )', 'national'], ['5dr', 'darwin', '1500', 'am', 'see 8dr', 'national'], ['8dn', 'darwin', '1242', 'am', '8tab ( hpon )', 'commercial'], ['8dr', 'darwin', '0 657', 'am', '8rn', 'national'], ['8kn', 'katherine', '0 639', 'am', '8rn', 'national'], ['8tc', 'tennant creek', '0 684', 'am', '8rn', 'national']]

1997 world club championship

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10637415-1.html.csv

majority

in the '97 rugby world club championship , most of the clubs with differentials over 100 did n't lose a match .

{'scope': 'subset', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': {'col': '6', 'criterion': 'greater_than', 'value': '100'}}

{'func': 'most_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'diff', '100'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; diff ; 100 }', 'tointer': 'select the rows whose diff record is greater than 100 .'}, 'lost', '0'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose diff record is greater than 100 . for the lost records of these rows , most of them are equal to 0 .', 'tostr': 'most_eq { filter_greater { all_rows ; diff ; 100 } ; lost ; 0 } = true'}

most_eq { filter_greater { all_rows ; diff ; 100 } ; lost ; 0 } = true

select the rows whose diff record is greater than 100 . for the lost records of these rows , most of them are equal to 0 .

2

2

{'most_eq_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'diff_4': 4, '100_5': 5, 'lost_6': 6, '0_7': 7}

{'most_eq_1': 'most_eq', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'diff_4': 'diff', '100_5': '100', 'lost_6': 'lost', '0_7': '0'}

{'most_eq_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'diff_4': [0], '100_5': [0], 'lost_6': [1], '0_7': [1]}

['club', 'played', 'lost', 'drawn', 'against', 'diff', 'points']

[['brisbane broncos', '6', '0', '0', '52', '218', '12'], ['auckland warriors', '6', '0', '0', '82', '186', '12'], ['cronulla sharks', '6', '0', '0', '54', '176', '12'], ['penrith panthers', '6', '0', '0', '120', '136', '12'], ['canberra raiders', '6', '1', '0', '108', '194', '10'], ['canterbury bulldogs', '6', '2', '0', '121', '97', '8']]

list of supernanny episodes

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19897294-5.html.csv

unique

the hillhouse - docherty family is the only episode of supernanny that was aired in the month of august .

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

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

and { only { filter_eq { all_rows ; original air date ; august } } ; eq { hop { filter_eq { all_rows ; original air date ; august } ; family / families } ; the hillhouse - docherty family } } = true

select the rows whose original air date record fuzzily matches to august . there is only one such row in the table . the family / families record of this unqiue row is the hillhouse - docherty family .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'original air date_7': 7, 'august_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'family / families_9': 9, 'the hillhouse - docherty family_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'original air date_7': 'original air date', 'august_8': 'august', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'family / families_9': 'family / families', 'the hillhouse - docherty family_10': 'the hillhouse - docherty family'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'original air date_7': [0], 'august_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'family / families_9': [2], 'the hillhouse - docherty family_10': [3]}

['no overall', 'no in series', 'family / families', 'location ( s )', 'original air date']

[['uk16', '1', 'the hillhouse - docherty family', 'ayr ( scotland )', '29 august 2006'], ['uk17', '2', 'the howat family', 'shenley', '5 september 2006'], ['uk18', '3', 'the brown - smith family', 'warrington', '12 september 2006'], ['uk19', '4', 'the bates family', 'evesham', '19 september 2006'], ['uk20', '5', 'the williams family', 'birmingham', '26 september 2006']]

worcestershire county cricket club

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1156428-2.html.csv

aggregation

the worcestershire county cricket club played a total of 1239 worcs f-c matches from 1910 - present .

{'scope': 'all', 'col': '4', 'type': 'sum', 'result': '1239', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'worcs f - c matches'], 'result': '1239', 'ind': 0, 'tostr': 'sum { all_rows ; worcs f - c matches }'}, '1239'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; worcs f - c matches } ; 1239 } = true', 'tointer': 'the sum of the worcs f - c matches record of all rows is 1239 .'}

round_eq { sum { all_rows ; worcs f - c matches } ; 1239 } = true

the sum of the worcs f - c matches record of all rows is 1239 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'worcs f - c matches_4': 4, '1239_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'worcs f - c matches_4': 'worcs f - c matches', '1239_5': '1239'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'worcs f - c matches_4': [0], '1239_5': [1]}

['name of ground', 'location', 'first - class span', 'worcs f - c matches', 'list a span', 'worcs la matches']

[['bournville cricket ground', 'bournville , birmingham', '1910 - 1911', '2', 'n / a', '0'], ['chain wire club ground', 'stourport - on - severn , worcestershire', '1980', '1', 'n / a', '0'], ['chester road north ground', 'kidderminster , worcestershire', '1921 - 2008', '68', '1969 - 2008', '5'], ['evesham cricket club ground', 'evesham , worcestershire', '1951', '1', 'n / a', '0'], ['new road ( county ground )', 'worcester', '1899 - present', '1072', '1963 - present', '425'], ['racecourse ground', 'hereford', '1919 - 1983', '5', '1983 - 1987', '3'], ['seth somers park', 'halesowen , west midlands', '1964 - 1969', '2', 'n / a', '0'], ['tipton road', 'dudley , west midlands', '1911 - 1971', '88', '1969 - 1977', '14']]

1979 - 80 philadelphia flyers season

https://en.wikipedia.org/wiki/1979%E2%80%9380_Philadelphia_Flyers_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14208862-5.html.csv

ordinal

the philadelphia flyers ' game on january 19 recorded their highest attendance of the 1979 - 80 season .

{'row': '9', 'col': '6', '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', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'date'], 'result': 'january 19', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; date }'}, 'january 19'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; january 19 } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the date record of this row is january 19 .'}

eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; january 19 } = true

select the row whose attendance record of all rows is 1st maximum . the date record of this row is january 19 .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'date_7': 7, 'january 19_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'date_7': 'date', 'january 19_8': 'january 19'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'date_7': [1], 'january 19_8': [2]}

['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record']

[['january 4', 'philadelphia', '5 - 3', 'ny rangers', 'myre', '17398', '25 - 1 - 10'], ['january 6', 'philadelphia', '4 - 2', 'buffalo', 'peeters', '16433', '26 - 1 - 10'], ['january 7', 'philadelphia', '1 - 7', 'minnesota', 'myre', '15962', '26 - 2 - 10'], ['january 10', 'winnipeg', '4 - 5', 'philadelphia', 'peeters', '17077', '27 - 2 - 10'], ['january 12', 'philadelphia', '3 - 4', 'montreal', 'myre', '18091', '27 - 3 - 10'], ['january 13', 'st louis', '1 - 1', 'philadelphia', 'peeters', '17077', '27 - 3 - 11'], ['january 15', 'washington', '4 - 7', 'philadelphia', 'myre', '17077', '28 - 3 - 11'], ['january 17', 'chicago', '1 - 5', 'philadelphia', 'peeters', '17077', '29 - 3 - 11'], ['january 19', 'philadelphia', '4 - 4', 'washington', 'myre', '18130', '29 - 3 - 12'], ['january 22', 'philadelphia', '3 - 1', 'st louis', 'peeters', '17453', '30 - 3 - 12'], ['january 23', 'philadelphia', '4 - 1', 'chicago', 'myre', '17160', '31 - 3 - 12'], ['january 25', 'philadelphia', '5 - 4', 'winnipeg', 'peeters', '15122', '32 - 3 - 12'], ['january 27', 'philadelphia', '5 - 3', 'edmonton', 'peeters', '15423', '33 - 3 - 12'], ['january 31', 'minnesota', '2 - 4', 'philadelphia', 'st croix', '17077', '34 - 3 - 12']]

1979 vfl season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823719-21.html.csv

superlative

in the 1979 vfl season , the largest crowd occurred when collingwood was the home team .

{'scope': 'all', 'col_superlative': '6', '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', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'home team'], 'result': 'collingwood', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; home team }'}, 'collingwood'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; home team } ; collingwood } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the home team record of this row is collingwood .'}

eq { hop { argmax { all_rows ; crowd } ; home team } ; collingwood } = true

select the row whose crowd record of all rows is maximum . the home team record of this row is collingwood .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'home team_6': 6, 'collingwood_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', 'home team_6': 'home team', 'collingwood_7': 'collingwood'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'home team_6': [1], 'collingwood_7': [2]}

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

[['melbourne', '24.17 ( 161 )', 'st kilda', '12.24 ( 96 )', 'mcg', '18435', '25 august 1979'], ['hawthorn', '7.18 ( 60 )', 'north melbourne', '24.21 ( 165 )', 'princes park', '18501', '25 august 1979'], ['geelong', '17.13 ( 115 )', 'richmond', '12.17 ( 89 )', 'kardinia park', '18039', '25 august 1979'], ['fitzroy', '22.19 ( 151 )', 'footscray', '14.16 ( 100 )', 'junction oval', '12076', '25 august 1979'], ['collingwood', '18.12 ( 120 )', 'carlton', '14.17 ( 101 )', 'victoria park', '36509', '25 august 1979'], ['essendon', '13.17 ( 95 )', 'south melbourne', '10.16 ( 76 )', 'vfl park', '32127', '25 august 1979']]

million dollar password

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13673176-3.html.csv

superlative

the episode of the million dollar password game show , broadcast on sunday june 1 , 2008 , had the highest viewing figures .

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

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'viewers ( millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; viewers ( millions ) }'}, 'airdate'], 'result': 'sunday , june 1 , 2008', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; viewers ( millions ) } ; airdate }'}, 'sunday , june 1 , 2008'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; viewers ( millions ) } ; airdate } ; sunday , june 1 , 2008 } = true', 'tointer': 'select the row whose viewers ( millions ) record of all rows is maximum . the airdate record of this row is sunday , june 1 , 2008 .'}

eq { hop { argmax { all_rows ; viewers ( millions ) } ; airdate } ; sunday , june 1 , 2008 } = true

select the row whose viewers ( millions ) record of all rows is maximum . the airdate record of this row is sunday , june 1 , 2008 .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'viewers (millions)_5': 5, 'airdate_6': 6, 'sunday , june 1 , 2008_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'viewers (millions)_5': 'viewers ( millions )', 'airdate_6': 'airdate', 'sunday , june 1 , 2008_7': 'sunday , june 1 , 2008'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'viewers (millions)_5': [0], 'airdate_6': [1], 'sunday , june 1 , 2008_7': [2]}

['airdate', 'celebrities', 'rating', 'share', '1849', 'viewers ( millions )', 'weekly rank', 'prod code']

[['sunday , june 1 , 2008', 'neil patrick harris , rachael ray', '6.8', '12', '2.2 / 7', '10.69', '3', '106'], ['sunday , june 8 , 2008', "tony hawk , rosie o'donnell", '6.3', '11', '2.1 / 6', '9.64', '5', '104'], ['thursday , june 12 , 2008', 'susie essman , betty white', '6.4', '12', '2.0 / 7', '9.52', '7', '102'], ['sunday , june 22 , 2008', 'shanna moakler , steven weber', '5.5', '10', '1.5 / 5', '8.29', '12', '105'], ['sunday , june 29 , 2008', 'sara evans , steve schirripa', '5.6', '10', '1.7 / 5', '8.55', '7', '101'], ['sunday , july 6 , 2008', 'monique coleman , damien fahey', '5.0', '9', '1.3 / 5', '7.53', '3', '103']]

1957 vfl season

https://en.wikipedia.org/wiki/1957_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10774891-18.html.csv

comparative

fitzroy had a higher score than north melbourne in the 1957 vfl season .

{'row_1': '4', 'row_2': '1', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

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

greater { hop { filter_eq { all_rows ; home team ; fitzroy } ; home team score } ; hop { filter_eq { all_rows ; home team ; north melbourne } ; home team score } } = true

select the rows whose home team record fuzzily matches to fitzroy . take the home team score record of this row . select the rows whose home team record fuzzily matches to north melbourne . take the home team score record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'home team_7': 7, 'fitzroy_8': 8, 'home team score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'home team_11': 11, 'north melbourne_12': 12, 'home team score_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'home team_7': 'home team', 'fitzroy_8': 'fitzroy', 'home team score_9': 'home team score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'home team_11': 'home team', 'north melbourne_12': 'north melbourne', 'home team score_13': 'home team score'}

{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'home team_7': [0], 'fitzroy_8': [0], 'home team score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'home team_11': [1], 'north melbourne_12': [1], 'home team score_13': [3]}

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

[['north melbourne', '10.20 ( 80 )', 'south melbourne', '17.11 ( 113 )', 'arden street oval', '10000', '24 august 1957'], ['melbourne', '18.12 ( 120 )', 'richmond', '10.11 ( 71 )', 'mcg', '35751', '24 august 1957'], ['footscray', '8.11 ( 59 )', 'hawthorn', '7.15 ( 57 )', 'western oval', '25436', '24 august 1957'], ['fitzroy', '15.14 ( 104 )', 'geelong', '10.20 ( 80 )', 'brunswick street oval', '10000', '24 august 1957'], ['st kilda', '14.12 ( 96 )', 'collingwood', '7.14 ( 56 )', 'junction oval', '29300', '24 august 1957'], ['essendon', '17.21 ( 123 )', 'carlton', '9.8 ( 62 )', 'windy hill', '35000', '24 august 1957']]

1948 vfl season

https://en.wikipedia.org/wiki/1948_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809529-8.html.csv

comparative

among home teams in the 1948 vfl season , geelong had a higher score than richmond .

{'row_1': '1', 'row_2': '6', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

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

greater { hop { filter_eq { all_rows ; home team ; geelong } ; home team score } ; hop { filter_eq { all_rows ; home team ; richmond } ; home team score } } = true

select the rows whose home team record fuzzily matches to geelong . take the home team score record of this row . select the rows whose home team record fuzzily matches to richmond . take the home team score record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'home team_7': 7, 'geelong_8': 8, 'home team score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'home team_11': 11, 'richmond_12': 12, 'home team score_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'home team_7': 'home team', 'geelong_8': 'geelong', 'home team score_9': 'home team score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'home team_11': 'home team', 'richmond_12': 'richmond', 'home team score_13': 'home team score'}

{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'home team_7': [0], 'geelong_8': [0], 'home team score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'home team_11': [1], 'richmond_12': [1], 'home team score_13': [3]}

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

[['geelong', '15.16 ( 106 )', 'south melbourne', '19.12 ( 126 )', 'kardinia park', '19500', '5 june 1948'], ['collingwood', '11.17 ( 83 )', 'melbourne', '11.10 ( 76 )', 'victoria park', '20000', '5 june 1948'], ['st kilda', '7.12 ( 54 )', 'hawthorn', '10.12 ( 72 )', 'junction oval', '7000', '5 june 1948'], ['north melbourne', '11.6 ( 72 )', 'footscray', '8.9 ( 57 )', 'arden street oval', '12000', '5 june 1948'], ['fitzroy', '12.8 ( 80 )', 'essendon', '9.10 ( 64 )', 'brunswick street oval', '25000', '5 june 1948'], ['richmond', '13.10 ( 88 )', 'carlton', '9.21 ( 75 )', 'punt road oval', '33000', '5 june 1948']]

list of ngc objects ( 5001 - 6000 )

https://en.wikipedia.org/wiki/List_of_NGC_objects_%285001%E2%80%936000%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11051845-5.html.csv

majority

the majority of ngc objects have an apparent magnitude over 10.0 .

{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10.0', 'subset': None}

{'func': 'most_greater', 'args': ['all_rows', 'apparent magnitude', '10.0'], 'result': True, 'ind': 0, 'tointer': 'for the apparent magnitude records of all rows , most of them are greater than 10.0 .', 'tostr': 'most_greater { all_rows ; apparent magnitude ; 10.0 } = true'}

most_greater { all_rows ; apparent magnitude ; 10.0 } = true

for the apparent magnitude records of all rows , most of them are greater than 10.0 .

1

1

{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'apparent magnitude_3': 3, '10.0_4': 4}

{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'apparent magnitude_3': 'apparent magnitude', '10.0_4': '10.0'}

{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'apparent magnitude_3': [0], '10.0_4': [0]}

['ngc number', 'object type', 'constellation', 'right ascension ( j2000 )', 'declination ( j2000 )', 'apparent magnitude']

[['5408', 'irregular galaxy', 'centaurus', '14h03 m21 .0 s', 'degree22 ′ 44 ″', '14.0'], ['5457', 'spiral galaxy', 'ursa major', '14h03 m12 .5 s', 'degree20 ′ 53 ″', '8.7'], ['5466', 'globular cluster', 'boötes', '14h05 m27 .4 s', 'degree32 ′ 04 ″', '10.5'], ['5474', 'spiral galaxy', 'ursa major', '14h05 m01 .5 s', 'degree39 ′ 45 ″', '11.9'], ['5477', 'irregular galaxy', 'ursa major', '14h05 m33 .1 s', 'degree27 ′ 40 ″', '14.5']]

athletics at the 1986 central american and caribbean games

https://en.wikipedia.org/wiki/Athletics_at_the_1986_Central_American_and_Caribbean_Games

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10258265-3.html.csv

comparative

puerto rico recorded more bronze medals than barbados in athletics at the 1986 central american and caribbean games .

{'row_1': '5', 'row_2': '12', 'col': '5', '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', 'nation', 'puerto rico'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to puerto rico .', 'tostr': 'filter_eq { all_rows ; nation ; puerto rico }'}, 'bronze'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nation ; puerto rico } ; bronze }', 'tointer': 'select the rows whose nation record fuzzily matches to puerto rico . take the bronze record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'barbados'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nation record fuzzily matches to barbados .', 'tostr': 'filter_eq { all_rows ; nation ; barbados }'}, 'bronze'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; nation ; barbados } ; bronze }', 'tointer': 'select the rows whose nation record fuzzily matches to barbados . take the bronze record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; nation ; puerto rico } ; bronze } ; hop { filter_eq { all_rows ; nation ; barbados } ; bronze } } = true', 'tointer': 'select the rows whose nation record fuzzily matches to puerto rico . take the bronze record of this row . select the rows whose nation record fuzzily matches to barbados . take the bronze record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; nation ; puerto rico } ; bronze } ; hop { filter_eq { all_rows ; nation ; barbados } ; bronze } } = true

select the rows whose nation record fuzzily matches to puerto rico . take the bronze record of this row . select the rows whose nation record fuzzily matches to barbados . take the bronze 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, 'nation_7': 7, 'puerto rico_8': 8, 'bronze_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'nation_11': 11, 'barbados_12': 12, 'bronze_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', 'nation_7': 'nation', 'puerto rico_8': 'puerto rico', 'bronze_9': 'bronze', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nation_11': 'nation', 'barbados_12': 'barbados', 'bronze_13': 'bronze'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'nation_7': [0], 'puerto rico_8': [0], 'bronze_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'nation_11': [1], 'barbados_12': [1], 'bronze_13': [3]}

['rank', 'nation', 'gold', 'silver', 'bronze', 'total']

[['1', 'cuba', '27', '16', '8', '51'], ['2', 'mexico', '6', '9', '6', '21'], ['3', 'colombia', '3', '1', '7', '11'], ['4', 'bahamas', '2', '4', '3', '9'], ['5', 'puerto rico', '2', '3', '6', '11'], ['6', 'jamaica', '1', '3', '3', '7'], ['7', 'us virgin islands', '1', '0', '1', '2'], ['8', 'guyana', '1', '0', '0', '1'], ['9', 'dominican republic', '0', '4', '2', '6'], ['10', 'trinidad and tobago', '0', '2', '1', '3'], ['10', 'venezuela', '0', '2', '1', '3'], ['12', 'barbados', '0', '0', '2', '2'], ['13', 'haiti', '0', '0', '1', '1'], ['13', 'panama', '0', '0', '1', '1']]

alan dzagoev

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16716472-2.html.csv

unique

the match played on 15 august 2012 was the only friendly competition that alan dzagoev scored in .

{'scope': 'all', 'row': '8', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'friendly', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to friendly .', 'tostr': 'filter_eq { all_rows ; competition ; friendly }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; competition ; friendly } }', 'tointer': 'select the rows whose competition record fuzzily matches to friendly . 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', 'friendly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to friendly .', 'tostr': 'filter_eq { all_rows ; competition ; friendly }'}, 'date'], 'result': '15 august 2012', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; competition ; friendly } ; date }'}, '15 august 2012'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; competition ; friendly } ; date } ; 15 august 2012 }', 'tointer': 'the date record of this unqiue row is 15 august 2012 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; competition ; friendly } } ; eq { hop { filter_eq { all_rows ; competition ; friendly } ; date } ; 15 august 2012 } } = true', 'tointer': 'select the rows whose competition record fuzzily matches to friendly . there is only one such row in the table . the date record of this unqiue row is 15 august 2012 .'}

and { only { filter_eq { all_rows ; competition ; friendly } } ; eq { hop { filter_eq { all_rows ; competition ; friendly } ; date } ; 15 august 2012 } } = true

select the rows whose competition record fuzzily matches to friendly . there is only one such row in the table . the date record of this unqiue row is 15 august 2012 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'competition_7': 7, 'friendly_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '15 august 2012_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', 'friendly_8': 'friendly', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '15 august 2012_10': '15 august 2012'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'competition_7': [0], 'friendly_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '15 august 2012_10': [3]}

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

[['8 october 2010', 'aviva stadium , dublin , ireland', '2 - 0', '3 - 2', 'euro 2012 qualifier'], ['7 october 2011', 'štadión pod dubňom , žilina , slovakia', '1 - 0', '1 - 0', 'euro 2012 qualifier'], ['11 october 2011', 'luzhniki stadium , moscow , russia', '1 - 0', '6 - 0', 'euro 2012 qualifier'], ['11 october 2011', 'luzhniki stadium , moscow , russia', '4 - 0', '6 - 0', 'euro 2012 qualifier'], ['8 june 2012', 'municipal stadium , wrocław , poland', '1 - 0', '4 - 1', 'euro 2012'], ['8 june 2012', 'municipal stadium , wrocław , poland', '3 - 1', '4 - 1', 'euro 2012'], ['12 june 2012', 'national stadium , warsaw , poland', '1 - 0', '1 - 1', 'euro 2012'], ['15 august 2012', 'lokomotiv stadium , moscow , russia', '1 - 0', '1 - 1', 'friendly']]

vc zenit - kazan

https://en.wikipedia.org/wiki/VC_Zenit-Kazan

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14363116-1.html.csv

aggregation

the average height of players in vc zenit - kazan team is 199 cm .

{'scope': 'all', 'col': '5', 'type': 'average', 'result': '198.77', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'height'], 'result': '198.77', 'ind': 0, 'tostr': 'avg { all_rows ; height }'}, '198.77'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; height } ; 198.77 } = true', 'tointer': 'the average of the height record of all rows is 198.77 .'}

round_eq { avg { all_rows ; height } ; 198.77 } = true

the average of the height record of all rows is 198.77 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'height_4': 4, '198.77_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'height_4': 'height', '198.77_5': '198.77'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'height_4': [0], '198.77_5': [1]}

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

[['1', 'united states', 'matthew anderson', 'april 18 , 1987 ( age26 )', '204', 'outside hitter'], ['3', 'russia', 'nikolay apalikov', 'august 26 , 1982 ( age31 )', '203', 'middle blocker'], ['4', 'russia', 'ivan demakov', 'june 1 , 1993 ( age20 )', '209', 'middle blocker'], ['5', 'italy', 'valerio vermiglio', 'march 1 , 1976 ( age37 )', '189', 'setter'], ['6', 'russia', 'eugeniy sivozhelez', 'june 8 , 1986 ( age27 )', '196', 'outside hitter'], ['7', 'russia', 'aleksandr volkov', 'february 14 , 1985 ( age28 )', '210', 'middle blocker'], ['8', 'russia', 'igor kolodinsky', 'july 7 , 1983 ( age30 )', '197', 'setter'], ['9', 'russia', 'alexey cheremisin', 'september 23 , 1980 ( age33 )', '204', 'opposite hitter'], ['10', 'russia', 'yury berezhko', 'january 27 , 1981 ( age33 )', '198', 'outside hitter'], ['13', 'russia', 'vitaliy matychenko', 'august 4 , 1983 ( age30 )', '194', 'setter'], ['14', 'russia', 'alexander abrosimov', 'august 25 , 1983 ( age30 )', '207', 'middle blocker'], ['15', 'russia', 'alexey obmochaev', 'may 22 , 1989 ( age24 )', '188', 'libero'], ['17', 'russia', 'vladislav babichev', 'february 18 , 1981 ( age32 )', '185', 'libero']]

catherine tanvier

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1676921-5.html.csv

count

catherine tanvier had two matches that took place in 1982 .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': '1982', 'result': '2', 'col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '1982'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 1982 .', 'tostr': 'filter_eq { all_rows ; date ; 1982 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; 1982 } }', 'tointer': 'select the rows whose date record fuzzily matches to 1982 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; 1982 } } ; 2 } = true', 'tointer': 'select the rows whose date record fuzzily matches to 1982 . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; date ; 1982 } } ; 2 } = true

select the rows whose date record fuzzily matches to 1982 . 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, 'date_5': 5, '1982_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', 'date_5': 'date', '1982_6': '1982', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '1982_6': [0], '2_7': [2]}

['date', 'tournament', 'surface', 'partner', 'opponents in final', 'score in final']

[['18 july 1982', 'monte carlo , monaco', 'clay', 'virginia ruzici', 'patricia medrado claudia monteiro', '7 - 6 , 6 - 2'], ['8 august 1982', 'us clay courts , usa', 'clay', 'ivanna madruga', 'joanne russell virginia ruzici', '7 - 5 , 7 - 6'], ['9 may 1983', 'perugia , italy', 'clay', 'ivanna madruga', 'virginia ruzici virginia wade', '3 - 6 , 6 - 2 , 1 - 6'], ['10 july 1983', 'hittfeld , germany', 'clay', 'ivanna madruga', 'bettina bunge claudia kohde - kilsch', '5 - 7 , 4 - 6'], ['30 october 1983', 'filderstadt , germany', 'carpet', 'virginia ruzici', 'martina navratilova candy reynolds', '2 - 6 , 1 - 6'], ['16 december 1984', 'tokyo pan pacific , japan', 'carpet', 'elizabeth smylie', 'claudia kohde - kilsch helena suková', '4 - 6 , 1 - 6'], ['19 may 1985', 'german open , germany', 'clay', 'steffi graf', 'claudia kohde - kilsch helena suková', '4 - 6 , 1 - 6'], ['11 november 1985', 'hilversum , netherlands', 'carpet', 'marcella mesker', 'sandra cecchini sabrina goleš', '6 - 2 , 6 - 2'], ['13 april 1986', 'hilton head , usa', 'clay', 'steffi graf', 'chris evert - lloyd anne white', '3 - 6 , 3 - 6'], ['20 april 1986', 'amelia island , usa', 'clay', 'gabriela sabatini', 'claudia kohde - kilsch helena suková', '2 - 6 , 7 - 5 , 6 - 7'], ['19 october 1986', 'hilversum , netherlands', 'carpet', 'tine scheuer - larsen', 'kathy jordan helena suková', '5 - 7 , 1 - 6'], ['24 may 1987', 'european open , switzerland', 'clay', 'laura gildemeister', 'betsy nagelsen liz smylie', '6 - 4 , 4 - 6 , 3 - 6'], ['17 july 1988', 'nice , france', 'clay', 'catherine suire', 'isabelle demongeot nathalie tauziat', '6 - 4 , 4 - 6 , 6 - 2'], ['24 july 1988', 'aix - en - provence , france', 'clay', 'nathalie herreman', 'sandra cecchini arantxa sánchez vicario', '6 - 4 , 7 - 5'], ['22 october 1989', 'bayonne , france', 'hard', 'manon bollegraf', 'elna reinach raffaella reggi', '7 - 6 , 7 - 5'], ['30 september 1990', 'bayonne , france', 'carpet', 'louise field', 'jo - anne faull rachel mcquillan', '7 - 6 , 6 - 7 , 7 - 6'], ['29 september 1991', 'bayonne , france', 'carpet', 'rachel mcquillan', 'patricia tarabini nathalie tauziat', '3 - 6 , ret'], ['23 february 1992', 'cesena , italy', 'carpet', 'catherine suire', 'sabina appelmans raffaella reggi', 'w / o']]

.38 special

https://en.wikipedia.org/wiki/.38_Special

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-173103-1.html.csv

ordinal

the .38 super gun cartridge has the fourth highest max pressure in psi .

{'row': '11', 'col': '5', 'order': '4', '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', 'max pressure', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; max pressure ; 4 }'}, 'cartridge'], 'result': '.38 super', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; max pressure ; 4 } ; cartridge }'}, '.38 super'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; max pressure ; 4 } ; cartridge } ; .38 super } = true', 'tointer': 'select the row whose max pressure record of all rows is 4th maximum . the cartridge record of this row is .38 super .'}

eq { hop { nth_argmax { all_rows ; max pressure ; 4 } ; cartridge } ; .38 super } = true

select the row whose max pressure record of all rows is 4th maximum . the cartridge record of this row is .38 super .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'max pressure_5': 5, '4_6': 6, 'cartridge_7': 7, '.38 super_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', 'max pressure_5': 'max pressure', '4_6': '4', 'cartridge_7': 'cartridge', '.38 super_8': '.38 super'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'max pressure_5': [0], '4_6': [0], 'cartridge_7': [1], '.38 super_8': [2]}

['cartridge', 'bullet weight', 'muzzle velocity', 'muzzle energy', 'max pressure']

[['.38 short colt', 'gr ( g )', 'ft / s ( m / s )', '181ft lbf ( 245 j )', '7500 cup'], ['.38 long colt', 'gr ( g )', 'ft / s ( m / s )', '201ft lbf ( 273 j )', '12000 cup'], ['.38 s & w', 'gr ( g )', 'ft / s ( m / s )', '206ft lbf ( 279 j )', '14500 psi'], ['.38 s & w special', 'gr ( g )', 'ft / s ( m / s )', '310ft lbf ( 420 j )', '17000 psi'], ['.38 special + p', 'gr ( g )', 'ft / s ( m / s )', '351ft lbf ( 476 j )', '20000 psi'], ['.38 special + p +', 'gr ( g )', 'ft / s ( m / s )', '295ft lbf ( 400 j )', '> 20000 psi'], ['.380 acp', 'gr ( g )', 'ft / s ( m / s )', '178ft lbf ( 241 j )', '21500 psi'], ['9x19 mm parabellum', 'gr ( g )', 'ft / s ( m / s )', '420ft lbf ( 570 j )', '39200 psi'], ['9x19 mm parabellum', 'gr ( g )', 'ft / s ( m / s )', '383ft lbf ( 520 j )', '39200 psi'], ['9x18 mm makarov', 'gr ( g )', 'ft / s ( m / s )', '231ft lbf ( 313 j )', '23206 psi'], ['.38 super', 'grains ( g )', 'ft / s ( m / s )', '468ft lbf ( 634 j )', '36500 psi'], ['.357 magnum', 'grains ( g )', 'ft / s ( m / s )', '639ft lbf ( 866 j )', '35000 psi'], ['.357 sig', 'grains ( g )', 'ft / s ( m / s )', '506ft lbf ( 686 j )', '40000 psi']]

wru division five south east

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17625749-3.html.csv

ordinal

in wru division five south east , when there were at least 10 games won , the 3rd highest number of losses was from pontyclun rfc .

{'scope': 'subset', 'row': '4', 'col': '5', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'greater_than_eq', 'value': '10'}}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'won', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; won ; 10 }', 'tointer': 'select the rows whose won record is greater than or equal to 10 .'}, 'lost', '3'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_greater_eq { all_rows ; won ; 10 } ; lost ; 3 }'}, 'club'], 'result': 'pontyclun rfc', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_greater_eq { all_rows ; won ; 10 } ; lost ; 3 } ; club }'}, 'pontyclun rfc'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_greater_eq { all_rows ; won ; 10 } ; lost ; 3 } ; club } ; pontyclun rfc } = true', 'tointer': 'select the rows whose won record is greater than or equal to 10 . select the row whose lost record of these rows is 3rd maximum . the club record of this row is pontyclun rfc .'}

eq { hop { nth_argmax { filter_greater_eq { all_rows ; won ; 10 } ; lost ; 3 } ; club } ; pontyclun rfc } = true

select the rows whose won record is greater than or equal to 10 . select the row whose lost record of these rows is 3rd maximum . the club record of this row is pontyclun rfc .

4

4

{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'won_6': 6, '10_7': 7, 'lost_8': 8, '3_9': 9, 'club_10': 10, 'pontyclun rfc_11': 11}

{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'won_6': 'won', '10_7': '10', 'lost_8': 'lost', '3_9': '3', 'club_10': 'club', 'pontyclun rfc_11': 'pontyclun rfc'}

{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'won_6': [0], '10_7': [0], 'lost_8': [1], '3_9': [1], 'club_10': [2], 'pontyclun rfc_11': [3]}

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

[['club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['porth harlequins rfc', '20', '17', '0', '3', '642', '173', '100', '19', '12', '2', '82'], ["st joseph 's rfc", '20', '17', '0', '3', '503', '179', '69', '17', '9', '3', '80'], ['pontyclun rfc', '20', '14', '1', '5', '468', '218', '66', '24', '7', '2', '67'], ['deri rfc', '20', '14', '0', '6', '476', '285', '65', '33', '7', '3', '66'], ['st albans rfc', '20', '11', '0', '9', '402', '423', '58', '61', '7', '1', '52'], ['cowbridge rfc', '20', '8', '0', '12', '329', '379', '37', '54', '3', '7', '42'], ['old penarthians rfc', '20', '9', '0', '11', '231', '369', '29', '53', '2', '3', '41'], ['penygraig rfc', '20', '6', '1', '13', '260', '436', '30', '63', '2', '5', '33'], ['ogmore vale rfc', '20', '6', '0', '14', '208', '475', '27', '71', '2', '3', '29'], ['canton rfc', '20', '4', '0', '16', '248', '499', '34', '67', '3', '6', '25'], ['dinas powys rfc', '20', '3', '0', '17', '161', '492', '20', '73', '1', '1', '14']]

red dwarf

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25721-4.html.csv

majority

most of the releases of the show red dwarf , had versions released in region 4 .

{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'not_equal', 'value': 'n / a', 'subset': None}

{'func': 'most_str_not_eq', 'args': ['all_rows', 'region 4', 'n / a'], 'result': True, 'ind': 0, 'tointer': 'for the region 4 records of all rows , most of them do not match to n / a .', 'tostr': 'most_not_eq { all_rows ; region 4 ; n / a } = true'}

most_not_eq { all_rows ; region 4 ; n / a } = true

for the region 4 records of all rows , most of them do not match to n / a .

1

1

{'most_str_not_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'region 4_3': 3, 'n / a_4': 4}

{'most_str_not_eq_0': 'most_str_not_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'region 4_3': 'region 4', 'n / a_4': 'n / a'}

{'most_str_not_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'region 4_3': [0], 'n / a_4': [0]}

['release', 'of discs', 'region 1', 'region 2', 'region 4']

[['series i', '2', '25 february 2003', '4 november 2002', '3 december 2002'], ['series ii', '2', '25 february 2003', '10 february 2003', '1 april 2003'], ['series iii', '2', '3 february 2004', '3 november 2003', '18 november 2003'], ['series iv', '2', '3 february 2004', '16 february 2004', '9 march 2004'], ['just the shows vol 1 series 1 - 4 with no extras', '4', 'n / a', '18 october 2004', '12 november 2004'], ['series v', '2', '15 march 2005', '8 november 2004', '1 december 2004'], ['series vi', '2', '15 march 2005', '21 february 2005', '6 april 2005'], ['series vii', '3', '10 january 2006', '7 november 2005', '1 december 2005'], ['series viii', '3', '2 may 2006', '27 march 2006', '20 april 2006'], ['the complete collection series 1 - 8 with extras', '18', '5 september 2006', 'n / a', 'n / a'], ['just the shows vol 2 series 5 - 8 with no extras', '6', 'n / a', '2 october 2006', '3 november 2006'], ['beat the geek ( interactive dvd quiz game )', '1', 'n / a', '23 october 2006', '3 march 2011'], ['all the shows series 1 - 8 with no extras', '10', 'n / a', '10 november 2008', 'n / a'], ['back to earth', '2', '6 october 2009', '15 june 2009', '17 december 2009'], ['just the shows series 1 - 8 with no extras', '10', 'n / a', '9 november 2009', 'n / a']]

national assembly for wales election , 2011

https://en.wikipedia.org/wiki/National_Assembly_for_Wales_election%2C_2011

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11099297-2.html.csv

comparative

in the national assembly for wales election , the percentage for green on october 27 , 2010 was one percent less than on november 24 , 2010 .

{'row_1': '8', 'row_2': '7', 'col': '6', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1', 'bigger': 'row2'}}

{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date ( s ) conducted', '27 october 2010'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date ( s ) conducted record fuzzily matches to 27 october 2010 .', 'tostr': 'filter_eq { all_rows ; date ( s ) conducted ; 27 october 2010 }'}, 'green'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ( s ) conducted ; 27 october 2010 } ; green }', 'tointer': 'select the rows whose date ( s ) conducted record fuzzily matches to 27 october 2010 . take the green record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date ( s ) conducted', '24 november 2010'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date ( s ) conducted record fuzzily matches to 24 november 2010 .', 'tostr': 'filter_eq { all_rows ; date ( s ) conducted ; 24 november 2010 }'}, 'green'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ( s ) conducted ; 24 november 2010 } ; green }', 'tointer': 'select the rows whose date ( s ) conducted record fuzzily matches to 24 november 2010 . take the green record of this row .'}], 'result': '-1', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; date ( s ) conducted ; 27 october 2010 } ; green } ; hop { filter_eq { all_rows ; date ( s ) conducted ; 24 november 2010 } ; green } }'}, '-1'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; date ( s ) conducted ; 27 october 2010 } ; green } ; hop { filter_eq { all_rows ; date ( s ) conducted ; 24 november 2010 } ; green } } ; -1 } = true', 'tointer': 'select the rows whose date ( s ) conducted record fuzzily matches to 27 october 2010 . take the green record of this row . select the rows whose date ( s ) conducted record fuzzily matches to 24 november 2010 . take the green record of this row . the second record is 1 larger than the first record .'}

eq { diff { hop { filter_eq { all_rows ; date ( s ) conducted ; 27 october 2010 } ; green } ; hop { filter_eq { all_rows ; date ( s ) conducted ; 24 november 2010 } ; green } } ; -1 } = true

select the rows whose date ( s ) conducted record fuzzily matches to 27 october 2010 . take the green record of this row . select the rows whose date ( s ) conducted record fuzzily matches to 24 november 2010 . take the green record of this row . the second record is 1 larger than the first record .

6

6

{'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'date (s) conducted_8': 8, '27 october 2010_9': 9, 'green_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'date (s) conducted_12': 12, '24 november 2010_13': 13, 'green_14': 14, '-1_15': 15}

{'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'date (s) conducted_8': 'date ( s ) conducted', '27 october 2010_9': '27 october 2010', 'green_10': 'green', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'date (s) conducted_12': 'date ( s ) conducted', '24 november 2010_13': '24 november 2010', 'green_14': 'green', '-1_15': '-1'}

{'eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'date (s) conducted_8': [0], '27 october 2010_9': [0], 'green_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'date (s) conducted_12': [1], '24 november 2010_13': [1], 'green_14': [3], '-1_15': [5]}

['date ( s ) conducted', 'cons', 'plaid cymru', 'lib dem', 'ukip', 'green', 'others', 'lead']

[['5 may 2011', '22.5 %', '17.9 %', '8.0 %', '4.6 %', '3.4 %', '6.7 %', '14.4 %'], ['14 april 2011', '20 %', '18 %', '8 %', '4 %', '2 %', '4 %', '24 %'], ['30 march 2011', '20 %', '16 %', '8 %', '6 %', '2 %', '2 %', '25 %'], ['8 march 2011', '20 %', '18 %', '5 %', '5 %', '4 %', '2 %', '25 %'], ['26 january 2011', '20 %', '21 %', '8 %', '4 %', '2 %', '4 %', '21 %'], ['22 december 2010', '22 %', '21 %', '5 %', '5 %', '3 %', '2 %', '20 %'], ['24 november 2010', '20 %', '20 %', '9 %', '4 %', '3 %', '4 %', '21 %'], ['27 october 2010', '18 %', '23 %', '9 %', '6 %', '2 %', '3 %', '21 %'], ['3 may 2007', '21.4 %', '21.0 %', '11.7 %', '4.0 %', '3.5 %', '8.8 %', '8.6 %']]

swimming at the 2000 summer olympics - women 's 200 metre individual medley

https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Women%27s_200_metre_individual_medley

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12446647-5.html.csv

count

china had two swimmers rank in the top 8 in the 2000 summer olympics .

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

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

eq { count { filter_eq { all_rows ; nationality ; china } } ; 2 } = true

select the rows whose nationality record fuzzily matches to china . 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, 'nationality_5': 5, 'china_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', 'nationality_5': 'nationality', 'china_6': 'china', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nationality_5': [0], 'china_6': [0], '2_7': [2]}

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

[['1', '5', 'yana klochkova', 'ukraine', '2:13.08'], ['2', '3', 'cristina teuscher', 'united states', '2:13.47'], ['3', '4', 'oxana verevka', 'russia', '2:14.04'], ['4', '6', 'tomoko hagiwara', 'japan', '2:15.09'], ['5', '2', 'chen yan', 'china', '2:15.27'], ['6', '7', 'sue rolph', 'great britain', '2:15.98'], ['7', '1', 'zhan shu', 'china', '2:16.58'], ['8', '8', 'nicole hetzer', 'germany', '2:18.08']]

polona hercog

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17717526-9.html.csv

majority

all of polona hercog 's tennis tournaments were played on the clay surface .

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

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

all_eq { all_rows ; surface ; clay } = true

for the surface records of all rows , all of them fuzzily match to clay .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]}

['date', 'tournament', 'surface', 'partner', 'opponents', 'score']

[['15 january 2007', 'algiers 2 , algeria', 'clay', 'rushmi chakravarthi', 'barbora matusova anna savitskaya', '6 - 2 , 6 - 0'], ['11 february 2008', 'mallorca 2 , spain', 'clay', 'stephanie vogt', 'leticia costas - moreira maite gabarrus alonso', '7 - 6 ( 7 - 2 ) , 6 - 3'], ['28 april 2008', 'makarska , croatia', 'clay', 'stephanie vogt', 'tadeja majerić maša zec peškirič', '7 - 5 , 6 - 2'], ['8 september 2008', 'sarajevo 2 , bosnia - herzegovina', 'clay', 'alberta brianti', 'çağla büyükakçay julia glushko', '6 - 4 , 7 - 5'], ['8 february 2010', 'cali , colombia', 'clay', 'edina gallovits', 'estrella cabeza candella laura pous tió', '3 - 6 , 6 - 3 ,']]

yankee small college conference

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10720390-1.html.csv

count

7 institutions in the yankee small college conference are public junior colleges .

{'scope': 'all', 'criterion': 'equal', 'value': 'public junior college', 'result': '7', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'affiliation', 'public junior college'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose affiliation record fuzzily matches to public junior college .', 'tostr': 'filter_eq { all_rows ; affiliation ; public junior college }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; affiliation ; public junior college } }', 'tointer': 'select the rows whose affiliation record fuzzily matches to public junior college . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; affiliation ; public junior college } } ; 7 } = true', 'tointer': 'select the rows whose affiliation record fuzzily matches to public junior college . the number of such rows is 7 .'}

eq { count { filter_eq { all_rows ; affiliation ; public junior college } } ; 7 } = true

select the rows whose affiliation record fuzzily matches to public junior college . the number of such rows is 7 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'affiliation_5': 5, 'public junior college_6': 6, '7_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'affiliation_5': 'affiliation', 'public junior college_6': 'public junior college', '7_7': '7'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'affiliation_5': [0], 'public junior college_6': [0], '7_7': [2]}

['institution', 'location', 'founded', 'affiliation', 'enrollment', 'team nickname']

[['central maine community college', 'auburn , maine', '1963', 'public junior college', '2720', 'mustangs'], ['college of st joseph', 'rutland , vermont', '1956', 'private', '500', 'saints'], ['eastern maine community college', 'bangor , maine', '1966', 'public junior college', '2099', 'golden eagles'], ['great bay community college', 'portsmouth , new hampshire', '1945', 'public junior college', '1850', 'herons'], ['hampshire college', 'amherst , massachusetts', '1965', 'private', '1463', 'frogs'], ['nashua community college', 'nashua , new hampshire', '1970', 'public junior college', '2147', 'jaguars'], ['new hampshire technical institute', 'concord , new hampshire', '1961', 'public junior college', '4127', 'capitals'], ['northern maine community college', 'presque isle , maine', '1961', 'public junior college', '1129', 'falcons'], ["paul smith 's college", 'paul smiths , new york', '1946', 'private', '1000', 'bobcats'], ['southern maine community college', 'south portland , maine', '1946', 'public junior college', '6261', 'seawolves'], ['university of maine at machias', 'machias , maine', '1909', 'public', '1200', 'clippers'], ['university of maine at augusta', 'augusta , maine', '1965', 'public', '5054', 'moose'], ['university of new hampshire club sports', 'durham , new hampshire', '1866', 'public', '15253', 'wildcats'], ['unity college', 'unity , maine', '1965', 'private', '564', 'rams'], ['vermont technical college', 'randolph , vermont', '1866', 'public', '1453', 'green knights']]

sheridan smith

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1644840-3.html.csv

majority

of the awards that sheridan smith was nominated for between the years of 2009 and 2013 , most of them she won .

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

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

most_eq { all_rows ; result ; won } = true

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

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'won_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'won_4': 'won'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'won_4': [0]}

['year', 'award', 'category', 'nominated work', 'result']

[['2009', 'laurence olivier award', 'best actress in a musical', 'little shop of horrors', 'nominated'], ['2010', 'evening standard award', 'best actress', 'legally blonde', 'nominated'], ['2011', 'laurence olivier award', 'best actress in a musical', 'legally blonde', 'won'], ['2011', "theatregoers ' choice award", 'best actress in a musical', 'legally blonde', 'won'], ['2011', 'evening standard award', 'best actress', 'flare path', 'won'], ['2011', 'broadwayworld uk award', 'best featured actress in a play', 'flare path', 'won'], ['2012', 'laurence olivier award', 'best performance in a supporting role', 'flare path', 'won'], ['2013', "theatregoers ' choice award", 'best actress in a play', 'hedda gabler', 'won'], ['2013', 'national television awards', 'outstanding drama performance ( female )', 'mrs biggs', 'nominated'], ['2013', 'royal television society awards', 'best actress', 'mrs biggs', 'nominated'], ['2013', 'british academy television award', 'best actress', 'mrs biggs', 'won'], ['2013', 'tv choice awards', 'best actress', 'mrs biggs', 'pending']]

major league soccer records and statistics

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11148572-1.html.csv

unique

2008 was the only year in which the columbus crew won the mls cup .

{'scope': 'all', 'row': '13', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'columbus crew', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mls cup winner', 'columbus crew'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mls cup winner record fuzzily matches to columbus crew .', 'tostr': 'filter_eq { all_rows ; mls cup winner ; columbus crew }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; mls cup winner ; columbus crew } }', 'tointer': 'select the rows whose mls cup winner record fuzzily matches to columbus crew . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mls cup winner', 'columbus crew'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mls cup winner record fuzzily matches to columbus crew .', 'tostr': 'filter_eq { all_rows ; mls cup winner ; columbus crew }'}, 'season'], 'result': '2008', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; mls cup winner ; columbus crew } ; season }'}, '2008'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; mls cup winner ; columbus crew } ; season } ; 2008 }', 'tointer': 'the season record of this unqiue row is 2008 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; mls cup winner ; columbus crew } } ; eq { hop { filter_eq { all_rows ; mls cup winner ; columbus crew } ; season } ; 2008 } } = true', 'tointer': 'select the rows whose mls cup winner record fuzzily matches to columbus crew . there is only one such row in the table . the season record of this unqiue row is 2008 .'}

and { only { filter_eq { all_rows ; mls cup winner ; columbus crew } } ; eq { hop { filter_eq { all_rows ; mls cup winner ; columbus crew } ; season } ; 2008 } } = true

select the rows whose mls cup winner record fuzzily matches to columbus crew . there is only one such row in the table . the season record of this unqiue row is 2008 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'mls cup winner_7': 7, 'columbus crew_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'season_9': 9, '2008_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'mls cup winner_7': 'mls cup winner', 'columbus crew_8': 'columbus crew', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'season_9': 'season', '2008_10': '2008'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'mls cup winner_7': [0], 'columbus crew_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'season_9': [2], '2008_10': [3]}

['season', 'mls cup winner', 'mls cup runner - up', 'mls supporters shield winner', 'mls supporters shield runner - up']

[['1996', 'dc united', 'los angeles galaxy', 'tampa bay mutiny', 'los angeles galaxy'], ['1997', 'dc united', 'colorado rapids', 'dc united', 'kansas city wizards'], ['1998', 'chicago fire', 'dc united', 'los angeles galaxy', 'dc united'], ['1999', 'dc united', 'los angeles galaxy', 'dc united', 'los angeles galaxy'], ['2000', 'kansas city wizards', 'chicago fire', 'kansas city wizards', 'chicago fire'], ['2001', 'san jose earthquakes', 'los angeles galaxy', 'miami fusion', 'chicago fire'], ['2002', 'los angeles galaxy', 'new england revolution', 'los angeles galaxy', 'san jose earthquakes'], ['2003', 'san jose earthquakes', 'chicago fire', 'chicago fire', 'san jose earthquakes'], ['2004', 'dc united', 'kansas city wizards', 'columbus crew', 'kansas city wizards'], ['2005', 'los angeles galaxy', 'new england revolution', 'san jose earthquakes', 'new england revolution'], ['2006', 'houston dynamo', 'new england revolution', 'dc united', 'fc dallas'], ['2007', 'houston dynamo', 'new england revolution', 'dc united', 'chivas usa'], ['2008', 'columbus crew', 'new york red bulls', 'columbus crew', 'houston dynamo'], ['2009', 'real salt lake', 'los angeles galaxy', 'columbus crew', 'los angeles galaxy'], ['2010', 'colorado rapids', 'fc dallas', 'los angeles galaxy', 'real salt lake'], ['2011', 'los angeles galaxy', 'houston dynamo', 'los angeles galaxy', 'seattle sounders fc'], ['2012', 'los angeles galaxy', 'houston dynamo', 'san jose earthquakes', 'sporting kansas city']]

1985 games of the small states of europe

https://en.wikipedia.org/wiki/1985_Games_of_the_Small_States_of_Europe

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11730098-1.html.csv

aggregation

the total number of bronze medals won at 1985 games of the small states of europe is 53 .

{'scope': 'all', 'col': '5', 'type': 'sum', 'result': '53', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'bronze'], 'result': '53', 'ind': 0, 'tostr': 'sum { all_rows ; bronze }'}, '53'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; bronze } ; 53 } = true', 'tointer': 'the sum of the bronze record of all rows is 53 .'}

round_eq { sum { all_rows ; bronze } ; 53 } = true

the sum of the bronze record of all rows is 53 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'bronze_4': 4, '53_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'bronze_4': 'bronze', '53_5': '53'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'bronze_4': [0], '53_5': [1]}

['rank', 'nation', 'gold', 'silver', 'bronze', 'total']

[['1', 'iceland', '21', '7', '4', '32'], ['2', 'cyprus', '15', '8', '9', '32'], ['3', 'luxembourg', '11', '23', '18', '52'], ['4', 'san marino', '2', '11', '11', '24'], ['5', 'andorra', '0', '0', '4', '4'], ['6', 'liechtenstein', '0', '0', '4', '4'], ['7', 'monaco', '0', '0', '2', '2'], ['8', 'malta', '0', '0', '1', '1']]

fc dnepr mogilev

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17140677-3.html.csv

majority

for the majority of dc dnepr mogilev 's season , the team competed in the eufa intertoto cup .

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

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

most_eq { all_rows ; competition ; uefa intertoto cup } = true

for the competition records of all rows , most of them fuzzily match to uefa intertoto cup .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, 'uefa intertoto cup_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', 'uefa intertoto cup_4': 'uefa intertoto cup'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], 'uefa intertoto cup_4': [0]}

['season', 'competition', 'round', 'club', '1st leg']

[['1995', 'uefa intertoto cup', 'group 8', 'bečej', '2 - 1 ( h )'], ['1995', 'uefa intertoto cup', 'group 8', 'pogoń szczecin', '3 - 3 ( a )'], ['1995', 'uefa intertoto cup', 'group 8', 'cannes', '2 - 2 ( h )'], ['1995', 'uefa intertoto cup', 'group 8', 'farul constanţa', '0 - 2 ( a )'], ['1998', 'uefa intertoto cup', '1r', 'debrecen', '2 - 4 ( h )'], ['1999 - 2000', 'uefa champions league', '2r', 'aik', '0 - 1 ( h )'], ['2000', 'uefa intertoto cup', '1r', 'silkeborg', '2 - 1 ( h )'], ['2000', 'uefa intertoto cup', '2r', 'chmel blšany', '2 - 6 ( a )'], ['2010 - 2011', 'uefa europa league', '1q', 'laçi', '1 - 1 ( a )'], ['2010 - 2011', 'uefa europa league', '2q', 'stabæk', '2 - 2 ( a )'], ['2010 - 2011', 'uefa europa league', '3q', 'baník ostrava', '1 - 0 ( h )'], ['2010 - 2011', 'uefa europa league', 'play - off', 'villareal', '0 - 5 ( a )']]

somerset county cricket club in 2010

https://en.wikipedia.org/wiki/Somerset_County_Cricket_Club_in_2010

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28846752-9.html.csv

count

7 players were members of the somerset county cricket club in the 2010 season .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '7', 'col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'player'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record is arbitrary .', 'tostr': 'filter_all { all_rows ; player }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; player } }', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; player } } ; 7 } = true', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 7 .'}

eq { count { filter_all { all_rows ; player } } ; 7 } = true

select the rows whose player record is arbitrary . the number of such rows is 7 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'player_5': 5, '7_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'player_5': 'player', '7_6': '7'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'player_5': [0], '7_6': [2]}

['player', 'matches', 'overs', 'wickets', 'average', 'economy', 'bbi', '4wi']

[['murali kartik', '10', '69.3', '20', '16.05', '4.61', '4 / 30', '1'], ['alfonso thomas', '14', '81.1', '27', '15.92', '5.29', '4 / 34', '2'], ['max waller', '8', '39.0', '4', '51.75', '5.30', '2 / 24', '0'], ['ben phillips', '13', '83.5', '19', '24.52', '5.55', '4 / 31', '1'], ['peter trego', '14', '75.3', '13', '33.00', '5.68', '2 / 29', '0'], ['zander de bruyn', '12', '47.2', '15', '19.40', '6.14', '3 / 27', '0'], ['mark turner', '6', '31.5', '9', '26.00', '7.35', '4 / 36', '1']]

1979 vfl season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823719-21.html.csv

majority

in the 1979 vfl season , all of the games took place on august 25 , 1979 .

{'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '25 august 1979', 'subset': None}

{'func': 'all_str_eq', 'args': ['all_rows', 'date', '25 august 1979'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 25 august 1979 .', 'tostr': 'all_eq { all_rows ; date ; 25 august 1979 } = true'}

all_eq { all_rows ; date ; 25 august 1979 } = true

for the date records of all rows , all of them fuzzily match to 25 august 1979 .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '25 august 1979_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '25 august 1979_4': '25 august 1979'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '25 august 1979_4': [0]}

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

[['melbourne', '24.17 ( 161 )', 'st kilda', '12.24 ( 96 )', 'mcg', '18435', '25 august 1979'], ['hawthorn', '7.18 ( 60 )', 'north melbourne', '24.21 ( 165 )', 'princes park', '18501', '25 august 1979'], ['geelong', '17.13 ( 115 )', 'richmond', '12.17 ( 89 )', 'kardinia park', '18039', '25 august 1979'], ['fitzroy', '22.19 ( 151 )', 'footscray', '14.16 ( 100 )', 'junction oval', '12076', '25 august 1979'], ['collingwood', '18.12 ( 120 )', 'carlton', '14.17 ( 101 )', 'victoria park', '36509', '25 august 1979'], ['essendon', '13.17 ( 95 )', 'south melbourne', '10.16 ( 76 )', 'vfl park', '32127', '25 august 1979']]

list of how it 's made episodes

https://en.wikipedia.org/wiki/List_of_How_It%27s_Made_episodes

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15187735-19.html.csv

unique

of these episodes , only episode 238 shows how canned tomatoes are made .

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

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment b', 'canned tomatoes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment b record fuzzily matches to canned tomatoes .', 'tostr': 'filter_eq { all_rows ; segment b ; canned tomatoes }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; segment b ; canned tomatoes } }', 'tointer': 'select the rows whose segment b record fuzzily matches to canned tomatoes . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment b', 'canned tomatoes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment b record fuzzily matches to canned tomatoes .', 'tostr': 'filter_eq { all_rows ; segment b ; canned tomatoes }'}, 'episode'], 'result': '238', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; segment b ; canned tomatoes } ; episode }'}, '238'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; segment b ; canned tomatoes } ; episode } ; 238 }', 'tointer': 'the episode record of this unqiue row is 238 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; segment b ; canned tomatoes } } ; eq { hop { filter_eq { all_rows ; segment b ; canned tomatoes } ; episode } ; 238 } } = true', 'tointer': 'select the rows whose segment b record fuzzily matches to canned tomatoes . there is only one such row in the table . the episode record of this unqiue row is 238 .'}

and { only { filter_eq { all_rows ; segment b ; canned tomatoes } } ; eq { hop { filter_eq { all_rows ; segment b ; canned tomatoes } ; episode } ; 238 } } = true

select the rows whose segment b record fuzzily matches to canned tomatoes . there is only one such row in the table . the episode record of this unqiue row is 238 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'segment b_7': 7, 'canned tomatoes_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'episode_9': 9, '238_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'segment b_7': 'segment b', 'canned tomatoes_8': 'canned tomatoes', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'episode_9': 'episode', '238_10': '238'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'segment b_7': [0], 'canned tomatoes_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'episode_9': [2], '238_10': [3]}

['series ep', 'episode', 'segment a', 'segment b', 'segment c', 'segment d']

[['19 - 01', '235', 'garden forks', 'english toffee', 'paint chip cards', 'bundt s pan'], ['19 - 02', '236', 'pewter flasks', 'potato salad', 'hydrogen s fuel cell', 'engineered wood siding'], ['19 - 03', '237', 'canvas wall s tent', 's peace pipe', 'shredded wheat cereal', 's cannon'], ['19 - 04', '238', 'ic robot ing hunt s decoy', 'canned tomatoes', 's scoreboard', 's lasso'], ['19 - 05', '239', 'turf grass', 'beef jerky', 'wood chippers', 'bowling pins'], ['19 - 06', '240', 's multi - tool', 'jojoba oil', 's marionette ( part 1 )', 's marionette ( part 2 )'], ['19 - 07', '241', 'fish decoys', 'film digitization', 'cylinder stoves', 'concrete light poles'], ['19 - 08', '242', 'bamboo bicycles', 'chainsaw art', 'breath mints', 'manual motorcycle transmissions'], ['19 - 09', '243', 'dinnerware', 'air brake tanks', 'frosted cereal', 's fossil'], ['19 - 10', '244', 'clay', 'pitted prunes', 's spur', 'polyurethane tires'], ['19 - 11', '245', 's taser', 'canned soup', 'jaw harps & mouth bows', 's diving board'], ['19 - 12', '246', 'navajo rugs', 'crude oil', 's kaleidoscope', 'titanium dental implants']]

1952 vfl season

https://en.wikipedia.org/wiki/1952_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10750694-12.html.csv

ordinal

in the 1952 vfl season , the 2nd largest crowd happened when the home team was south melbourne .

{'row': '5', 'col': '6', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

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

eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; south melbourne } = true

select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is south melbourne .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '2_6': 6, 'home team_7': 7, 'south melbourne_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '2_6': '2', 'home team_7': 'home team', 'south melbourne_8': 'south melbourne'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '2_6': [0], 'home team_7': [1], 'south melbourne_8': [2]}

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

[['richmond', '10.17 ( 77 )', 'st kilda', '6.8 ( 44 )', 'punt road oval', '9000', '12 july 1952'], ['footscray', '4.11 ( 35 )', 'hawthorn', '9.4 ( 58 )', 'western oval', '12218', '12 july 1952'], ['fitzroy', '13.11 ( 89 )', 'north melbourne', '10.11 ( 71 )', 'brunswick street oval', '10500', '12 july 1952'], ['carlton', '6.14 ( 50 )', 'melbourne', '6.14 ( 50 )', 'princes park', '24839', '12 july 1952'], ['south melbourne', '8.12 ( 60 )', 'essendon', '9.15 ( 69 )', 'lake oval', '27000', '12 july 1952'], ['geelong', '9.8 ( 62 )', 'collingwood', '4.9 ( 33 )', 'kardinia park', '36145', '12 july 1952']]

1982 atlanta falcons season

https://en.wikipedia.org/wiki/1982_Atlanta_Falcons_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16710829-2.html.csv

majority

the atlanta falcons won most games in the month of december during the 1982 season .

{'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'win', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'dec'}}

{'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'dec'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; dec }', 'tointer': 'select the rows whose date record fuzzily matches to dec .'}, 'result', 'win'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to dec . for the result records of these rows , most of them fuzzily match to win .', 'tostr': 'most_eq { filter_eq { all_rows ; date ; dec } ; result ; win } = true'}

most_eq { filter_eq { all_rows ; date ; dec } ; result ; win } = true

select the rows whose date record fuzzily matches to dec . for the result records of these rows , most of them fuzzily match to win .

2

2

{'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'dec_5': 5, 'result_6': 6, 'win_7': 7}

{'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'dec_5': 'dec', 'result_6': 'result', 'win_7': 'win'}

{'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'dec_5': [0], 'result_6': [1], 'win_7': [1]}

['game', 'date', 'opponent', 'result', 'falcons points', 'opponents', 'record', 'attendance']

[['1', 'sept 12', 'new york giants', 'win', '16', '14', '1 - 0', '74286'], ['2', 'sept 19', 'los angeles raiders', 'loss', '14', '38', '1 - 1', '54774'], ['3', 'nov 21', 'los angeles rams', 'win', '34', '17', '2 - 1', '39686'], ['4', 'nov 28', 'st louis cardinals', 'loss', '20', '23', '2 - 2', '33411'], ['5', 'dec 5', 'denver broncos', 'win', '34', '27', '3 - 2', '73984'], ['6', 'dec 12', 'new orleans saints', 'win', '35', '0', '4 - 2', '39535'], ['7', 'dec 19', 'san francisco 49ers', 'win', '17', '7', '5 - 2', '53234'], ['8', 'dec 26', 'green bay packers', 'loss', '7', '38', '5 - 3', '50245'], ['9', 'jan 2', 'new orleans saints', 'loss', '6', '35', '5 - 4', '47336']]

2009 - 10 pittsburgh panthers men 's basketball team

https://en.wikipedia.org/wiki/2009%E2%80%9310_Pittsburgh_Panthers_men%27s_basketball_team

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24925945-3.html.csv

comparative

for the 2009 - 10 pittsburgh panthers men 's basketball team , dante taylor weighed 20 pounds more than nasir robinson .

{'row_1': '12', 'row_2': '11', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'dante taylor'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to dante taylor .', 'tostr': 'filter_eq { all_rows ; name ; dante taylor }'}, 'weight ( lb )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; dante taylor } ; weight ( lb ) }', 'tointer': 'select the rows whose name record fuzzily matches to dante taylor . take the weight ( lb ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'nasir robinson'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to nasir robinson .', 'tostr': 'filter_eq { all_rows ; name ; nasir robinson }'}, 'weight ( lb )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; nasir robinson } ; weight ( lb ) }', 'tointer': 'select the rows whose name record fuzzily matches to nasir robinson . take the weight ( lb ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; dante taylor } ; weight ( lb ) } ; hop { filter_eq { all_rows ; name ; nasir robinson } ; weight ( lb ) } } = true', 'tointer': 'select the rows whose name record fuzzily matches to dante taylor . take the weight ( lb ) record of this row . select the rows whose name record fuzzily matches to nasir robinson . take the weight ( lb ) record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; name ; dante taylor } ; weight ( lb ) } ; hop { filter_eq { all_rows ; name ; nasir robinson } ; weight ( lb ) } } = true

select the rows whose name record fuzzily matches to dante taylor . take the weight ( lb ) record of this row . select the rows whose name record fuzzily matches to nasir robinson . take the weight ( lb ) record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'dante taylor_8': 8, 'weight ( lb )_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'nasir robinson_12': 12, 'weight ( lb )_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'dante taylor_8': 'dante taylor', 'weight ( lb )_9': 'weight ( lb )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'nasir robinson_12': 'nasir robinson', 'weight ( lb )_13': 'weight ( lb )'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'dante taylor_8': [0], 'weight ( lb )_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'nasir robinson_12': [1], 'weight ( lb )_13': [3]}

['name', '-', 'position', 'height', 'weight ( lb )', 'year', 'hometown', 'previous school']

[['chase adams', '3', 'guard', 'ft10in ( m )', '190', '2 senior', 'baltimore , md', 'centenary / mount saint joseph hs'], ['gilbert brown', '5', 'guard / forward', 'ft6in ( m )', '200', '2 junior ( rs )', 'harrisburg , pa', 'south kent school'], ['jermaine dixon', '24', 'guard', 'ft3in ( m )', '200', '3 senior , transfer', 'baltimore , md', 'tallahassee cc / maine central inst / blake hs'], ['tim frye', '44', 'guard', 'ft4in ( m )', '205', '2 junior', 'mars , pa', 'mars area hs'], ['ashton gibbs', '12', 'guard', 'ft2in ( m )', '190', '1 sophomore', 'scotch plains , nj', 'seton hall prep'], ['gary mcghee', '52', 'center', 'ft10in ( m )', '250', '2 junior', 'anderson , in', 'highland hs'], ['dwight miller', '25', 'forward', 'ft8in ( m )', '240', '1 freshman ( rs )', 'nassau , bahamas', 'st pius x hs'], ['lamar patterson', '21', 'guard / forward', 'ft5in ( m )', '220', '1 freshman', 'lancaster , pa', "st benedict 's prep / jp mccaskey hs"], ['jj richardson', '55', 'forward', 'ft7in ( m )', '235', '1 freshman', 'missouri city , tx', 'fort bend hightower hs'], ['nick rivers', '14', 'guard', 'ft0in ( m )', '180', '1 junior', 'phoenix , az', 'brophy college prep'], ['nasir robinson', '35', 'forward', 'ft5in ( m )', '220', '1 sophomore', 'chester , pa', 'chester hs'], ['dante taylor', '11', 'forward', 'ft9in ( m )', '240', '1 freshman', 'greenburgh , ny', 'national christian academy ( md )'], ['brad wanamaker', '22', 'guard', 'ft4in ( m )', '210', '2 junior', 'philadelphia , pa', 'roman catholic hs'], ['travon woodall', '1', 'guard', 'ft11in ( m )', '190', '1 freshman ( rs )', 'brooklyn , ny', 'st anthony hs']]

2007 - 08 leb season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16176685-4.html.csv

ordinal

jakim donaldson scored the highest number of points during the 2007 - 08 leb season .

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

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

eq { hop { nth_argmax { all_rows ; points ; 1 } ; name } ; jakim donaldson } = true

select the row whose points record of all rows is 1st maximum . the name record of this row is jakim donaldson .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, '1_6': 6, 'name_7': 7, 'jakim donaldson_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', '1_6': '1', 'name_7': 'name', 'jakim donaldson_8': 'jakim donaldson'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], '1_6': [0], 'name_7': [1], 'jakim donaldson_8': [2]}

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

[['1', 'jakim donaldson', 'ciudad de la laguna', '36', '357'], ['2', 'oriol junyent', 'ciudad de huelva', '21', '204'], ['3', 'serge ibaka', "l'hospitalet", '28', '234'], ['4', 'ondrej starosta', 'cai zaragoza', '34', '259'], ['5', 'andrew panko', 'bruesa gbc', '38', '287']]

hiroshi izumi

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12149929-2.html.csv

majority

most of the fights in hiroshi izumi 's record resulted in his win .

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

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

most_eq { all_rows ; res ; win } = true

for the res records of all rows , most of them fuzzily match to win .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'res_3': 3, 'win_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'res_3': 'res', 'win_4': 'win'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'res_3': [0], 'win_4': [0]}

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

[['loss', '4 - 2', 'gegard mousasi', 'tko ( punches )', '1', '3:28', 'tokyo , japan'], ['win', '4 - 1', 'ikuhisa minowa', 'tko ( punches )', '3', '2:50', 'saitama , saitama , japan'], ['win', '3 - 1', 'james zikic', 'decision ( split )', '3', '5:00', 'tokyo , japan'], ['win', '2 - 1', 'chang seob lee', 'tko ( punches )', '1', '4:37', 'tokyo , japan'], ['win', '1 - 1', 'katsuyori shibata', 'decision ( unanimous )', '3', '5:00', 'saitama , saitama , japan'], ['loss', '0 - 1', 'antz nansen', 'tko ( punches )', '1', '2:56', 'saitama , saitama , japan']]

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/2-11545282-1.html.csv

unique

john amaechi is the only player on the utah jazz all - time roster from penn state .

{'scope': 'all', 'row': '2', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'penn state', 'subset': None}

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

and { only { filter_eq { all_rows ; school / club team ; penn state } } ; eq { hop { filter_eq { all_rows ; school / club team ; penn state } ; player } ; john amaechi } } = true

select the rows whose school / club team record fuzzily matches to penn state . there is only one such row in the table . the player record of this unqiue row is john amaechi .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'school / club team_7': 7, 'penn state_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'john amaechi_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'school / club team_7': 'school / club team', 'penn state_8': 'penn state', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'john amaechi_10': 'john amaechi'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'school / club team_7': [0], 'penn state_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'john amaechi_10': [3]}

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

[['rick adelman', 'united states', 'guard', '1974 - 75', 'loyola ( ca )'], ['john amaechi', 'england', 'center / forward', '2001 - 03', 'penn state'], ['louis amundson', 'united states', 'forward', '2007', 'unlv'], ['j j anderson', 'united states', 'forward', '1982 - 85', 'bradley'], ['shandon anderson', 'united states', 'guard / forward', '1996 - 99', 'georgia'], ['rafael araãjo', 'brazil', 'center', '2006 - 2007', 'byu'], ['carlos arroyo', 'puerto rico', 'guard', '2002 - 05', 'florida international'], ['isaac austin', 'united states', 'center', '1991 - 93', 'arizona state'], ['anthony avent', 'united states', 'forward', '1998 - 99', 'seton hall']]

1990 - 91 dundee united f.c. season

https://en.wikipedia.org/wiki/1990%E2%80%9391_Dundee_United_F.C._season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15255963-3.html.csv

count

dundee united f.c. had east fife as their opponent two times in the 1990-91 season .

{'scope': 'all', 'criterion': 'equal', 'value': 'east fife', 'result': '2', 'col': '2', 'subset': None}

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

eq { count { filter_eq { all_rows ; opponent ; east fife } } ; 2 } = true

select the rows whose opponent record fuzzily matches to east fife . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'east fife_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'east fife_6': 'east fife', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'east fife_6': [0], '2_7': [2]}

['date', 'opponent', 'venue', 'result', 'attendance', 'scorers']

[['26 january 1990', 'east fife', 'a', '1 - 1', '4947', 'connolly'], ['29 january 1990', 'east fife', 'h', '2 - 1', '7190', 'clark , ferguson'], ['23 february 1990', 'airdrieonians', 'h', '2 - 0', '8648', 'french ( 2 )'], ['13 march 1990', 'dundee', 'h', '3 - 1', '16228', 'mckinnon , jackson , ferguson'], ['6 april 1991', 'st johnstone', 'n', '0 - 0', '16560', 'clark , ferguson'], ['18 may 1991', 'motherwell', 'n', '3 - 4', '57319', "bowman , j o'neil , jackson"]]

bc lietuvos rytas

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1771141-1.html.csv

unique

2005-06 was the only bc lietuvos rytas season that neven spahija was the head coach .

{'scope': 'all', 'row': '9', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'neven spahija', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'head coach', 'neven spahija'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose head coach record fuzzily matches to neven spahija .', 'tostr': 'filter_eq { all_rows ; head coach ; neven spahija }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; head coach ; neven spahija } }', 'tointer': 'select the rows whose head coach record fuzzily matches to neven spahija . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'head coach', 'neven spahija'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose head coach record fuzzily matches to neven spahija .', 'tostr': 'filter_eq { all_rows ; head coach ; neven spahija }'}, 'season'], 'result': '2005 - 06', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; head coach ; neven spahija } ; season }'}, '2005 - 06'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; head coach ; neven spahija } ; season } ; 2005 - 06 }', 'tointer': 'the season record of this unqiue row is 2005 - 06 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; head coach ; neven spahija } } ; eq { hop { filter_eq { all_rows ; head coach ; neven spahija } ; season } ; 2005 - 06 } } = true', 'tointer': 'select the rows whose head coach record fuzzily matches to neven spahija . there is only one such row in the table . the season record of this unqiue row is 2005 - 06 .'}

and { only { filter_eq { all_rows ; head coach ; neven spahija } } ; eq { hop { filter_eq { all_rows ; head coach ; neven spahija } ; season } ; 2005 - 06 } } = true

select the rows whose head coach record fuzzily matches to neven spahija . there is only one such row in the table . the season record of this unqiue row is 2005 - 06 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'head coach_7': 7, 'neven spahija_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'season_9': 9, '2005 - 06_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'head coach_7': 'head coach', 'neven spahija_8': 'neven spahija', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'season_9': 'season', '2005 - 06_10': '2005 - 06'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'head coach_7': [0], 'neven spahija_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'season_9': [2], '2005 - 06_10': [3]}

['season', 'lkf cup', 'regional competitions', 'europe', 'head coach']

[['1997 - 98', 'champion', '-', 'korać cup group stage', 'modestas paulauskas , alfredas vainauskas'], ['1998 - 99', '-', 'nebl 3rd place', 'saporta cup group stage', 'vainauskas , sakalauskas'], ['1999 - 00', '-', 'nebl finalist', 'saporta cup semifinalist', 'vainauskas , sakalauskas'], ['2000 - 01', '-', 'nebl 3rd place', 'suproleague top 16', 'šarūnas sakalauskas , alfredas vainauskas'], ['2001 - 02', '-', 'nebl champion', 'saporta cup quarterfinalist', 'jonas kazlauskas'], ['2002 - 03', '-', 'nebl finalist', 'champions cup group stage', 'jonas kazlauskas'], ['2003 - 04', '-', '-', 'uleb cup quarterfinalist', 'kazlauskas , kemzūra'], ['2004 - 05', '-', 'bbl elite division finalist', 'uleb cup champion', 'vlade djurović , tomo mahorić'], ['2005 - 06', '-', 'bbl elite division champion', 'euroleague top 16', 'neven spahija'], ['2006 - 07', 'finalist', 'bbl elite division champion', 'uleb cup finalist', 'drucker , sagadin , trifunović'], ['2007 - 08', 'finalist', 'bbl elite division finalist', 'euroleague top 16', 'aleksandar trifunović'], ['2008 - 09', 'champion', 'bbl elite division champion', 'eurocup champion', 'antanas sireika , rimas kurtinaitis'], ['2009 - 10', 'champion', 'bbl elite division finalist', 'euroleague group stage', 'rimas kurtinaitis'], ['2010 - 11', 'finalist', 'bbl elite division 3rd place', 'euroleague top 16', 'anzulović , trifunović , maskoliūnas'], ['2010 - 11', 'finalist', 'vtb group stage', 'euroleague top 16', 'anzulović , trifunović , maskoliūnas'], ['2011 - 12', '-', 'bbl elite division finalist', 'eurocup 3rd place', 'aleksandar džikić'], ['2011 - 12', '-', 'vtb 3rd place', 'eurocup 3rd place', 'aleksandar džikić'], ['2012 - 13', '-', 'vtb group stage', 'euroleague group stage', 'džikić , maskoliūnas , bauermann']]

b " 2008 world men 's curling championship "

https://en.wikipedia.org/wiki/2008_World_Men%27s_Curling_Championship

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1644857-2.html.csv

count

12 countries were represented in the 2008 world men 's curling championship .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '12', 'col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'country'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record is arbitrary .', 'tostr': 'filter_all { all_rows ; country }'}], 'result': '12', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; country } }', 'tointer': 'select the rows whose country record is arbitrary . the number of such rows is 12 .'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; country } } ; 12 } = true', 'tointer': 'select the rows whose country record is arbitrary . the number of such rows is 12 .'}

eq { count { filter_all { all_rows ; country } } ; 12 } = true

select the rows whose country record is arbitrary . the number of such rows is 12 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'country_5': 5, '12_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'country_5': 'country', '12_6': '12'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'country_5': [0], '12_6': [2]}

['country', 'skip', 'ends won', 'ends lost', 'blank ends', 'stolen ends', 'shot %']

[['canada', 'kevin martin', '49', '37', '10', '14', '87'], ['scotland', 'david murdoch', '46', '38', '20', '10', '85'], ['china', 'wang fengchun', '43', '43', '18', '9', '81'], ['norway', 'thomas ulsrud', '52', '47', '10', '11', '84'], ['france', 'thomas dufour', '42', '35', '18', '11', '78'], ['australia', 'hugh millikin', '42', '45', '20', '8', '78'], ['united states', 'craig brown', '40', '44', '13', '6', '81'], ['germany', 'andy kapp', '47', '43', '17', '14', '80'], ['denmark', 'johnny frederiksen', '45', '50', '6', '11', '78'], ['sweden', 'anders kraupp', '38', '49', '17', '4', '79'], ['switzerland', 'claudio pescia', '42', '49', '15', '7', '78'], ['czech republic', 'jiří snítil', '43', '48', '10', '7', '75']]

united states house of representatives elections , 1976

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1976

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341672-6.html.csv

majority

most of the democratic candidates elected to the united states house of representatives in 1976 were first elected before 1970 .

{'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1970', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'democratic'}}

{'func': 'most_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; party ; democratic }', 'tointer': 'select the rows whose party record fuzzily matches to democratic .'}, 'first elected', '1970'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose party record fuzzily matches to democratic . for the first elected records of these rows , most of them are less than 1970 .', 'tostr': 'most_less { filter_eq { all_rows ; party ; democratic } ; first elected ; 1970 } = true'}

most_less { filter_eq { all_rows ; party ; democratic } ; first elected ; 1970 } = true

select the rows whose party record fuzzily matches to democratic . for the first elected records of these rows , most of them are less than 1970 .

2

2

{'most_less_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'party_4': 4, 'democratic_5': 5, 'first elected_6': 6, '1970_7': 7}

{'most_less_1': 'most_less', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'party_4': 'party', 'democratic_5': 'democratic', 'first elected_6': 'first elected', '1970_7': '1970'}

{'most_less_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'party_4': [0], 'democratic_5': [0], 'first elected_6': [1], '1970_7': [1]}

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

[['california 4', 'robert l leggett', 'democratic', '1962', 're - elected', 'robert l leggett ( d ) 50.2 % albert dehr ( r ) 49.8 %'], ['california 14', 'john j mcfall', 'democratic', '1956', 're - elected', 'john j mcfall ( d ) 72.5 % roger a blain ( r ) 27.5 %'], ['california 16', 'burt l talcott', 'republican', '1962', 'lost re - election democratic gain', 'leon panetta ( d ) 53.4 % burt l talcott ( r ) 46.6 %'], ['california 18', 'william m ketchum', 'republican', '1972', 're - elected', 'william m ketchum ( r ) 64.2 % dean close ( d ) 35.8 %'], ['california 26', 'john h rousselot', 'republican', '1970', 're - elected', 'john h rousselot ( r ) 65.6 % bruce latta ( d ) 34.4 %'], ['california 27', 'alphonzo e bell , jr', 'republican', '1960', 'retired to run for u s senate republican hold', 'bob dornan ( r ) 54.7 % gary familian ( d ) 45.3 %'], ['california 31', 'charles h wilson', 'democratic', '1962', 're - elected', 'charles h wilson ( d ) unopposed'], ['california 33', 'del m clawson', 'republican', '1963', 're - elected', 'del m clawson ( r ) 55.1 % ted snyder ( d ) 44.9 %'], ['california 34', 'mark w hannaford', 'democratic', '1974', 're - elected', 'mark w hannaford ( d ) 50.7 % dan lungren ( r ) 49.3 %'], ['california 35', 'james f lloyd', 'democratic', '1974', 're - elected', 'james f lloyd ( d ) 53.3 % louis brutocao ( r ) 46.7 %'], ['california 40', 'andrew j hinshaw', 'republican', '1972', 'lost renomination republican hold', 'robert badham ( r ) 59.3 % vivian hall ( d ) 40.7 %'], ['california 41', 'bob wilson', 'republican', '1952', 're - elected', 'bob wilson ( r ) 57.7 % king golden , jr ( d ) 42.3 %'], ['california 42', 'lionel van deerlin', 'democratic', '1962', 're - elected', 'lionel van deerlin ( d ) 76.0 % wes marden ( r ) 24.0 %']]

north island main trunk

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1799173-1.html.csv

ordinal

the north auckland line is the second longest north island main truck line .

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

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

eq { hop { nth_argmax { all_rows ; length ; 2 } ; line name } ; north auckland line } = true

select the row whose length record of all rows is 2nd maximum . the line name record of this row is north auckland line .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'length_5': 5, '2_6': 6, 'line name_7': 7, 'north auckland line_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'length_5': 'length', '2_6': '2', 'line name_7': 'line name', 'north auckland line_8': 'north auckland line'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'length_5': [0], '2_6': [0], 'line name_7': [1], 'north auckland line_8': [2]}

['line name', 'date closed', 'nimt junction', 'terminus', 'length']

[['auckland - newmarket line', 'open', 'quay park junction', 'newmarket junction', '2.5 km'], ['north auckland line', 'open', 'westfield junction', 'otiria junction', '280 km'], ['manukau branch', 'open', 'wiri junction', 'manukau', '2.5 km'], ['mission bush branch', 'open', 'paerata junction', 'mission bush', '17 km'], ['kimihia branch', 'open', 'huntly north', 'kimihia mine', '2.75 km'], ['rotowaro branch', 'open', 'huntly', 'rotowaro', '8.5 km'], ['waipa railway and coal co line', '19 - 5 - 1958', 'ngaruawahia', 'wilton collieries', '10.5 km'], ['east coast main trunk railway', 'open', 'frankton junction', 'kawerau', '180 km'], ['stratford - okahukura line', 'mothballed 2009', 'okahukura junction', 'stratford', '144 km'], ['raetihi branch', '1 - 1 - 1968', 'ohakune junction', 'raetihi', '13 km'], ['marton - new plymouth line', 'open', 'marton junction', 'breakwater ( new plymouth )', '212 km'], ['taonui branch', '14 - 8 - 1895', 'taonui', 'colyton', '3.5 km'], ['palmerston north - gisborne line', 'open', 'roslyn junction', 'gisborne', '391 km'], ['foxton branch', '18 - 7 - 1959', 'longburn junction', 'foxton', '31 km'], ['wairarapa line', 'open', 'distant junction ( wellington )', 'woodville', '170 km'], ['johnsonville branch', 'open', 'wellington junction', 'johnsonville', '10 km'], ['te aro branch', '23 - 4 - 1917', 'wellington ( lambton )', 'te aro', '1.77 km']]

2008 - 09 kansas jayhawks men 's basketball team

https://en.wikipedia.org/wiki/2008%E2%80%9309_Kansas_Jayhawks_men%27s_basketball_team

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17728794-2.html.csv

unique

on the 08 ' -09 ' kansas jayhawks basketball team , tyshawn taylor was the only peron with a weight of 160 .

{'scope': 'all', 'row': '14', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '160', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'weight', '160'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose weight record is equal to 160 .', 'tostr': 'filter_eq { all_rows ; weight ; 160 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; weight ; 160 } }', 'tointer': 'select the rows whose weight record is equal to 160 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'weight', '160'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose weight record is equal to 160 .', 'tostr': 'filter_eq { all_rows ; weight ; 160 }'}, 'name'], 'result': 'tyshawn taylor', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; weight ; 160 } ; name }'}, 'tyshawn taylor'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; weight ; 160 } ; name } ; tyshawn taylor }', 'tointer': 'the name record of this unqiue row is tyshawn taylor .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; weight ; 160 } } ; eq { hop { filter_eq { all_rows ; weight ; 160 } ; name } ; tyshawn taylor } } = true', 'tointer': 'select the rows whose weight record is equal to 160 . there is only one such row in the table . the name record of this unqiue row is tyshawn taylor .'}

and { only { filter_eq { all_rows ; weight ; 160 } } ; eq { hop { filter_eq { all_rows ; weight ; 160 } ; name } ; tyshawn taylor } } = true

select the rows whose weight record is equal to 160 . there is only one such row in the table . the name record of this unqiue row is tyshawn taylor .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'weight_7': 7, '160_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'tyshawn taylor_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'weight_7': 'weight', '160_8': '160', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'tyshawn taylor_10': 'tyshawn taylor'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'weight_7': [0], '160_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'tyshawn taylor_10': [3]}

['name', 'position', 'height', 'weight', 'year', 'home town']

[['cole aldrich', 'center', '6 - 11', '245', 'sophomore', 'bloomington , mn'], ['tyrone appleton', 'guard', '6 - 3', '190', 'junior', 'midland , texas'], ['brennan bechard', 'guard', '6 - 0', '183', 'senior', 'lawrence , ks'], ['chase buford', 'guard', '6 - 3', '200', 'sophomore', 'san antonio , texas'], ['sherron collins', 'guard', '5 - 11', '200', 'junior', 'chicago , il'], ['jordan juenemann', 'guard', '6 - 4', '195', 'freshman', 'hays , ks'], ['matt kleinmann', 'center', '6 - 10', '247', 'senior', 'overland park , ks'], ['mario little', 'forward', '6 - 5', '210', 'junior', 'marianna , fl'], ['brady morningstar', 'guard', '6 - 3', '185', 'sophomore', 'lawrence , ks'], ['marcus morris', 'forward', '6 - 8', '230', 'freshman', 'pennsauken , nj'], ['markieff morris', 'forward', '6 - 9', '220', 'freshman', 'pennsauken , nj'], ['tyrel reed', 'guard', '6 - 3', '180', 'sophomore', 'burlington , ks'], ['travis releford', 'guard', '6 - 5', '190', 'freshman', 'shawnee mission , ks'], ['tyshawn taylor', 'guard', '6 - 3', '160', 'freshman', 'jersey city , nj'], ['conner teahan', 'guard', '6 - 5', '200', 'sophomore', 'leawood , ks'], ['quintrell thomas', 'forward', '6 - 8', '225', 'freshman', 'elizabeth , nj']]

cycling at the 2008 summer olympics - men 's bmx

https://en.wikipedia.org/wiki/Cycling_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_BMX

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18603914-3.html.csv

superlative

ivo lakučs had the highest total in men 's bmx at the 2008 summer olympics .

{'scope': 'all', 'col_superlative': '6', 'row_superlative': '8', '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', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'name'], 'result': 'ivo lakučs ( lat )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; name }'}, 'ivo lakučs ( lat )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; name } ; ivo lakučs ( lat ) } = true', 'tointer': 'select the row whose total record of all rows is maximum . the name record of this row is ivo lakučs ( lat ) .'}

eq { hop { argmax { all_rows ; total } ; name } ; ivo lakučs ( lat ) } = true

select the row whose total record of all rows is maximum . the name record of this row is ivo lakučs ( lat ) .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'name_6': 6, 'ivo lakučs ( lat )_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'name_6': 'name', 'ivo lakučs ( lat )_7': 'ivo lakučs ( lat )'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'name_6': [1], 'ivo lakučs ( lat )_7': [2]}

['rank', 'name', '1st run', '2nd run', '3rd run', 'total']

[['1', 'mike day ( usa )', '36.170 ( 1 )', '36.080 ( 1 )', '36.122 ( 1 )', '3'], ['2', 'marc willers ( nzl )', '47.614 ( 4 )', '36.253 ( 3 )', '36.278 ( 2 )', '9'], ['3', 'donny robinson ( usa )', '48.906 ( 6 )', '36.235 ( 2 )', '36.490 ( 3 )', '11'], ['4', 'andrés jiménez caicedo ( col )', '36.619 ( 2 )', '36.939 ( 5 )', '36.660 ( 4 )', '11'], ['5', 'jonathan suárez ( ven )', '53.614 ( 8 )', '36.481 ( 4 )', '36.789 ( 5 )', '17'], ['6', 'emilio falla ( ecu )', '37.080 ( 3 )', '37.381 ( 6 )', '1:02.877 ( 8 )', '17'], ['7', 'akifumi sakamoto ( jpn )', '48.487 ( 5 )', '42.614 ( 8 )', '40.046 ( 6 )', '19'], ['8', 'ivo lakučs ( lat )', '53.300 ( 7 )', '39.213 ( 7 )', '57.461 ( 7 )', '21']]

don freeland

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1236238-1.html.csv

superlative

the best starting position that don freeland had in his participations in indy 500 was in 1954 .

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

{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'start'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; start }'}, 'year'], 'result': '1954', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; start } ; year }'}, '1954'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; start } ; year } ; 1954 } = true', 'tointer': 'select the row whose start record of all rows is minimum . the year record of this row is 1954 .'}

eq { hop { argmin { all_rows ; start } ; year } ; 1954 } = true

select the row whose start record of all rows is minimum . the year record of this row is 1954 .

3

3

{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'start_5': 5, 'year_6': 6, '1954_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'start_5': 'start', 'year_6': 'year', '1954_7': '1954'}

{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'start_5': [0], 'year_6': [1], '1954_7': [2]}

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

[['1953', '15', '136.867', '12', '27', '76'], ['1954', '6', '138.339', '17', '7', '200'], ['1955', '21', '139.866', '14', '15', '178'], ['1956', '26', '141.699', '22', '3', '200'], ['1957', '21', '139.649', '33', '17', '192'], ['1958', '13', '143.033', '17', '7', '200'], ['1959', '25', '143.056', '14', '22', '136'], ['1960', '11', '144.352', '14', '22', '129']]

royal canadian mint ice hockey coins

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12991375-7.html.csv

count

2 of the royal canadian mint ice hockey coins were of the theme montreal canadiens .

{'scope': 'all', 'criterion': 'equal', 'value': 'montreal canadiens', 'result': '2', 'col': '2', 'subset': None}

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

eq { count { filter_eq { all_rows ; theme ; montreal canadiens } } ; 2 } = true

select the rows whose theme record fuzzily matches to montreal canadiens . 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, 'theme_5': 5, 'montreal canadiens_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', 'theme_5': 'theme', 'montreal canadiens_6': 'montreal canadiens', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'theme_5': [0], 'montreal canadiens_6': [0], '2_7': [2]}

['year', 'theme', 'artist', 'mintage', 'issue price', 'special notes']

[['2006', 'montreal canadiens', 'n / a', 'n / a', '24.95', 'from montreal canadiens gift set'], ['2006', 'ottawa senators', 'n / a', 'n / a', '24.95', 'from ottawa senators gift set'], ['2006', 'toronto maple leafs', 'n / a', 'n / a', '24.95', 'from toronto maple leafs gift set'], ['2007', 'calgary flames', 'n / a', '832', '24.95', 'from calgary flames gift set'], ['2007', 'edmonton oilers', 'n / a', '2213', '24.95', 'from edmonton oilers gift set'], ['2007', 'montreal canadiens', 'n / a', '2952', '24.95', 'from montreal canadiens gift set'], ['2007', 'ottawa senators', 'n / a', '1634', '24.95', 'from ottawa senators gift set'], ['2007', 'toronto maple leafs', 'n / a', '3527', '24.95', 'from toronto maple leafs gift set'], ['2007', 'vancouver canucks', 'n / a', '1264', '24.95', 'from vancouver canucks gift set']]

1984 masters tournament

https://en.wikipedia.org/wiki/1984_Masters_Tournament

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16488662-1.html.csv

ordinal

tom watson had the second most payout in prize money in the 1984 masters tournament .

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

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

eq { hop { nth_argmax { all_rows ; money ; 2 } ; player } ; tom watson } = true

select the row whose money record of all rows is 2nd maximum . the player record of this row is tom watson .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'money_5': 5, '2_6': 6, 'player_7': 7, 'tom watson_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', 'money_5': 'money', '2_6': '2', 'player_7': 'player', 'tom watson_8': 'tom watson'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'money_5': [0], '2_6': [0], 'player_7': [1], 'tom watson_8': [2]}

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

[['1', 'ben crenshaw', 'united states', '67 + 72 + 70 + 68 = 277', '- 11', '108000'], ['2', 'tom watson', 'united states', '74 + 67 + 69 + 69 = 279', '- 9', '64800'], ['t3', 'david edwards', 'united states', '71 + 70 + 72 + 67 = 280', '- 8', '34800'], ['t3', 'gil morgan', 'united states', '73 + 71 + 69 + 67 = 280', '- 8', '34800'], ['5', 'larry nelson', 'united states', '76 + 69 + 66 + 70 = 281', '- 7', '24000'], ['t6', 'ronnie black', 'united states', '71 + 74 + 69 + 68 = 282', '- 6', '19425'], ['t6', 'david graham', 'australia', '69 + 70 + 70 + 73 = 282', '- 6', '19425'], ['t6', 'tom kite', 'united states', '70 + 68 + 69 + 75 = 282', '- 6', '19425'], ['t6', 'mark lye', 'united states', '69 + 66 + 73 + 74 = 282', '- 6', '19425'], ['10', 'fred couples', 'united states', '71 + 73 + 67 + 72 = 283', '- 5', '16200']]

list of england national rugby union team results 1980 - 89

https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1980%E2%80%9389

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178608-9.html.csv

aggregation

a total of 121 points were scored against the england national rugby union team from 1980 - 89 .

{'scope': 'all', 'col': '2', 'type': 'sum', 'result': '121', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'against'], 'result': '121', 'ind': 0, 'tostr': 'sum { all_rows ; against }'}, '121'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; against } ; 121 } = true', 'tointer': 'the sum of the against record of all rows is 121 .'}

round_eq { sum { all_rows ; against } ; 121 } = true

the sum of the against record of all rows is 121 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'against_4': 4, '121_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'against_4': 'against', '121_5': '121'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'against_4': [0], '121_5': [1]}

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

[['france', '10', '16 / 01 / 1988', 'parc des princes , paris', 'five nations'], ['wales', '11', '06 / 02 / 1988', 'twickenham , london', 'five nations'], ['scotland', '6', '05 / 03 / 1988', 'murrayfield , edinburgh', 'five nations'], ['ireland', '3', '19 / 03 / 1988', 'twickenham , london', 'five nations'], ['ireland', '10', '23 / 04 / 1988', 'lansdowne road , dublin', 'millennium trophy match'], ['australia', '22', '29 / 05 / 1988', 'ballymore , brisbane', 'first test'], ['australia', '28', '12 / 06 / 1988', 'concord oval , sydney', 'second test'], ['fiji', '12', '16 / 06 / 1988', 'national stadium , suva', 'test match'], ['australia', '19', '05 / 11 / 1988', 'twickenham , london', 'test match']]

list of townships in north dakota

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18600760-10.html.csv

superlative

joliette township has the highest square miles of land of all the townships in north dakota .

{'scope': 'all', 'col_superlative': '4', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'land ( sqmi )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; land ( sqmi ) }'}, 'township'], 'result': 'joliette', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; land ( sqmi ) } ; township }'}, 'joliette'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; land ( sqmi ) } ; township } ; joliette } = true', 'tointer': 'select the row whose land ( sqmi ) record of all rows is maximum . the township record of this row is joliette .'}

eq { hop { argmax { all_rows ; land ( sqmi ) } ; township } ; joliette } = true

select the row whose land ( sqmi ) record of all rows is maximum . the township record of this row is joliette .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'land ( sqmi )_5': 5, 'township_6': 6, 'joliette_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'land ( sqmi )_5': 'land ( sqmi )', 'township_6': 'township', 'joliette_7': 'joliette'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'land ( sqmi )_5': [0], 'township_6': [1], 'joliette_7': [2]}

['township', 'county', 'pop ( 2010 )', 'land ( sqmi )', 'water ( sqmi )', 'latitude', 'longitude', 'geo id', 'ansi code']

[['jackson', 'sargent', '33', '35.809', '0.000', '46.066276', '- 97.945530', '3808140460', '1036797'], ['james hill', 'mountrail', '32', '31.820', '4.243', '48.423125', '- 102.429934', '3806140500', '1037048'], ['james river valley', 'dickey', '40', '28.597', '0.000', '46.246641', '- 98.188329', '3802140540', '1036767'], ['janke', 'logan', '28', '35.995', '0.163', '46.415512', '- 99.131701', '3804740620', '1037193'], ['jefferson', 'pierce', '45', '35.069', '1.125', '48.232149', '- 100.182370', '3806940700', '1759556'], ['jim river valley', 'stutsman', '38', '34.134', '1.746', '47.112388', '- 98.778478', '3809340780', '1036484'], ['johnson', 'wells', '36', '35.299', '0.908', '47.377745', '- 99.458677', '3810340820', '1037137'], ['johnstown', 'grand forks', '79', '36.199', '0.000', '48.151362', '- 97.449033', '3803540940', '1036624'], ['joliette', 'pembina', '67', '70.044', '0.771', '48.796545', '- 97.217227', '3806741020', '1036723']]

wind power in the republic of ireland

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14101606-2.html.csv

unique

glenough extension is the only wind farm with a single turbine in the republic of ireland .

{'scope': 'all', 'row': '17', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '1', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'turbines', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose turbines record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; turbines ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; turbines ; 1 } }', 'tointer': 'select the rows whose turbines 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', 'turbines', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose turbines record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; turbines ; 1 }'}, 'wind farm'], 'result': 'glenough extension', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; turbines ; 1 } ; wind farm }'}, 'glenough extension'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; turbines ; 1 } ; wind farm } ; glenough extension }', 'tointer': 'the wind farm record of this unqiue row is glenough extension .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; turbines ; 1 } } ; eq { hop { filter_eq { all_rows ; turbines ; 1 } ; wind farm } ; glenough extension } } = true', 'tointer': 'select the rows whose turbines record is equal to 1 . there is only one such row in the table . the wind farm record of this unqiue row is glenough extension .'}

and { only { filter_eq { all_rows ; turbines ; 1 } } ; eq { hop { filter_eq { all_rows ; turbines ; 1 } ; wind farm } ; glenough extension } } = true

select the rows whose turbines record is equal to 1 . there is only one such row in the table . the wind farm record of this unqiue row is glenough extension .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'turbines_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'wind farm_9': 9, 'glenough extension_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'turbines_7': 'turbines', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'wind farm_9': 'wind farm', 'glenough extension_10': 'glenough extension'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'turbines_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'wind farm_9': [2], 'glenough extension_10': [3]}

['wind farm', 'scheduled', 'capacity ( mw )', 'turbines', 'type', 'location']

[['codling', 'unknown', '1100', '220', 'unknown', 'county wicklow'], ['carrowleagh', '2012', '36.8', '16', 'enercon e - 70 2.3', 'county cork'], ['dublin array', '2015', '364', '145', 'unknown', 'county dublin'], ['glenmore', '2009 summer', '30', '10', 'vestas v90', 'county clare'], ['glenough', '2010 winter', '32.5', '13', 'nordex n80 / n90', 'county tipperary'], ['gortahile', '2010 autumn', '20', '8', 'nordex n90', 'county laois'], ['grouse lodge', '2011 summer', '20', '8', 'nordex n90', 'county tipperary'], ['moneypoint', 'unknown', '22.5', '9', 'unknown', 'county clare'], ['mount callan', 'unknown', '90', '30', '3 mw', 'county clare'], ['oriel', '2013', '330', '55', 'unknown', 'county louth'], ['skerd rocks', 'unknown', '100', '20', '5 mw', 'county galway'], ['shragh', 'planning submitted oct 2011', '135', '45', 'enercon e82 3.0 mw', 'county clare'], ['garracummer', '2012', '42.5', '17', 'nordex n90 2.5 mw', 'county tipperary'], ['knockacummer', '2013', '87.5', '35', 'nordex n90 2.5 mw', 'county cork'], ['monaincha', '2013', '36', '15', 'nordex n117 2.4 mw', 'county tipperary'], ['gibbet hill', '2013', '15', '6', 'nordex n90 2.5 mw', 'county wexford'], ['glenough extension', '2013', '2.5', '1', 'nordex n90 2.5 mw', 'county tipperary']]

1965 american football league draft

https://en.wikipedia.org/wiki/1965_American_Football_League_Draft

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18652198-3.html.csv

count

two of the players were drafted for the position of linebacker .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'linebacker', 'result': '2', 'col': '4', 'subset': None}

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

eq { count { filter_eq { all_rows ; position ; linebacker } } ; 2 } = true

select the rows whose position record fuzzily matches to linebacker . 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, 'position_5': 5, 'linebacker_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', 'position_5': 'position', 'linebacker_6': 'linebacker', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'linebacker_6': [0], '2_7': [2]}

['pick', 'team', 'player', 'position', 'college']

[['17', 'denver broncos', 'glenn ressler', 'offensive guard', 'penn state'], ['18', 'houston oilers', 'ernie koy', 'running back', 'texas'], ['19', 'oakland raiders', 'bob svihus', 'defensive tackle', 'usc'], ['20', 'new york jets', 'verlon biggs', 'defensive end', 'jackson state'], ['21', 'kansas city chiefs', 'mike curtis', 'linebacker', 'duke'], ['22', 'san diego chargers', 'allen brown', 'tight end', 'mississippi'], ['23', 'boston patriots', 'jim whalen', 'tackle', 'boston college'], ['24', 'buffalo bills', 'al atkinson', 'linebacker', 'villanova']]

1999 - 2000 manchester united f.c. season

https://en.wikipedia.org/wiki/1999%E2%80%932000_Manchester_United_F.C._season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12988799-9.html.csv

count

in the 1999-2000 manchester united f. c. season , there were three times where the group position was 1st .

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

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

eq { count { filter_eq { all_rows ; group position ; 1st } } ; 3 } = true

select the rows whose group position record fuzzily matches to 1st . 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, 'group position_5': 5, '1st_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', 'group position_5': 'group position', '1st_6': '1st', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'group position_5': [0], '1st_6': [0], '3_7': [2]}

['date', 'opponents', 'h / a', 'result f - a', 'attendance', 'group position']

[['23 november 1999', 'fiorentina', 'a', '0 - 2', '36002', '3rd'], ['8 december 1999', 'valencia', 'h', '3 - 0', '54606', '2nd'], ['1 march 2000', 'bordeaux', 'h', '2 - 0', '59786', '2nd'], ['7 march 2000', 'bordeaux', 'a', '2 - 1', '30130', '1st'], ['15 march 2000', 'fiorentina', 'h', '3 - 1', '59926', '1st'], ['21 march 2000', 'valencia', 'a', '0 - 0', '40419', '1st']]