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1975 minnesota vikings season | https://en.wikipedia.org/wiki/1975_Minnesota_Vikings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10361480-2.html.csv | majority | the vikings won most of their games during the 1975 nfl season . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; result ; w } = true'} | most_eq { all_rows ; result ; w } = true | for the result records of all rows , most of them fuzzily match to w . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 21 , 1975', 'san francisco 49ers', 'w 27 - 17', '46479'], ['2', 'september 28 , 1975', 'cleveland browns', 'w 42 - 10', '68064'], ['3', 'october 5 , 1975', 'chicago bears', 'w 28 - 3', '47578'], ['4', 'october 12 , 1975', 'new york jets', 'w 29 - 21', '47739'], ['5', 'october 19 , 1975', 'detroit lions', 'w 25 - 19', '47872'], ['6', 'october 27 , 1975', 'chicago bears', 'w 13 - 9', '51259'], ['7', 'november 2 , 1975', 'green bay packers', 'w 28 - 17', '57267'], ['8', 'november 9 , 1975', 'atlanta falcons', 'w 38 - 0', '43751'], ['9', 'november 16 , 1975', 'new orleans saints', 'w 20 - 7', '52765'], ['10', 'november 23 , 1975', 'san diego chargers', 'w 28 - 13', '43737'], ['11', 'november 30 , 1975', 'washington redskins', 'l 30 - 31', '54498'], ['12', 'december 7 , 1975', 'green bay packers', 'w 24 - 3', '46147'], ['13', 'december 14 , 1975', 'detroit lions', 'l 10 - 17', '73130'], ['14', 'december 20 , 1975', 'buffalo bills', 'w 35 - 13', '54993']] |
1998 icc knockout trophy | https://en.wikipedia.org/wiki/1998_ICC_KnockOut_Trophy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11950720-1.html.csv | majority | the majority of players in the 1998 icc knockout trophy had a right hand batting style . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'right hand bat', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'batting style', 'right hand bat'], 'result': True, 'ind': 0, 'tointer': 'for the batting style records of all rows , most of them fuzzily match to right hand bat .', 'tostr': 'most_eq { all_rows ; batting style ; right hand bat } = true'} | most_eq { all_rows ; batting style ; right hand bat } = true | for the batting style records of all rows , most of them fuzzily match to right hand bat . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'batting style_3': 3, 'right hand bat_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'batting style_3': 'batting style', 'right hand bat_4': 'right hand bat'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'batting style_3': [0], 'right hand bat_4': [0]} | ['player', 'date of birth', 'batting style', 'bowling style', 'first class team'] | [['steve waugh ( captain )', '2 june 1965', 'right hand bat', 'right arm medium', 'new south wales'], ['mark waugh ( vice - captain )', '2 june 1965', 'right hand bat', 'right arm medium right arm off break', 'new south wales'], ['michael bevan', '8 may 1970', 'left hand bat', 'left arm slow chinaman', 'new south wales'], ['damien fleming', '24 april 1970', 'right hand bat', 'right arm fast - medium', 'victoria'], ['adam gilchrist ( wicket - keeper )', '14 november 1971', 'left hand bat', 'wicket - keeper', 'western australia'], ['brendon julian', '10 august 1970', 'right hand bat', 'left arm fast - medium', 'western australia'], ['michael kasprowicz', '10 february 1972', 'right hand bat', 'right arm fast - medium', 'queensland'], ['darren lehmann', '5 february 1970', 'left hand bat', 'left arm orthodox spin', 'south australia'], ['damien martyn', '21 october 1971', 'right hand bat', 'right arm medium', 'western australia'], ['glenn mcgrath', '9 february 1970', 'right hand bat', 'right arm fast - medium', 'new south wales'], ['ricky ponting', '19 december 1974', 'right hand bat', 'right arm medium', 'tasmania'], ['gavin robertson', '28 may 1966', 'right hand bat', 'right arm off break', 'new south wales'], ['andrew symonds', '9 june 1975', 'right hand bat', 'right arm medium right arm off break', 'queensland'], ['brad young', '23 february 1973', 'right hand bat', 'left arm orthodox spin', 'south australia']] |
1963 in brazilian football | https://en.wikipedia.org/wiki/1963_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15244400-2.html.csv | superlative | in 1963 , of the brazilian football teams with at least 10 points , the team with the most drawn games was botafogo . | {'scope': 'subset', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,3', 'subset': {'col': '3', 'criterion': 'greater_than_eq', 'value': '10'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'points', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; points ; 10 }', 'tointer': 'select the rows whose points record is greater than or equal to 10 .'}, 'drawn'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_greater_eq { all_rows ; points ; 10 } ; drawn }'}, 'team'], 'result': 'botafogo', 'ind': 2, 'tostr': 'hop { argmax { filter_greater_eq { all_rows ; points ; 10 } ; drawn } ; team }'}, 'botafogo'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_greater_eq { all_rows ; points ; 10 } ; drawn } ; team } ; botafogo } = true', 'tointer': 'select the rows whose points record is greater than or equal to 10 . select the row whose drawn record of these rows is maximum . the team record of this row is botafogo .'} | eq { hop { argmax { filter_greater_eq { all_rows ; points ; 10 } ; drawn } ; team } ; botafogo } = true | select the rows whose points record is greater than or equal to 10 . select the row whose drawn record of these rows is maximum . the team record of this row is botafogo . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'points_6': 6, '10_7': 7, 'drawn_8': 8, 'team_9': 9, 'botafogo_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'points_6': 'points', '10_7': '10', 'drawn_8': 'drawn', 'team_9': 'team', 'botafogo_10': 'botafogo'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'points_6': [0], '10_7': [0], 'drawn_8': [1], 'team_9': [2], 'botafogo_10': [3]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'santos', '13', '9', '1', '2', '15', '15'], ['2', 'corinthians', '12', '9', '0', '3', '9', '8'], ['3', 'fluminense', '11', '9', '3', '2', '12', '1'], ['4', 'botafogo', '10', '9', '4', '2', '14', '2'], ['5', 'palmeiras', '10', '9', '2', '3', '12', '0'], ['6', 'portuguesa', '9', '9', '3', '3', '21', '- 3'], ['7', 'portuguesa', '8', '9', '0', '5', '13', '1'], ['8', 'são paulo', '8', '9', '2', '4', '16', '- 5'], ['9', 'vasco da gama', '7', '9', '5', '3', '12', '- 3'], ['10', 'olaria', '7', '9', '2', '7', '23', '- 14']] |
list of amd athlon x2 microprocessors | https://en.wikipedia.org/wiki/List_of_AMD_Athlon_X2_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13869651-2.html.csv | ordinal | the athlon x2 5050e has a higher frequency compared to the athlon x2 4450e , among the amd athlon x2 microprocessors . | {'row': '5', 'col': '3', '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', 'frequency', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; frequency ; 1 }'}, 'model number'], 'result': 'athlon x2 5050e', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; frequency ; 1 } ; model number }'}, 'athlon x2 5050e'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; frequency ; 1 } ; model number } ; athlon x2 5050e } = true', 'tointer': 'select the row whose frequency record of all rows is 1st maximum . the model number record of this row is athlon x2 5050e .'} | eq { hop { nth_argmax { all_rows ; frequency ; 1 } ; model number } ; athlon x2 5050e } = true | select the row whose frequency record of all rows is 1st maximum . the model number record of this row is athlon x2 5050e . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'frequency_5': 5, '1_6': 6, 'model number_7': 7, 'athlon x2 5050e_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'frequency_5': 'frequency', '1_6': '1', 'model number_7': 'model number', 'athlon x2 5050e_8': 'athlon x2 5050e'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'frequency_5': [0], '1_6': [0], 'model number_7': [1], 'athlon x2 5050e_8': [2]} | ['model number', 'stepping', 'frequency', 'l2 cache', 'multi 1', 'v core', 'socket', 'release date', 'part number ( s )'] | [['athlon x2 3250e', 'g2', '1500 mhz', '2 512 kb', '7.5', '1.15 - 1.25 v', 'socket am2', 'q4 , 2008', 'adj3250iav5do'], ['athlon x2 4050e', 'g2', '2100 mhz', '2 512 kb', '10.5', '1.15 - 1.25 v', 'socket am2', 'april 21 , 2008', 'adh4050iaa5do'], ['athlon x2 4450e', 'g2', '2300 mhz', '2 512 kb', '11.5', '1.15 - 1.25 v', 'socket am2', 'april 21 , 2008', 'adh4450iaa5do'], ['athlon x2 4850e', 'g2', '2500 mhz', '2 512 kb', '12.5', '1.15 - 1.25 v', 'socket am2', 'march 5 , 2008', 'adh4850iaa5do'], ['athlon x2 5050e', 'g2', '2600 mhz', '2 512 kb', '13', '1.15 - 1.25 v', 'socket am2', 'october 21 , 2008', 'adh5050iaa5do']] |
1971 isle of man tt | https://en.wikipedia.org/wiki/1971_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10638654-8.html.csv | majority | the majority of the riders in the 1971 isle of man tt had recorded a speed of at least 80 mph . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '80', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'speed', '80'], 'result': True, 'ind': 0, 'tointer': 'for the speed records of all rows , most of them are greater than or equal to 80 .', 'tostr': 'most_greater_eq { all_rows ; speed ; 80 } = true'} | most_greater_eq { all_rows ; speed ; 80 } = true | for the speed records of all rows , most of them are greater than or equal to 80 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'speed_3': 3, '80_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'speed_3': 'speed', '80_4': '80'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'speed_3': [0], '80_4': [0]} | ['rank', 'rider', 'team', 'speed', 'time'] | [['1', 'georg auerbacher / hhahn', 'bmw', '86.86 mph', '1.18.12.0'], ['2', 'ajsamson / dajose', 'triumph', '82.50 mph', '1.22.20.2'], ['3', 'rwilliamson / jmcpherson', 'weslake', '82.25 mph', '1.23.50.0'], ['4', 'rwoodhouse / dwoodhouse', 'honda', '81.91 mph', '1.22.55.0'], ['5', 'dwood / dcoomber', 'norton', '81.19 mph', '1.23.39.8'], ['6', 'dplummer / mbrett', 'triumph', '80.77 mph', '1.24.05.6'], ['7', 'bcurrie / mscott', 'triumph', '80.60 mph', '1.24.16.2'], ['8', 'mpotter / pjburleigh', 'bsa', '80.18 mph', '1.24.43.4'], ['9', 'dhawes / jpmann', 'seeley', '80.09 mph', '1.24.48.6'], ['10', 'amethersill / mmitchinson', 'ams', '79.52 mph', '1.25.24.8']] |
1983 world judo championships | https://en.wikipedia.org/wiki/1983_World_Judo_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15807776-2.html.csv | ordinal | the soviet union was awarded the second highest total amount of medals in the 1983 world judo championships . | {'row': '2', 'col': '6', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'total', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 2 }'}, 'nation'], 'result': 'soviet union', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 2 } ; nation }'}, 'soviet union'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ; 2 } ; nation } ; soviet union } = true', 'tointer': 'select the row whose total record of all rows is 2nd maximum . the nation record of this row is soviet union .'} | eq { hop { nth_argmax { all_rows ; total ; 2 } ; nation } ; soviet union } = true | select the row whose total record of all rows is 2nd maximum . the nation record of this row is soviet union . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '2_6': 6, 'nation_7': 7, 'soviet union_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', '2_6': '2', 'nation_7': 'nation', 'soviet union_8': 'soviet union'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '2_6': [0], 'nation_7': [1], 'soviet union_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'japan', '4', '1', '2', '7'], ['2', 'soviet union', '2', '1', '2', '5'], ['3', 'east germany', '2', '0', '2', '4'], ['4', 'italy', '0', '1', '1', '2'], ['4', 'hungary', '0', '1', '1', '2'], ['6', 'france', '0', '1', '0', '1'], ['6', 'czech republic', '0', '1', '0', '1'], ['6', 'great britain', '0', '1', '0', '1'], ['6', 'netherlands', '0', '1', '0', '1'], ['10', 'germany', '0', '0', '2', '2'], ['10', 'belgium', '0', '0', '2', '2'], ['10', 'romania', '0', '0', '2', '2'], ['13', 'united states', '0', '0', '1', '1'], ['13', 'poland', '0', '0', '1', '1']] |
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 | ordinal | jj anderson was the second earliest player to join the utah jazz all - time roster . | {'row': '4', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'years for jazz', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; years for jazz ; 2 }'}, 'player'], 'result': 'j j anderson', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; years for jazz ; 2 } ; player }'}, 'j j anderson'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; years for jazz ; 2 } ; player } ; j j anderson } = true', 'tointer': 'select the row whose years for jazz record of all rows is 2nd minimum . the player record of this row is j j anderson .'} | eq { hop { nth_argmin { all_rows ; years for jazz ; 2 } ; player } ; j j anderson } = true | select the row whose years for jazz record of all rows is 2nd minimum . the player record of this row is j j anderson . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'years for jazz_5': 5, '2_6': 6, 'player_7': 7, 'j j anderson_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', 'years for jazz_5': 'years for jazz', '2_6': '2', 'player_7': 'player', 'j j anderson_8': 'j j anderson'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'years for jazz_5': [0], '2_6': [0], 'player_7': [1], 'j j anderson_8': [2]} | ['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']] |
united states house of representatives elections , 1890 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1890 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1431450-2.html.csv | count | california elected two democrats in the 1890 election . | {'scope': 'all', 'criterion': 'equal', 'value': 'democratic', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to democratic .', 'tostr': 'filter_eq { all_rows ; party ; democratic }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; party ; democratic } }', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; party ; democratic } } ; 2 } = true', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; party ; democratic } } ; 2 } = true | select the rows whose party record fuzzily matches to democratic . 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, 'party_5': 5, 'democratic_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', 'party_5': 'party', 'democratic_6': 'democratic', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'democratic_6': [0], '2_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result'] | [['california 1', 'vacant', 'vacant', 'vacant', 'democratic gain'], ['california 2', 'marion biggs', 'democratic', '1886', 'retired democratic hold'], ['california 3', 'joseph mckenna', 'republican', '1884', 're - elected'], ['california 4', 'william w morrow', 'republican', '1884', 'retired republican hold'], ['california 5', 'thomas j clunie', 'democratic', '1888', 'lost re - election republican gain'], ['california 6', 'william vandever', 'republican', '1886', 'retired republican hold']] |
1962 - 63 illinois fighting illini men 's basketball team | https://en.wikipedia.org/wiki/1962%E2%80%9363_Illinois_Fighting_Illini_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22824297-1.html.csv | count | three of the players for the 1962 - 63 illinois fighting illini men 's basketball team have a height of 6-2 . | {'scope': 'all', 'criterion': 'equal', 'value': '6 - 2', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'height', '6 - 2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height record fuzzily matches to 6 - 2 .', 'tostr': 'filter_eq { all_rows ; height ; 6 - 2 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; height ; 6 - 2 } }', 'tointer': 'select the rows whose height record fuzzily matches to 6 - 2 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; height ; 6 - 2 } } ; 3 } = true', 'tointer': 'select the rows whose height record fuzzily matches to 6 - 2 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; height ; 6 - 2 } } ; 3 } = true | select the rows whose height record fuzzily matches to 6 - 2 . 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, 'height_5': 5, '6 - 2_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', 'height_5': 'height', '6 - 2_6': '6 - 2', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'height_5': [0], '6 - 2_6': [0], '3_7': [2]} | ['no', 'player', 'hometown', 'class', 'position', 'height', 'weight'] | [['10', 'larry bauer', 'springfield , illinois', 'so', 'forward', '6 - 7', '207'], ['11', 'bob meadows', 'collinsville , illinois', 'so', 'guard', '5 - 7', '157'], ['12', 'tal brody', 'trenton , new jersey / central high school', 'so', 'guard', '6 - 2', '165'], ['14', 'john love', 'ottawa , illinois', 'jr', 'forward', '6 - 3', '199'], ['22', 'jay lovelace', 'carbondale , illinois', 'sr', 'guard', '6 - 0', '164'], ['25', 'bill burwell', 'brooklyn , new york / boys high school', 'sr', 'center', '6 - 8', '227'], ['30', 'jeff ferguson', 'benton , illinois', 'sr', 'forward', '6 - 3', '195'], ['31', 'tony latham', 'waukegan , illinois', 'so', 'guard', '6 - 10', '163'], ['32', 'bill edwards', 'windsor , illinois', 'jr', 'guard', '6 - 2', '208'], ['33', 'bogie redmon', 'collinsville , illinois', 'so', 'forward', '6 - 5', '218'], ['34', 'bill mckeown', 'clinton , illinois', 'so', 'guard', '6 - 2', '185'], ['35', 'skip thoren', 'rockford , illinois / rockford east high school', 'so', 'center', '6 - 8', '201'], ['40', 'dave downey', 'canton , illinois', 'sr', 'forward', '6 - 4', '204']] |
list of state leaders in 840s bc | https://en.wikipedia.org/wiki/List_of_state_leaders_in_840s_BC | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17337904-7.html.csv | count | there were 4 kings who served as state leaders in the 840s bc . | {'scope': 'all', 'criterion': 'equal', 'value': 'king', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'king'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to king .', 'tostr': 'filter_eq { all_rows ; title ; king }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; title ; king } }', 'tointer': 'select the rows whose title record fuzzily matches to king . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; title ; king } } ; 4 } = true', 'tointer': 'select the rows whose title record fuzzily matches to king . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; title ; king } } ; 4 } = true | select the rows whose title record fuzzily matches to king . 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, 'title_5': 5, 'king_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', 'title_5': 'title', 'king_6': 'king', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'title_5': [0], 'king_6': [0], '4_7': [2]} | ['type', 'name', 'title', 'royal house', 'from'] | [['sovereign', 'jehoshaphat', 'king', 'david', '873 bc or 871 bc or 870 bc'], ['sovereign', 'jehoram', 'king', 'david', '851 bc or 849 bc or 848 bc'], ['sovereign', 'ahaziah', 'king', 'david', '843 bc or 842 bc or 841 bc'], ['sovereign', 'athaliah', 'queen regnant', 'david', '842 bc or 841 bc'], ['sovereign', 'jehoash', 'king', 'david', '842 bc or 841 bc or 837 bc or 835 bc']] |
united states house of representatives elections , 1930 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1930 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342359-2.html.csv | majority | the majority of the candidates ran unopposed in the 1930 house of representative elections . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'unopposed', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': True, 'ind': 0, 'tointer': 'for the candidates records of all rows , most of them fuzzily match to unopposed .', 'tostr': 'most_eq { all_rows ; candidates ; unopposed } = true'} | most_eq { all_rows ; candidates ; unopposed } = true | for the candidates records of all rows , most of them fuzzily match to unopposed . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'candidates_3': 3, 'unopposed_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'candidates_3': 'candidates', 'unopposed_4': 'unopposed'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'candidates_3': [0], 'unopposed_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['alabama 1', 'john mcduffie', 'democratic', '1918', 're - elected', 'john mcduffie ( d ) unopposed'], ['alabama 2', 'j lister hill', 'democratic', '1923', 're - elected', 'j lister hill ( d ) unopposed'], ['alabama 3', 'henry b steagall', 'democratic', '1914', 're - elected', 'henry b steagall ( d ) unopposed'], ['alabama 4', 'lamar jeffers', 'democratic', '1921', 're - elected', 'lamar jeffers ( d ) 68.5 % e d banks ( r ) 31.5 %'], ['alabama 5', 'lafayette l patterson', 'democratic', '1928', 're - elected', 'lafayette l patterson ( d ) unopposed'], ['alabama 6', 'william b oliver', 'democratic', '1914', 're - elected', 'william b oliver ( d ) unopposed']] |
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/2-15187735-21.html.csv | count | there was a total of 13 episodes created . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '13', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'series ep'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose series ep record is arbitrary .', 'tostr': 'filter_all { all_rows ; series ep }'}], 'result': '13', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; series ep } }', 'tointer': 'select the rows whose series ep record is arbitrary . the number of such rows is 13 .'}, '13'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; series ep } } ; 13 } = true', 'tointer': 'select the rows whose series ep record is arbitrary . the number of such rows is 13 .'} | eq { count { filter_all { all_rows ; series ep } } ; 13 } = true | select the rows whose series ep record is arbitrary . the number of such rows is 13 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'series ep_5': 5, '13_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'series ep_5': 'series ep', '13_6': '13'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'series ep_5': [0], '13_6': [2]} | ['series ep', 'episode', 'segment a', 'segment b', 'segment c', 'segment d'] | [['21 - 01', '261', 'rubber gloves', 'soap carvings', 'aircraft cabinets', 'motorcycle brake locks'], ['21 - 02', '262', 'powder horns', 'handcrafted moulds', 'perogies', 'inner tubes'], ['21 - 03', '263', 'lace', 'antique frame replicas', 'orchids', 'unicycle wheel hubs'], ['21 - 04', '264', 'external hard drives', 'frozen shrimp', 'thai rice boxes', 'paper towels'], ['21 - 05', '265', 'tea', 'roof finials', 'artificial flowers', 'alloy wheels'], ['21 - 06', '266', 'gel caps', 'playground spring riders', 'frozen pancakes', 'natural rubber'], ['21 - 07', '267', 'paper umbrellas', 'coal', 'aircraft seats', 's cremation urn'], ['21 - 08', '268', 'aluminium s canoe', 'wooden stave bowls', 'wheelchair accessible vans', 's marimba'], ['21 - 09', '269', 'indy car seats', 'paper flowers', 'standby generators ( part 1 )', 'standby generators ( part 2 )'], ['21 - 10', '270', 'customized knee replacements', 'leaf springs', 'lavender essential oil', 'rivets and rivet tools'], ['21 - 11', '271', 'cast iron stoves', 'ultralight aircraft', 'snow groomers', 'rubber bands'], ['21 - 12', '272', 'barber chairs', 'sewage pumps', 'bimini boat tops', 'diesel filters'], ['21 - 13', '273', 'car tires', 'silk', 'art conservation', 'scuba tanks']] |
united states house of representatives elections , 1828 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1828 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668243-25.html.csv | majority | most of the incumbents of the 1828 united states house of representatives elections were from the jacksonian party . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'jacksonian', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'jacksonian'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to jacksonian .', 'tostr': 'most_eq { all_rows ; party ; jacksonian } = true'} | most_eq { all_rows ; party ; jacksonian } = true | for the party records of all rows , most of them fuzzily match to jacksonian . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'jacksonian_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'jacksonian_4': 'jacksonian'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'jacksonian_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['virginia 2', 'james trezvant', 'jacksonian', '1825', 're - elected', 'james trezvant ( j ) 100 %'], ['virginia 3', 'william s archer', 'jacksonian', '1820 ( special )', 're - elected', 'william s archer ( j ) 100 %'], ['virginia 4', 'mark alexander', 'jacksonian', '1819', 're - elected', 'mark alexander ( j ) 100 %'], ['virginia 6', 'thomas davenport', 'jacksonian', '1825', 're - elected', 'thomas davenport ( j ) 100 %'], ['virginia 7', 'nathaniel h claiborne', 'jacksonian', '1825', 're - elected', 'nathaniel h claiborne ( j ) 100 %'], ['virginia 9', 'andrew stevenson', 'jacksonian', '1821', 're - elected', 'andrew stevenson ( j ) 100 %'], ['virginia 10', 'william c rives', 'jacksonian', '1823', 're - elected', 'william c rives ( j ) 100 %'], ['virginia 11', 'philip p barbour', 'jacksonian', '1815 1827', 're - elected', 'philip p barbour ( j ) 100 %'], ['virginia 12', 'john roane', 'jacksonian', '1809 1827', 're - elected', 'john roane ( j ) 100 %'], ['virginia 13', 'john taliaferro', 'anti - jacksonian', '1824 ( special )', 're - elected', 'john taliaferro ( aj ) 61.8 % willoughby newton 38.2 %'], ['virginia 14', 'charles f mercer', 'anti - jacksonian', '1817', 're - elected', 'charles f mercer ( aj ) 82.0 % john gibson 18.0 %'], ['virginia 15', 'john s barbour', 'jacksonian', '1823', 're - elected', 'john s barbour ( j ) 100 %'], ['virginia 16', 'william armstrong', 'anti - jacksonian', '1825', 're - elected', 'william armstrong ( aj ) 100 %'], ['virginia 17', 'robert allen', 'jacksonian', '1827', 're - elected', 'robert allen ( j ) 61.5 % samuel kerceval 38.5 %'], ['virginia 19', 'william mccoy', 'jacksonian', '1811', 're - elected', 'william mccoy ( j ) 100 %'], ['virginia 20', 'john floyd', 'jacksonian', '1817', 'retired jacksonian hold', 'robert craig ( j ) 55.0 % fleming b miller 45.0 %']] |
1997 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1997_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162179-6.html.csv | majority | at the 1997 u.s. open , most of the players were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'ernie els', 'south africa', '71 + 67 + 69 + 69 = 276', '- 4', '465000'], ['2', 'colin montgomerie', 'scotland', '65 + 76 + 67 + 69 = 277', '- 3', '275000'], ['3', 'tom lehman', 'united states', '67 + 70 + 68 + 73 = 278', '- 2', '172828'], ['4', 'jeff maggert', 'united states', '73 + 66 + 68 + 74 = 281', '+ 1', '120454'], ['t5', 'olin browne', 'united states', '71 + 71 + 69 + 71 = 282', '+ 2', '79875'], ['t5', 'jim furyk', 'united states', '74 + 68 + 69 + 71 = 282', '+ 2', '79875'], ['t5', 'jay haas', 'united states', '73 + 69 + 68 + 72 = 282', '+ 2', '79875'], ['t5', 'tommy tolles', 'united states', '74 + 67 + 69 + 72 = 282', '+ 2', '79875'], ['t5', 'bob tway', 'united states', '71 + 71 + 70 + 70 = 282', '+ 2', '79875'], ['t10', 'scott hoch', 'united states', '71 + 68 + 72 + 72 = 283', '+ 3', '56949'], ['t10', 'scott mccarron', 'united states', '73 + 71 + 69 + 70 = 283', '+ 3', '56949'], ['t10', 'david ogrin', 'united states', '70 + 69 + 71 + 73 = 283', '+ 3', '56949']] |
1976 usac championship car season | https://en.wikipedia.org/wiki/1976_USAC_Championship_Car_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22673872-1.html.csv | ordinal | the first race of the 1976 season took place on march 14th . | {'row': '1', 'col': '1', 'order': '1', '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', 'rnd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; rnd ; 1 }'}, 'date'], 'result': 'march 14', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; rnd ; 1 } ; date }'}, 'march 14'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; rnd ; 1 } ; date } ; march 14 } = true', 'tointer': 'select the row whose rnd record of all rows is 1st minimum . the date record of this row is march 14 .'} | eq { hop { nth_argmin { all_rows ; rnd ; 1 } ; date } ; march 14 } = true | select the row whose rnd record of all rows is 1st minimum . the date record of this row is march 14 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'rnd_5': 5, '1_6': 6, 'date_7': 7, 'march 14_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', 'rnd_5': 'rnd', '1_6': '1', 'date_7': 'date', 'march 14_8': 'march 14'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'rnd_5': [0], '1_6': [0], 'date_7': [1], 'march 14_8': [2]} | ['rnd', 'date', 'race name', 'length', 'track', 'location', 'pole position', 'winning driver'] | [['1', 'march 14', 'jimmy bryan 150', '-', 'phoenix international raceway', 'avondale , arizona', 'al unser', 'bobby unser'], ['2', 'may 2', 'trenton 200', '-', 'trenton international speedway', 'trenton , new jersey', 'a j foyt', 'johnny rutherford'], ['3', 'may 30', 'international 500 mile sweepstakes', '-', 'indianapolis motor speedway', 'speedway , indiana', 'johnny rutherford', 'johnny rutherford'], ['4', 'june 13', 'rex mays classic', '-', 'wisconsin state fair park speedway', 'west allis , wisconsin', 'gordon johncock', 'mike mosley'], ['5', 'june 27', 'schaefer 500', '-', 'pocono international raceway', 'long pond , pennsylvania', 'johnny parsons', 'al unser'], ['6', 'july 18', 'norton twin 200s', '-', 'michigan international speedway', 'brooklyn , michigan', 'a j foyt', 'gordon johncock'], ['7', 'august 1', 'texas 150', '-', 'texas world speedway', 'college station , texas', 'a j foyt', 'a j foyt'], ['8', 'august 15', 'trenton 200', '-', 'trenton international speedway', 'trenton , new jersey', 'a j foyt', 'gordon johncock'], ['9', 'august 22', 'tony bettenhausen 200', '-', 'wisconsin state fair park speedway', 'west allis , wisconsin', 'johnny rutherford', 'al unser'], ['10', 'september 5', 'california 500', '-', 'ontario motor speedway', 'ontario , california', 'a j foyt', 'bobby unser'], ['11', 'september 18', 'michigan 150', '-', 'michigan international speedway', 'brooklyn , michigan', 'a j foyt', 'a j foyt'], ['12', 'october 31', 'benihana world series of auto racing', '-', 'texas world speedway', 'college station , texas', 'a j foyt', 'johnny rutherford']] |
2007 japanese television dramas | https://en.wikipedia.org/wiki/2007_Japanese_television_dramas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18539861-3.html.csv | count | a total of five 2007 japanese television dramas were broadcast by fuji tv . | {'scope': 'all', 'criterion': 'equal', 'value': 'fuji tv', 'result': '5', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tv station', 'fuji tv'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tv station record fuzzily matches to fuji tv .', 'tostr': 'filter_eq { all_rows ; tv station ; fuji tv }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; tv station ; fuji tv } }', 'tointer': 'select the rows whose tv station record fuzzily matches to fuji tv . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; tv station ; fuji tv } } ; 5 } = true', 'tointer': 'select the rows whose tv station record fuzzily matches to fuji tv . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; tv station ; fuji tv } } ; 5 } = true | select the rows whose tv station record fuzzily matches to fuji tv . 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, 'tv station_5': 5, 'fuji tv_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', 'tv station_5': 'tv station', 'fuji tv_6': 'fuji tv', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'tv station_5': [0], 'fuji tv_6': [0], '5_7': [2]} | ['japanese title', 'romaji title', 'tv station', 'episodes', 'average ratings'] | [['スシ王子 ！', 'sushi ouji !', 'tv asahi', '8', '7.5 %'], ['菊次郎とさき 3', 'kikujirou to saki 3', 'tv asahi', '11', '9.3 %'], ['牛に願いを love & farm', 'ushi ni negai wo - love & farm', 'fuji tv', '11', '8.7 %'], ['ライフ', 'life', 'fuji tv', '11', '12.16 %'], ['受験の神様', 'juken no kamisama', 'ntv', '9', '9.5 %'], ['パパとムスメの7日間', 'papa to musume no nanokakan', 'tbs', '7', '13.9 %'], ['肩ごしの恋人', 'katagoshi no koibito', 'tbs', '9', '7.4 %'], ['花ざかりの君たちへ ～ イケメン ♂ パラダイス ～', 'hanazakari no kimitachi e ～ ikemen ♂ paradise ～', 'fuji tv', '12', '17.04 %'], ['ファースト ・ キス', 'first kiss', 'fuji tv', '11', '14.1 %'], ['山おんな壁おんな', 'yama onna kabe onna', 'fuji tv', '12', '12.1 %'], ['ホタルノヒカリ', 'hotaru no hikari', 'ntv', '10', '13.6 %'], ['山田太郎ものがたり', 'yamada taro monogatari', 'tbs', '10', '15.24 %'], ['探偵学園q', 'tantei gakuen q', 'ntv', '11', '11.1 %'], ['地獄の沙汰もヨメ次第', 'jigoku no sada mo yome shidai', 'tbs', '10', '10.3 %'], ['女帝', 'jotei', 'tv asahi', '10', '14.4 %']] |
1968 cleveland browns season | https://en.wikipedia.org/wiki/1968_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10652150-3.html.csv | aggregation | in the 1968 cleveland browns season they had a total of 894532 fans in attendance . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '894532', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'attendance'], 'result': '894532', 'ind': 0, 'tostr': 'sum { all_rows ; attendance }'}, '894532'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; attendance } ; 894532 } = true', 'tointer': 'the sum of the attendance record of all rows is 894532 .'} | round_eq { sum { all_rows ; attendance } ; 894532 } = true | the sum of the attendance record of all rows is 894532 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '894532_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '894532_5': '894532'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '894532_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 15 , 1968', 'new orleans saints', 'w 24 - 10', '74215'], ['2', 'september 22 , 1968', 'dallas cowboys', 'l 28 - 7', '68733'], ['3', 'september 29 , 1968', 'los angeles rams', 'l 24 - 6', '82514'], ['4', 'october 5 , 1968', 'pittsburgh steelers', 'w 31 - 24', '81865'], ['5', 'october 13 , 1968', 'st louis cardinals', 'l 27 - 21', '79349'], ['6', 'october 20 , 1968', 'baltimore colts', 'w 30 - 20', '60238'], ['7', 'october 27 , 1968', 'atlanta falcons', 'w 30 - 7', '67723'], ['8', 'november 3 , 1968', 'san francisco 49ers', 'w 33 - 21', '31359'], ['9', 'november 10 , 1968', 'new orleans saints', 'w 35 - 17', '71025'], ['10', 'november 17 , 1968', 'pittsburgh steelers', 'w 45 - 24', '41572'], ['11', 'november 24 , 1968', 'philadelphia eagles', 'w 47 - 13', '62338'], ['12', 'december 1 , 1968', 'new york giants', 'w 45 - 10', '83193'], ['13', 'december 8 , 1968', 'washington redskins', 'w 24 - 21', '50661'], ['14', 'december 14 , 1968', 'st louis cardinals', 'l 27 - 16', '39746']] |
list of apollo astronauts | https://en.wikipedia.org/wiki/List_of_Apollo_astronauts | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-129540-2.html.csv | count | in the list of apollo astronauts given jim lovell is shown as taking part in two missions . | {'scope': 'all', 'criterion': 'equal', 'value': 'jim lovell', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'jim lovell'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to jim lovell .', 'tostr': 'filter_eq { all_rows ; name ; jim lovell }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; name ; jim lovell } }', 'tointer': 'select the rows whose name record fuzzily matches to jim lovell . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; name ; jim lovell } } ; 2 } = true', 'tointer': 'select the rows whose name record fuzzily matches to jim lovell . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; name ; jim lovell } } ; 2 } = true | select the rows whose name record fuzzily matches to jim lovell . 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, 'name_5': 5, 'jim lovell_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', 'name_5': 'name', 'jim lovell_6': 'jim lovell', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'name_5': [0], 'jim lovell_6': [0], '2_7': [2]} | ['name', 'born', 'age on mission', 'mission', 'mission dates', 'service'] | [['frank borman', 'march 14 , 1928 ( age85 )', '40', 'apollo 8', 'december 21 - 27 , 1968', 'air force'], ['jim lovell', 'march 25 , 1928 ( age85 )', '40', 'apollo 8', 'december 21 - 27 , 1968', 'navy'], ['bill anders', 'october 17 , 1933 ( age80 )', '35', 'apollo 8', 'december 21 - 27 , 1968', 'air force'], ['tom stafford', 'september 17 , 1930 ( age83 )', '38', 'apollo 10', 'may 18 - 26 , 1969', 'air force'], ['john young', 'september 24 , 1930 ( age83 )', '38', 'apollo 10', 'may 18 - 26 , 1969', 'navy'], ['eugene cernan', 'march 14 , 1934 ( age79 )', '35', 'apollo 10', 'may 18 - 26 , 1969', 'navy'], ['mike collins', 'october 31 , 1930 ( age83 )', '38', 'apollo 11', 'july 16 - 24 , 1969', 'air force'], ['dick gordon', 'october 5 , 1929 ( age84 )', '40', 'apollo 12', 'november 14 - 24 , 1969', 'navy'], ['jim lovell', 'march 25 , 1928 ( age85 )', '42', 'apollo 13', 'april 11 - 17 , 1970', 'navy'], ['jack swigert', 'august 30 , 1931', '38', 'apollo 13', 'april 11 - 17 , 1970', 'nasa'], ['fred haise', 'november 14 , 1933 ( age80 )', '36', 'apollo 13', 'april 11 - 17 , 1970', 'nasa'], ['stu roosa', 'august 16 , 1933', '37', 'apollo 14', 'january 31 - february 9 , 1971', 'air force'], ['al worden', 'february 7 , 1932 ( age81 )', '39', 'apollo 15', 'july 26 - august 7 , 1971', 'air force'], ['ken mattingly', 'march 17 , 1936 ( age77 )', '36', 'apollo 16', 'april 16 - 27 , 1972', 'navy'], ['ron evans', 'november 10 , 1933', '39', 'apollo 17', 'december 7 - 19 , 1972', 'navy']] |
television in italy | https://en.wikipedia.org/wiki/Television_in_Italy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15887683-19.html.csv | majority | for television in italy , when the content is general television , the language is always italian . | {'scope': 'subset', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'italian', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'general television'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'content', 'general television'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; content ; general television }', 'tointer': 'select the rows whose content record fuzzily matches to general television .'}, 'language', 'italian'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose content record fuzzily matches to general television . for the language records of these rows , all of them fuzzily match to italian .', 'tostr': 'all_eq { filter_eq { all_rows ; content ; general television } ; language ; italian } = true'} | all_eq { filter_eq { all_rows ; content ; general television } ; language ; italian } = true | select the rows whose content record fuzzily matches to general television . for the language records of these rows , all of them fuzzily match to italian . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'content_4': 4, 'general television_5': 5, 'language_6': 6, 'italian_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'content_4': 'content', 'general television_5': 'general television', 'language_6': 'language', 'italian_7': 'italian'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'content_4': [0], 'general television_5': [0], 'language_6': [1], 'italian_7': [1]} | ['n degree', 'television service', 'country', 'language', 'content', 'dar', 'hdtv', 'ppv', 'package / option'] | [['981', 'contotv 1', 'italy', 'italian', 'general television', '4:3', 'no', 'yes', 'qualsiasi'], ['982', 'contotv 2', 'italy', 'italian', 'general television', '4:3', 'no', 'yes', 'qualsiasi'], ['983', 'contotv 3', 'italy', 'italian', 'general television', '16:9', 'no', 'no', 'qualsiasi'], ['984', 'contotv 4', 'italy', 'italian', 'programmi per adulti 24h / 24', '4:3', 'no', 'no', 'qualsiasi'], ['985', 'contotv 5', 'italy', 'italian', 'programmi per adulti 24h / 24', '4:3', 'no', 'no', 'qualsiasi'], ['987', 'teleitalia', 'italy', 'italian', 'general television', '4:3', 'no', 'yes', 'qualsiasi ( fta )'], ['988', 'teleitalia spot', 'italy', 'italian', 'general television', '4:3', 'no', 'yes', 'qualsiasi ( fta )'], ['989', 'd - xtv', 'italy', 'italian', 'programmi per adulti 24h / 24', '4:3', 'no', 'yes', 'qualsiasi'], ['990', 'r - light', 'italy', 'italian', 'programmi per adulti 24h / 24', '4:3', 'no', 'yes', 'qualsiasi'], ['991', 'sct', 'italy', 'italian', 'programmi per adulti 24h / 24', '4:3', 'no', 'yes', 'qualsiasi'], ['992', 'boy & boy', 'italy', 'italian', 'programmi per adulti 24h / 24', '4:3', 'no', 'yes', 'qualsiasi'], ['993', 'privè', 'italy', 'italian', 'programmi per adulti 24h / 24', '4:3', 'no', 'yes', 'qualsiasi'], ['994', 'themex', 'italy', 'italian', 'programmi per adulti 24h / 24', '4:3', 'no', 'yes', 'qualsiasi']] |
independent school league ( boston area ) | https://en.wikipedia.org/wiki/Independent_School_League_%28Boston_Area%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2439728-1.html.csv | majority | the majority of the schools of the independent school league ( boston area ) were founded before the year 1900 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1900', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'founded', '1900'], 'result': True, 'ind': 0, 'tointer': 'for the founded records of all rows , most of them are less than 1900 .', 'tostr': 'most_less { all_rows ; founded ; 1900 } = true'} | most_less { all_rows ; founded ; 1900 } = true | for the founded records of all rows , most of them are less than 1900 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'founded_3': 3, '1900_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'founded_3': 'founded', '1900_4': '1900'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'founded_3': [0], '1900_4': [0]} | ['school', 'mascot', 'location', 'founded', 'entered isl', 'grades', 'number of students', 'varsity teams'] | [['belmont hill school', 'no mascot ( sextant is school symbol )', 'belmont , ma', '1923', '1948', '7 - 12', '420 boys', '16'], ['brooks school', 'bishops', 'north andover , ma', '1926', '1948', '9 - 12', '368', '22'], ['buckingham browne & nichols', 'knights', 'cambridge , ma', '1883', '1948', 'pre - k - 12', '997', '16'], ["governor 's academy", 'red dogs', 'byfield , ma', '1763', '1948', '9 - 12', '376', '20'], ['groton school', 'zebras', 'groton , ma', '1884', '1972', '8 - 12', '352', '19'], ['lawrence academy at groton', 'spartans', 'groton , ma', '1793', '1973', '9 - 12', '375', '22'], ['middlesex school', 'zebras', 'concord , ma', '1901', '1968', '9 - 12', '350', '24'], ['milton academy', 'mustangs', 'milton , ma', '1798', '1948', 'k - 12', '680', '25'], ['noble and greenough school', 'bulldogs', 'dedham , ma', '1866', '1948', '7 - 12', '525', '25'], ['rivers school', 'red wings', 'weston , ma', '1915', '1973', '6 - 12', '450', '16'], ['roxbury latin school', 'foxes', 'west roxbury , ma', '1645', '1974', '7 - 12', '290 boys', '10'], ["st george 's school", 'dragons', 'middletown , ri', '1896', '1981', '9 - 12', '345', '24'], ["st mark 's school", 'lions', 'southborough , ma', '1865', '1948', '9 - 12', '325', '22'], ["st paul 's school", 'pelicans ( teams are cheered for as big red )', 'concord , nh', '1856', '1973', '9 - 12', '533', '17'], ["st sebastian 's school", 'arrows', 'needham , ma', '1941', '1973', '7 - 12', '350 boys', '14']] |
partnership ( cricket ) | https://en.wikipedia.org/wiki/Partnership_%28cricket%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1670921-1.html.csv | count | two of these cricket matches were held at columbo . | {'scope': 'all', 'criterion': 'equal', 'value': 'colombo', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'colombo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to colombo .', 'tostr': 'filter_eq { all_rows ; venue ; colombo }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; colombo } }', 'tointer': 'select the rows whose venue record fuzzily matches to colombo . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; colombo } } ; 2 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to colombo . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; venue ; colombo } } ; 2 } = true | select the rows whose venue record fuzzily matches to colombo . 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, 'venue_5': 5, 'colombo_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', 'venue_5': 'venue', 'colombo_6': 'colombo', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'colombo_6': [0], '2_7': [2]} | ['wicket', 'runs', 'battling partners', 'battling team', 'fielding team', 'venue', 'season'] | [['1st', '415', 'gc smith and neil mckenzie', 'south africa', 'bangladesh', 'chittagong', '2008'], ['2nd', '576', 'roshan mahanama and sanath jayasuriya', 'sri lanka', 'india', 'colombo', '1997'], ['3rd', '624', 'mahela jayawardene and kumar sangakkara', 'sri lanka', 'south africa', 'colombo', '2006'], ['4th', '437', 'mahela jayawardene and thilan samaraweera', 'sri lanka', 'pakistan', 'karachi', '2008 / 09'], ['5th', '405', 'donald bradman and sid barnes', 'australia', 'england', 'sydney', '1946 / 47'], ['6th', '351', 'mahela jayawardene and prasanna jayawardene', 'sri lanka', 'india', 'ahmedabad', '2009 / 10'], ['7th', '347', 'clairmonte depeiaza and denis atkinson', 'west indies', 'australia', 'bridgetown', '1954 / 55'], ['8th', '332', 'jonathan trott and stuart broad', 'england', 'pakistan', "lord 's", '2010'], ['9th', '195', 'pat symcox and mark boucher', 'south africa', 'pakistan', 'johannesburg', '1997 / 98']] |
1946 vfl season | https://en.wikipedia.org/wiki/1946_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809368-15.html.csv | aggregation | for the 1946 vfl season the total combined crowd was 105500 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '105500', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '105500', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '105500'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 105500 } = true', 'tointer': 'the sum of the crowd record of all rows is 105500 .'} | round_eq { sum { all_rows ; crowd } ; 105500 } = true | the sum of the crowd record of all rows is 105500 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '105500_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '105500_5': '105500'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '105500_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '21.18 ( 144 )', 'hawthorn', '12.7 ( 79 )', 'windy hill', '12000', '3 august 1946'], ['collingwood', '15.24 ( 114 )', 'st kilda', '10.9 ( 69 )', 'victoria park', '12000', '3 august 1946'], ['south melbourne', '15.16 ( 106 )', 'melbourne', '14.11 ( 95 )', 'junction oval', '22000', '3 august 1946'], ['north melbourne', '15.10 ( 100 )', 'geelong', '6.12 ( 48 )', 'arden street oval', '7500', '3 august 1946'], ['richmond', '12.21 ( 93 )', 'footscray', '14.15 ( 99 )', 'punt road oval', '31000', '3 august 1946'], ['fitzroy', '14.10 ( 94 )', 'carlton', '11.8 ( 74 )', 'brunswick street oval', '21000', '3 august 1946']] |
united states house of representatives elections , 1972 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1972 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341707-12.html.csv | comparative | jack thomas brinkley was first elected to the united states house of representatives earlier than dawson mathis . | {'row_1': '3', 'row_2': '2', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'jack thomas brinkley'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to jack thomas brinkley .', 'tostr': 'filter_eq { all_rows ; incumbent ; jack thomas brinkley }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; jack thomas brinkley } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to jack thomas brinkley . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'dawson mathis'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to dawson mathis .', 'tostr': 'filter_eq { all_rows ; incumbent ; dawson mathis }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; dawson mathis } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to dawson mathis . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; jack thomas brinkley } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; dawson mathis } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to jack thomas brinkley . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to dawson mathis . take the first elected record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; incumbent ; jack thomas brinkley } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; dawson mathis } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to jack thomas brinkley . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to dawson mathis . take the first elected record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'jack thomas brinkley_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'dawson mathis_12': 12, 'first elected_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'jack thomas brinkley_8': 'jack thomas brinkley', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'dawson mathis_12': 'dawson mathis', 'first elected_13': 'first elected'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'jack thomas brinkley_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'dawson mathis_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['georgia 1', 'george elliott hagan', 'democratic', '1960', 'lost renomination democratic hold', "ronald ' bo ' ginn ( d ) unopposed"], ['georgia 2', 'dawson mathis', 'democratic', '1970', 're - elected', 'dawson mathis ( d ) unopposed'], ['georgia 3', 'jack thomas brinkley', 'democratic', '1966', 're - elected', 'jack thomas brinkley ( d ) unopposed'], ['georgia 5', 'fletcher thompson', 'republican', '1966', 'retired to run for us senate democratic gain', 'andrew young ( d ) 52.8 % rodney m cook ( r ) 47.2 %'], ['georgia 6', 'john james flynt , jr', 'democratic', '1954', 're - elected', 'john james flynt , jr ( d ) unopposed'], ['georgia 7', 'john w davis', 'democratic', '1960', 're - elected', 'john w davis ( d ) 58.3 % charlie sherrill ( r ) 41.7 %'], ['georgia 9', 'phillip m landrum', 'democratic', '1952', 're - elected', 'phillip m landrum ( d ) unopposed']] |
equestrian at the 1980 summer olympics | https://en.wikipedia.org/wiki/Equestrian_at_the_1980_Summer_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1461487-1.html.csv | majority | most of the countries in the 1980 equestrian event in the olympics won at least one gold medal . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '1', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'gold', '1'], 'result': True, 'ind': 0, 'tointer': 'for the gold records of all rows , most of them are greater than or equal to 1 .', 'tostr': 'most_greater_eq { all_rows ; gold ; 1 } = true'} | most_greater_eq { all_rows ; gold ; 1 } = true | for the gold records of all rows , most of them are greater than or equal to 1 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'gold_3': 3, '1_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'gold_3': 'gold', '1_4': '1'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'gold_3': [0], '1_4': [0]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'soviet union ( urs )', '3', '3', '2', '8'], ['2', 'italy ( ita )', '1', '1', '0', '2'], ['2', 'poland ( pol )', '1', '1', '0', '2'], ['4', 'austria ( aut )', '1', '0', '0', '1'], ['5', 'bulgaria ( bul )', '0', '1', '0', '1'], ['6', 'mexico ( mex )', '0', '0', '3', '3'], ['7', 'romania ( rou )', '0', '0', '1', '1']] |
mikael pernfors | https://en.wikipedia.org/wiki/Mikael_Pernfors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1828774-4.html.csv | unique | for championships mikael pernfors played in , when the surface was hard , the only time the opponent in the final was todd martin was in 1993 . | {'scope': 'subset', 'row': '5', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'todd martin', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'hard'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; hard }', 'tointer': 'select the rows whose surface record fuzzily matches to hard .'}, 'opponent in the final', 'todd martin'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose surface record fuzzily matches to hard . among these rows , select the rows whose opponent in the final record fuzzily matches to todd martin .', 'tostr': 'filter_eq { filter_eq { all_rows ; surface ; hard } ; opponent in the final ; todd martin }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; surface ; hard } ; opponent in the final ; todd martin } }', 'tointer': 'select the rows whose surface record fuzzily matches to hard . among these rows , select the rows whose opponent in the final record fuzzily matches to todd martin . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; hard }', 'tointer': 'select the rows whose surface record fuzzily matches to hard .'}, 'opponent in the final', 'todd martin'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose surface record fuzzily matches to hard . among these rows , select the rows whose opponent in the final record fuzzily matches to todd martin .', 'tostr': 'filter_eq { filter_eq { all_rows ; surface ; hard } ; opponent in the final ; todd martin }'}, 'date'], 'result': '28 february 1993', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; surface ; hard } ; opponent in the final ; todd martin } ; date }'}, '28 february 1993'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; surface ; hard } ; opponent in the final ; todd martin } ; date } ; 28 february 1993 }', 'tointer': 'the date record of this unqiue row is 28 february 1993 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; surface ; hard } ; opponent in the final ; todd martin } } ; eq { hop { filter_eq { filter_eq { all_rows ; surface ; hard } ; opponent in the final ; todd martin } ; date } ; 28 february 1993 } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to hard . among these rows , select the rows whose opponent in the final record fuzzily matches to todd martin . there is only one such row in the table . the date record of this unqiue row is 28 february 1993 .'} | and { only { filter_eq { filter_eq { all_rows ; surface ; hard } ; opponent in the final ; todd martin } } ; eq { hop { filter_eq { filter_eq { all_rows ; surface ; hard } ; opponent in the final ; todd martin } ; date } ; 28 february 1993 } } = true | select the rows whose surface record fuzzily matches to hard . among these rows , select the rows whose opponent in the final record fuzzily matches to todd martin . there is only one such row in the table . the date record of this unqiue row is 28 february 1993 . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'surface_8': 8, 'hard_9': 9, 'opponent in the final_10': 10, 'todd martin_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'date_12': 12, '28 february 1993_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'surface_8': 'surface', 'hard_9': 'hard', 'opponent in the final_10': 'opponent in the final', 'todd martin_11': 'todd martin', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'date_12': 'date', '28 february 1993_13': '28 february 1993'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'surface_8': [0], 'hard_9': [0], 'opponent in the final_10': [1], 'todd martin_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'date_12': [3], '28 february 1993_13': [4]} | ['outcome', 'date', 'championship', 'surface', 'opponent in the final', 'score in the final'] | [['runner - up', '26 may 1986', 'french open , paris , france', 'clay', 'ivan lendl', '3 - 6 , 2 - 6 , 4 - 6'], ['runner - up', '15 february 1988', 'memphis , usa', 'hard ( i )', 'andre agassi', '4 - 6 , 4 - 6 , 5 - 7'], ['winner', '19 september 1988', 'los angeles , usa', 'hard', 'andre agassi', '6 - 2 , 7 - 5'], ['winner', '3 october 1988', 'scottsdale , usa', 'hard', 'glenn layendecker', '6 - 2 , 6 - 4'], ['winner', '28 february 1993', 'montreal , canada', 'hard', 'todd martin', '2 - 6 , 6 - 2 , 7 - 5']] |
1974 - 75 philadelphia flyers season | https://en.wikipedia.org/wiki/1974%E2%80%9375_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13908184-11.html.csv | majority | during the 74-75 flyers season , a majority of games saw attendance over 15,800 . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '15800', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'attendance', '15800'], 'result': True, 'ind': 0, 'tointer': 'for the attendance records of all rows , most of them are greater than 15800 .', 'tostr': 'most_greater { all_rows ; attendance ; 15800 } = true'} | most_greater { all_rows ; attendance ; 15800 } = true | for the attendance records of all rows , most of them are greater than 15800 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'attendance_3': 3, '15800_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'attendance_3': 'attendance', '15800_4': '15800'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'attendance_3': [0], '15800_4': [0]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'series'] | [['may 15', 'buffalo', '1 - 4', 'philadelphia', 'parent', '17077', 'flyers lead 1 - 0'], ['may 18', 'buffalo', '1 - 2', 'philadelphia', 'parent', '17077', 'flyers lead 2 - 0'], ['may 20', 'philadelphia', '4 - 5', 'buffalo', 'parent', '15863', 'flyers lead 2 - 1'], ['may 22', 'philadelphia', '2 - 4', 'buffalo', 'parent', '15863', 'series tied 2 - 2'], ['may 25', 'buffalo', '1 - 5', 'philadelphia', 'parent', '17077', 'flyers lead 3 - 2'], ['may 27', 'philadelphia', '2 - 0', 'buffalo', 'parent', '15863', 'flyers win 4 - 2']] |
2007 abc supply company a.j. foyt 225 | https://en.wikipedia.org/wiki/2007_ABC_Supply_Company_A.J._Foyt_225 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17330069-1.html.csv | majority | the majority of divers in the 2007 abc supply company a.j. foyt 225 completed more than 223 laps . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '223', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'laps', '223'], 'result': True, 'ind': 0, 'tointer': 'for the laps records of all rows , most of them are greater than 223 .', 'tostr': 'most_greater { all_rows ; laps ; 223 } = true'} | most_greater { all_rows ; laps ; 223 } = true | for the laps records of all rows , most of them are greater than 223 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laps_3': 3, '223_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laps_3': 'laps', '223_4': '223'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'laps_3': [0], '223_4': [0]} | ['fin pos', 'car no', 'driver', 'team', 'laps', 'time / retired', 'grid', 'laps led', 'points'] | [['1', '11', 'tony kanaan', 'andretti green', '225', '1:47:42.4393', '3', '25', '50'], ['2', '27', 'dario franchitti', 'andretti green', '225', '+ 2.5707', '10', '0', '40'], ['3', '10', 'dan wheldon', 'target chip ganassi', '225', '+ 3.1149', '4', '37', '35'], ['4', '9', 'scott dixon', 'target chip ganassi', '225', '+ 3.4026', '2', '0', '32'], ['5', '4', 'vitor meira', 'panther racing', '225', '+ 5.2684', '9', '0', '30'], ['6', '8', 'scott sharp', 'rahal letterman', '225', '+ 6.8359', '11', '0', '28'], ['7', '20', 'ed carpenter', 'vision racing', '225', '+ 7.0360', '8', '0', '26'], ['8', '7', 'danica patrick', 'andretti green', '225', '+ 8.0205', '17', '0', '24'], ['9', '6', 'sam hornish , jr', 'team penske', '224', '+ 1 lap', '5', '0', '22'], ['10', '17', 'jeff simmons', 'rahal letterman', '224', '+ 1 lap', '18', '0', '20'], ['11', '14', 'darren manning', 'aj foyt racing', '224', '+ 1 lap', '15', '0', '19'], ['12', '55', 'kosuke matsuura', 'panther racing', '223', '+ 2 laps', '6', '0', '18'], ['13', '22', 'a j foyt iv', 'vision racing', '222', '+ 3 laps', '12', '0', '17'], ['14', '5', 'sarah fisher', 'dreyer & reinbold racing', '221', '+ 4 laps', '16', '0', '16'], ['15', '26', 'marco andretti', 'andretti green', '209', 'accident', '19', '0', '15'], ['16', '3', 'hãlio castroneves', 'team penske', '201', 'rear wing', '1', '126', '14 + 3'], ['17', '2', 'tomas scheckter', 'vision racing', '159', 'mechanical', '13', '0', '13'], ['18', '15', 'buddy rice', 'dreyer & reinbold racing', '156', 'accident', '7', '37', '12']] |
1973 denver broncos season | https://en.wikipedia.org/wiki/1973_Denver_Broncos_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17861179-1.html.csv | aggregation | in 1973 season of denver broncos , their games attracted an average crown of around 46,203 people . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '46,203', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '46,203', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '46,203'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 46,203 } = true', 'tointer': 'the average of the attendance record of all rows is 46,203 .'} | round_eq { avg { all_rows ; attendance } ; 46,203 } = true | the average of the attendance record of all rows is 46,203 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '46,203_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '46,203_5': '46,203'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '46,203_5': [1]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 16', 'cincinnati bengals', 'w 28 - 10', 'mile high stadium', '1 - 0', '49059'], ['2', 'september 23', 'san francisco 49ers', 'l 34 - 36', 'mile high stadium', '1 - 1', '50966'], ['3', 'september 30', 'chicago bears', 'l 14 - 33', 'mile high stadium', '1 - 2', '51159'], ['4', 'october 7', 'kansas city chiefs', 'l 14 - 16', 'arrowhead stadium', '1 - 3', '71414'], ['5', 'october 14', 'houston oilers', 'w 48 - 20', 'astrodome', '2 - 3', '32801'], ['6', 'october 22', 'oakland raiders', 't 23 - 23', 'mile high stadium', '2 - 3 - 1', '51270'], ['7', 'october 28', 'new york jets', 'w 40 - 28', 'shea stadium', '3 - 3 - 1', '55108'], ['8', 'november 4', 'st louis cardinals', 't 17 - 17', 'busch memorial stadium', '3 - 3 - 2', '46565'], ['9', 'november 11', 'san diego chargers', 'w 30 - 19', 'mile high stadium', '4 - 3 - 2', '51034'], ['10', 'november 18', 'pittsburgh steelers', 'w 23 - 13', 'three rivers stadium', '5 - 3 - 2', '48580'], ['11', 'november 25', 'kansas city chiefs', 'w 14 - 10', 'mile high stadium', '6 - 3 - 2', '51331'], ['12', 'december 2', 'dallas cowboys', 'l 10 - 22', 'mile high stadium', '6 - 4 - 2', '51508'], ['13', 'december 9', 'san diego chargers', 'w 42 - 28', 'san diego stadium', '7 - 4 - 2', '44954']] |
maryland public television | https://en.wikipedia.org/wiki/Maryland_Public_Television | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1381064-1.html.csv | superlative | wwpb is the maryland public television channel that has the highest haat . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'haat'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; haat }'}, 'station'], 'result': 'wwpb', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; haat } ; station }'}, 'wwpb'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; haat } ; station } ; wwpb } = true', 'tointer': 'select the row whose haat record of all rows is maximum . the station record of this row is wwpb .'} | eq { hop { argmax { all_rows ; haat } ; station } ; wwpb } = true | select the row whose haat record of all rows is maximum . the station record of this row is wwpb . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'haat_5': 5, 'station_6': 6, 'wwpb_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'haat_5': 'haat', 'station_6': 'station', 'wwpb_7': 'wwpb'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'haat_5': [0], 'station_6': [1], 'wwpb_7': [2]} | ['station', 'city of license', 'channels tv / rf', 'first air date', 'haat', 'facility id', 'public license information'] | [['wmpb', 'baltimore', '67 ( psip ) 29 ( uhf )', 'october 5 , 1969', '309 m', '65944', 'profile cdbs'], ['wmpt 1', 'annapolis', '22 ( psip ) 42 ( uhf )', 'september 22 , 1975', '289 m', '65942', 'profile cdbs'], ['wcpb', 'salisbury', '28 ( psip ) 28 ( uhf )', 'march 18 , 1971', '155 m', '40618', 'profile cdbs'], ['wwpb', 'hagerstown', '31 ( psip ) 44 ( uhf )', 'october 5 , 1974', '369 m', '65943', 'profile cdbs'], ['wgpt', 'oakland', '36 ( psip ) 36 ( uhf )', 'july 4 , 1987', '285 m', '40619', 'profile cdbs'], ['wfpt', 'frederick', '62 ( psip ) 28 ( uhf )', 'july 4 , 1987', '158 m', '40626', 'profile cdbs']] |
6 mm caliber | https://en.wikipedia.org/wiki/6_mm_caliber | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1058122-4.html.csv | aggregation | the average length of the different kinds of 6 mm caliber cartilages is about 55mm . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '55', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'length'], 'result': '55', 'ind': 0, 'tostr': 'avg { all_rows ; length }'}, '55'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; length } ; 55 } = true', 'tointer': 'the average of the length record of all rows is 55 .'} | round_eq { avg { all_rows ; length } ; 55 } = true | the average of the length record of all rows is 55 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'length_4': 4, '55_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'length_4': 'length', '55_5': '55'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'length_4': [0], '55_5': [1]} | ['name', 'bullet', 'length', 'base', 'shoulder', 'neck'] | [['6.5 x 50 sr arisaka', '6.705 ( 264 )', '50.39 ( 1.984 )', '11.35 ( 447 )', '10.59 ( 417 )', '7.34 ( 289 )'], ['6.5 x 53.5 r dutch mannlicher', '6.756 ( 266 )', '53.59 ( 2.110 )', '11.48 ( 453 )', '10.75 ( 423 )', '7.55 ( 297 )'], ['6.5 x54 mm mannlicher - schãnauer', '6.705 ( 264 )', '53.65 ( 2.112 )', '11.47 ( 452 )', '10.87 ( 428 )', '7.56 ( 288 )'], ['6.5 x55 mm swedish ( aka 6.5 x55 mm krag )', '6.7 ( 264 )', '54.864 ( 2.16 )', '12.17 ( 479 )', '10.688 ( 420 )', '7.468 ( 294 )'], ['6.5 x58 mm vergueiro', '6.65 ( 262 )', '57.85 ( 2.278 )', '11.88 ( 468 )', '10.94 ( 431 )', '7.56 ( 298 )'], ['6.5 x 68', '6.70 ( 264 )', '75.02 ( 2.956 )', '13.30 ( 524 )', '12.18 ( 480 )', '7.60 ( 299 )'], ['6.5 - 284', '6.70 ( 264 )', '55.118 ( 2.170 )', '12.725 ( 501 )', '12.065 ( 475 )', '7.544 ( 297 )'], ['.260 remington', '6.70 ( 264 )', '51.7 ( 2.035 )', '11.9 ( 470 )', '11.5 ( 454 )', '7.5 ( 297 )'], ['6.5 mm creedmoor', '6.70 ( 264 )', '48.8 ( 1.924 )', '11.9 ( 470 )', '11.7 ( 459 )', '7.54 ( 297 )'], ['6.5 x47 mm lapua', '6.70 ( 264 )', '47 ( 1.9 )', '11.95 ( 470 )', '11.53 ( 454 )', '7.41 ( 292 )'], ['6.5 mm grendel', '6.70 ( 264 )', '38.7 ( 1.524 )', '11.14 ( 439 )', '10.87 ( 428 )', '7.44 ( 293 )'], ['.264 win magnum', '6.70 ( 264 )', '64 ( 2.5 )', '13.1 ( 515 )', '12.5 ( 491 )', '7.6 ( 299 )'], ['6.5 x 52 mm carcano', '6.80 ( 268 )', '52.50 ( 2.067 )', '11.42 ( 450 )', '10.85 ( 427 )', '7.52 ( 296 )']] |
bruno giacomelli | https://en.wikipedia.org/wiki/Bruno_Giacomelli | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1219697-2.html.csv | unique | 1980 was the only year where bruno giacomelli scored a total of 4 points . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '4', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 4 .', 'tostr': 'filter_eq { all_rows ; points ; 4 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; points ; 4 } }', 'tointer': 'select the rows whose points record is equal to 4 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 4 .', 'tostr': 'filter_eq { all_rows ; points ; 4 }'}, 'year'], 'result': '1980', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; points ; 4 } ; year }'}, '1980'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; points ; 4 } ; year } ; 1980 }', 'tointer': 'the year record of this unqiue row is 1980 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; points ; 4 } } ; eq { hop { filter_eq { all_rows ; points ; 4 } ; year } ; 1980 } } = true', 'tointer': 'select the rows whose points record is equal to 4 . there is only one such row in the table . the year record of this unqiue row is 1980 .'} | and { only { filter_eq { all_rows ; points ; 4 } } ; eq { hop { filter_eq { all_rows ; points ; 4 } ; year } ; 1980 } } = true | select the rows whose points record is equal to 4 . there is only one such row in the table . the year record of this unqiue row is 1980 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'points_7': 7, '4_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1980_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'points_7': 'points', '4_8': '4', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1980_10': '1980'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'points_7': [0], '4_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1980_10': [3]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1977', 'marlboro team mclaren', 'mclaren m23', 'ford v8', '0'], ['1978', 'marlboro team mclaren', 'mclaren m26', 'ford v8', '0'], ['1979', 'autodelta', 'alfa romeo 177', 'alfa romeo f12', '0'], ['1979', 'autodelta', 'alfa romeo 179', 'alfa romeo v12', '0'], ['1980', 'marlboro team alfa romeo', 'alfa romeo 179', 'alfa romeo v12', '4'], ['1981', 'marlboro team alfa romeo', 'alfa romeo 179c', 'alfa romeo v12', '7'], ['1981', 'marlboro team alfa romeo', 'alfa romeo 179b', 'alfa romeo v12', '7'], ['1982', 'marlboro team alfa romeo', 'alfa romeo 179d', 'alfa romeo v12', '2'], ['1982', 'marlboro team alfa romeo', 'alfa romeo 182', 'alfa romeo v12', '2'], ['1983', 'candy toleman motorsport', 'toleman tg183b', 'hart l4 t', '1'], ['1990', 'life racing engines', 'life f190', 'life w12', '0'], ['1990', 'life racing engines', 'life f190', 'judd v8', '0']] |
2003 u.s. open ( golf ) | https://en.wikipedia.org/wiki/2003_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16292316-1.html.csv | majority | most of the players of the 2003 u.s. open ( golf ) were from the united states . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['ernie els', 'south africa', '1994 , 1997', '280', 'e', 't5'], ['tiger woods', 'united states', '2000 , 2002', '283', '+ 3', 't20'], ['tom watson', 'united states', '1982', '284', '+ 4', 't28'], ['retief goosen', 'south africa', '2001', '286', '+ 6', 't42'], ['lee janzen', 'united states', '1993 , 1998', '289', '+ 9', 't55']] |
bermuda national cricket team | https://en.wikipedia.org/wiki/Bermuda_national_cricket_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1829476-2.html.csv | aggregation | the total amount of runs scored by all of the bermuda national cricket players is 3324 . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '3324', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'runs'], 'result': '3324', 'ind': 0, 'tostr': 'sum { all_rows ; runs }'}, '3324'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; runs } ; 3324 } = true', 'tointer': 'the sum of the runs record of all rows is 3324 .'} | round_eq { sum { all_rows ; runs } ; 3324 } = true | the sum of the runs record of all rows is 3324 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'runs_4': 4, '3324_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'runs_4': 'runs', '3324_5': '3324'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'runs_4': [0], '3324_5': [1]} | ['rank', 'player', 'runs', 'average', 'career'] | [['1', 'irving romaine', '783', '25.25', '2006 - 2009'], ['2', 'david hemp', '641', '33.73', '2006 - 2009'], ['3', 'lionel cann', '590', '26.81', '2006 - 2009'], ['4', 'janeiro tucker', '496', '19.84', '2006 - 2009'], ['5', 'dean minors', '478', '26.55', '2006 - 2007'], ['6', 'steven outerbridge', '336', '14.60', '2006 - 2009']] |
1992 tampa bay buccaneers season | https://en.wikipedia.org/wiki/1992_Tampa_Bay_Buccaneers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11465246-2.html.csv | aggregation | the average attendance of games in the 1992 tampa bay buccaneers season was 50799 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '50799', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '50799', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '50799'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 50799 } = true', 'tointer': 'the average of the attendance record of all rows is 50799 .'} | round_eq { avg { all_rows ; attendance } ; 50799 } = true | the average of the attendance record of all rows is 50799 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '50799_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '50799_5': '50799'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '50799_5': [1]} | ['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'] | [['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'], ['1', 'september 6 , 1992', 'phoenix cardinals', 'w 23 - 7', '4:00', 'tampa stadium', '41315', '1 - 0'], ['2', 'september 13 , 1992', 'green bay packers', 'w 31 - 3', '1:00', 'tampa stadium', '50051', '2 - 0'], ['3', 'september 20 , 1992', 'minnesota vikings', 'l 26 - 20', '1:00', 'hubert h humphrey metrodome', '48113', '2 - 1'], ['4', 'september 27 , 1992', 'detroit lions', 'w 27 - 23', '1:00', 'pontiac silverdome', '51374', '3 - 1'], ['5', 'october 4 , 1992', 'indianapolis colts', 'l 24 - 14', '1:00', 'tampa stadium', '56585', '3 - 2'], ['6', '-', '-', '-', '-', '-', '-', ''], ['7', 'october 18 , 1992', 'chicago bears', 'l 31 - 14', '1:00', 'soldier field', '61412', '3 - 3'], ['8', 'october 25 , 1992', 'detroit lions', 'l 38 - 7', '1:00', 'tampa stadium', '53995', '3 - 4'], ['9', 'november 1 , 1992', 'new orleans saints', 'l 23 - 21', '1:00', 'louisiana superdome', '68591', '3 - 5'], ['10', 'november 8 , 1992', 'minnesota vikings', 'l 35 - 7', '1:00', 'tampa stadium', '49095', '3 - 6'], ['11', 'november 15 , 1992', 'chicago bears', 'w 20 - 17', '4:00', 'tampa stadium', '69102', '4 - 6'], ['12', 'november 22 , 1992', 'san diego chargers', 'l 29 - 14', '4:00', 'jack murphy stadium', '43197', '4 - 7'], ['13', 'november 29 , 1992', 'green bay packers', 'l 19 - 14', '1:00', 'milwaukee county stadium', '52347', '4 - 8'], ['14', 'december 6 , 1992', 'los angeles rams', 'l 31 - 27', '1:00', 'tampa stadium', '38387', '4 - 9'], ['15', 'december 13 , 1992', 'atlanta falcons', 'l 35 - 7', '1:00', 'tampa stadium', '39056', '4 - 10'], ['16', 'december 19 , 1992', 'san francisco 49ers', 'l 21 - 14', '4:00', 'candlestick park', '60519', '4 - 11'], ['17', 'december 27 , 1992', 'phoenix cardinals', 'w 7 - 3', '5:00', 'sun devil stadium', '29645', '5 - 11']] |
northeast hoosier conference | https://en.wikipedia.org/wiki/Northeast_Hoosier_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18936832-1.html.csv | superlative | in the northeast hoosier conference , the school with the highest enrollment is fort wayne homestead . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '6', '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', 'enrollment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment }'}, 'school'], 'result': 'fort wayne homestead', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; school }'}, 'fort wayne homestead'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; enrollment } ; school } ; fort wayne homestead } = true', 'tointer': 'select the row whose enrollment record of all rows is maximum . the school record of this row is fort wayne homestead .'} | eq { hop { argmax { all_rows ; enrollment } ; school } ; fort wayne homestead } = true | select the row whose enrollment record of all rows is maximum . the school record of this row is fort wayne homestead . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'school_6': 6, 'fort wayne homestead_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', 'school_6': 'school', 'fort wayne homestead_7': 'fort wayne homestead'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'school_6': [1], 'fort wayne homestead_7': [2]} | ['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'county'] | [['bellmont', 'decatur', 'braves', '927', 'aaa', '01 adams'], ['columbia city', 'columbia city', 'eagles', '1127', 'aaaa', '92 whitley'], ['dekalb', 'waterloo', 'barons', '1302', 'aaaa', '17 dekalb'], ['east noble', 'kendallville', 'knights', '1213', 'aaaa', '57 noble'], ['fort wayne carroll', 'fort wayne', 'chargers', '1889', 'aaaaa', '02 allen'], ['fort wayne homestead', 'fort wayne', 'spartans', '2141', 'aaaaa', '02 allen'], ['new haven', 'new haven', 'bulldogs', '985', 'aaaa', '02 allen'], ['norwell', 'ossian', 'knights', '876', 'aaaa', '90 wells']] |
2005 chicago white sox season | https://en.wikipedia.org/wiki/2005_Chicago_White_Sox_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12569321-11.html.csv | majority | the angels were the opponent for all of the chicago white sox games . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'angels', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'opponent', 'angels'], 'result': True, 'ind': 0, 'tointer': 'for the opponent records of all rows , all of them fuzzily match to angels .', 'tostr': 'all_eq { all_rows ; opponent ; angels } = true'} | all_eq { all_rows ; opponent ; angels } = true | for the opponent records of all rows , all of them fuzzily match to angels . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'opponent_3': 3, 'angels_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'opponent_3': 'opponent', 'angels_4': 'angels'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'opponent_3': [0], 'angels_4': [0]} | ['date', 'opponent', 'score', 'loss', 'time', 'att', 'record'] | [['october 11', 'angels', '2 - 3', 'contreras ( 1 - 1 )', '2:47', '40659', '3 - 1 ( 0 - 1 )'], ['october 12', 'angels', '2 - 1', 'escobar ( 1 - 1 )', '2:34', '41013', '4 - 1 ( 1 - 1 )'], ['october 14', 'angels', '5 - 2', 'lackey ( 0 - 1 )', '2:42', '44725', '5 - 1 ( 2 - 1 )'], ['october 15', 'angels', '8 - 2', 'santana ( 1 - 1 )', '2:46', '44857', '6 - 1 ( 3 - 1 )'], ['october 16', 'angels', '6 - 3', 'escobar ( 1 - 2 )', '3:11', '44712', '7 - 1 ( 4 - 1 )']] |
vanity ( performer ) | https://en.wikipedia.org/wiki/Vanity_%28performer%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1023439-2.html.csv | majority | the majority of vanity 's singles failed to appear on the us dance chart . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '-', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'us dance', '-'], 'result': True, 'ind': 0, 'tointer': 'for the us dance records of all rows , most of them fuzzily match to - .', 'tostr': 'most_eq { all_rows ; us dance ; - } = true'} | most_eq { all_rows ; us dance ; - } = true | for the us dance records of all rows , most of them fuzzily match to - . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'us dance_3': 3, '-_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'us dance_3': 'us dance', '-_4': '-'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'us dance_3': [0], '-_4': [0]} | ['year', 'title', 'us', 'us r & b', 'us dance'] | [['1984', 'pretty mess', '75', '15', '13'], ['1985', 'mechanical emotion', '107', '23', '-'], ['1986', 'under the influence', '56', '9', '6'], ['1986', 'animals', '-', '-', '-'], ['1988', 'undress', '-', '-', '-']] |
2006 hamburg sea devils season | https://en.wikipedia.org/wiki/2006_Hamburg_Sea_Devils_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24989925-2.html.csv | aggregation | all of the 9 games had an average attendance of 16261 . | {'scope': 'all', 'col': '8', 'type': 'average', 'result': '16261', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '16261', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '16261'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 16261 } = true', 'tointer': 'the average of the attendance record of all rows is 16261 .'} | round_eq { avg { all_rows ; attendance } ; 16261 } = true | the average of the attendance record of all rows is 16261 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '16261_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '16261_5': '16261'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '16261_5': [1]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'saturday , march 18', '6:00 pm', 'cologne centurions', 'l 10 - 14', '0 - 1 - 0', 'aol arena', '15243'], ['2', 'saturday , march 25', '7:00 pm', 'frankfurt galaxy', 'l 14 - 31', '0 - 2 - 0', 'commerzbank - arena', '26713'], ['3', 'saturday , april 1', '6:00 pm', 'berlin thunder', 't 17 - 17 ot', '0 - 2 - 1', 'aol arena', '15837'], ['4', 'saturday , april 8', '7:00 pm', 'rhein fire', 'l 21 - 31', '0 - 3 - 1', 'ltu arena', '18224'], ['5', 'saturday , april 15', '6:00 pm', 'frankfurt galaxy', 'l 13 - 17', '0 - 4 - 1', 'aol arena', '12281'], ['6', 'sunday , april 23', '4:00 pm', 'cologne centurions', 'l 17 - 20', '0 - 5 - 1', 'rheinenergiestadion', '9238'], ['7', 'saturday , april 29', '6:00 pm', 'amsterdam admirals', 'l 17 - 18', '0 - 6 - 1', 'aol arena', '15224'], ['8', 'sunday , may 7', '4:00 pm', 'berlin thunder', 'w 38 - 14', '1 - 6 - 1', 'olympic stadium', '16762'], ['9', 'sunday , may 14', '4:00 pm', 'rhein fire', 'w 13 - 10', '2 - 6 - 1', 'aol arena', '16823']] |
list of the busiest airports in the united states | https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_the_United_States | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18047346-5.html.csv | comparative | los angeles international airport is busier than jfk international airport . | {'row_1': '5', 'row_2': '6', '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', 'airport name', 'los angeles international airport'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose airport name record fuzzily matches to los angeles international airport .', 'tostr': 'filter_eq { all_rows ; airport name ; los angeles international airport }'}, 'tonnes'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; airport name ; los angeles international airport } ; tonnes }', 'tointer': 'select the rows whose airport name record fuzzily matches to los angeles international airport . take the tonnes record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'airport name', 'john f kennedy international airport'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose airport name record fuzzily matches to john f kennedy international airport .', 'tostr': 'filter_eq { all_rows ; airport name ; john f kennedy international airport }'}, 'tonnes'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; airport name ; john f kennedy international airport } ; tonnes }', 'tointer': 'select the rows whose airport name record fuzzily matches to john f kennedy international airport . take the tonnes record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; airport name ; los angeles international airport } ; tonnes } ; hop { filter_eq { all_rows ; airport name ; john f kennedy international airport } ; tonnes } } = true', 'tointer': 'select the rows whose airport name record fuzzily matches to los angeles international airport . take the tonnes record of this row . select the rows whose airport name record fuzzily matches to john f kennedy international airport . take the tonnes record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; airport name ; los angeles international airport } ; tonnes } ; hop { filter_eq { all_rows ; airport name ; john f kennedy international airport } ; tonnes } } = true | select the rows whose airport name record fuzzily matches to los angeles international airport . take the tonnes record of this row . select the rows whose airport name record fuzzily matches to john f kennedy international airport . take the tonnes 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, 'airport name_7': 7, 'los angeles international airport_8': 8, 'tonnes_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'airport name_11': 11, 'john f kennedy international airport_12': 12, 'tonnes_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', 'airport name_7': 'airport name', 'los angeles international airport_8': 'los angeles international airport', 'tonnes_9': 'tonnes', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'airport name_11': 'airport name', 'john f kennedy international airport_12': 'john f kennedy international airport', 'tonnes_13': 'tonnes'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'airport name_7': [0], 'los angeles international airport_8': [0], 'tonnes_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'airport name_11': [1], 'john f kennedy international airport_12': [1], 'tonnes_13': [3]} | ['rank', 'airport name', 'location', 'iata code', 'tonnes', '% chg 2010 / 11'] | [['1', 'memphis international airport', 'memphis , tennessee', 'mem', '3916410', '0 0.0 %'], ['2', 'ted stevens anchorage international airport', 'anchorage , alaska', 'anc', '2543105', '0 3.9 %'], ['3', 'louisville international airport', 'louisville , kentucky', 'sdf', '2188422', '0 1.0 %'], ['4', 'miami international airport', 'miami , florida', 'mia', '1841929', '0 0.3 %'], ['5', 'los angeles international airport', 'los angeles , california', 'lax', '1681611', '0 3.8 %'], ['6', 'john f kennedy international airport', 'queens , new york', 'jfk', '1348992', '0 0.5 %'], ['7', "o'hare international airport", 'chicago , illinois', 'ord', '1311622', '0 4.7 %'], ['8', 'indianapolis international airport', 'indianapolis', 'ind', '0 971664', '0 4.0 %'], ['9', 'newark liberty international airport', 'newark , new jersey', 'ewr', '0 813209', '0 5.0 %']] |
1982 world ice hockey championships | https://en.wikipedia.org/wiki/1982_World_Ice_Hockey_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14155555-4.html.csv | aggregation | a total of 56 points were scored at the 1982 world ice hockey championships . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '56', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '56', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '56'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 56 } = true', 'tointer': 'the sum of the points record of all rows is 56 .'} | round_eq { sum { all_rows ; points } ; 56 } = true | the sum of the points record of all rows is 56 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '56_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '56_5': '56'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '56_5': [1]} | ['games', 'drawn', 'lost', 'points difference', 'points'] | [['7', '1', '0', '48 - 25', '13'], ['7', '1', '2', '33 - 26', '9'], ['7', '1', '2', '42 - 23', '9'], ['7', '0', '4', '24 - 43', '6'], ['7', '1', '4', '27 - 30', '5'], ['7', '3', '3', '20 - 27', '5'], ['7', '1', '4', '32 - 47', '5'], ['7', '0', '5', '22 - 27', '4']] |
2009 - 10 south florida bulls men 's basketball team | https://en.wikipedia.org/wiki/2009%E2%80%9310_South_Florida_Bulls_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25177625-1.html.csv | aggregation | the average weight of the four freshman on the 2009-10 university of south florida men 's basketball team was 215 pounds . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '215', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'freshman'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', 'freshman'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; freshman }', 'tointer': 'select the rows whose year record fuzzily matches to freshman .'}, 'weight'], 'result': '215', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; year ; freshman } ; weight }'}, '215'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; year ; freshman } ; weight } ; 215 } = true', 'tointer': 'select the rows whose year record fuzzily matches to freshman . the average of the weight record of these rows is 215 .'} | round_eq { avg { filter_eq { all_rows ; year ; freshman } ; weight } ; 215 } = true | select the rows whose year record fuzzily matches to freshman . the average of the weight record of these rows is 215 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, 'freshman_6': 6, 'weight_7': 7, '215_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', 'freshman_6': 'freshman', 'weight_7': 'weight', '215_8': '215'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], 'freshman_6': [0], 'weight_7': [1], '215_8': [2]} | ['name', '-', 'position', 'height', 'weight', 'year', 'former school', 'hometown'] | [['ron anderson jr', '1', 'forward', '6 - 8', '255', 'rs junior', 'kansas state / mccallie school', 'upper marlboro , md'], ['mike burwell', '23', 'guard', '6 - 6', '210', 'freshman', 'south kent school / cardinal mccarrick hs', 'east brunswick , nj'], ['anthony crater', '10', 'guard', '6 - 1', '170', 'sophomore', 'ohio state university / brewster academy', 'flint , mi'], ['bj daniels', '2', 'guard', '6 - 1', '212', 'sophomore', 'lincoln hs', 'tallahassee , fl'], ['jordan dumars', '4', 'guard', '6 - 5', '225', 'freshman', 'detroit country day school', 'detroit , mi'], ['toarlyn fitzpatrick', '32', 'forward', '6 - 8', '230', 'freshman', 'king hs', 'tampa , fl'], ['augustus gilchrist', '24', 'forward / center', '6 - 10', '245', 'sophomore', 'maryland / academy', 'clinton , md'], ['chris howard', '3', 'guard', '6 - 3', '200', 'senior', 'friendly hs', 'fort washington , md'], ['dominique jones', '20', 'guard', '6 - 4', '215', 'junior', 'lake wales hs', 'lake wales , fl'], ['ryan kardok', '13', 'guard', '6 - 3', '188', 'senior', 'broward community college / stoneman douglas hs', 'parkland , fl'], ['justin leemow', '5', 'guard', '6 - 1', '180', 'somphomore', 'mt zion christian academy', 'brooklyn , ny'], ['mike mercer', '33', 'guard', '6 - 5', '195', 'senior', 'georgia / south gwinnett hs', 'snellville , ga'], ['shaun noriega', '22', 'guard', '6 - 4', '195', 'freshman', 'north port hs', 'north port , fl']] |
1948 ashes series | https://en.wikipedia.org/wiki/1948_Ashes_series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16570286-3.html.csv | unique | ernie toshack is the only player who played 4 matches in the 1948 ashes series . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '4', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'matches', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose matches record is equal to 4 .', 'tostr': 'filter_eq { all_rows ; matches ; 4 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; matches ; 4 } }', 'tointer': 'select the rows whose matches record is equal to 4 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'matches', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose matches record is equal to 4 .', 'tostr': 'filter_eq { all_rows ; matches ; 4 }'}, 'player'], 'result': 'ernie toshack', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; matches ; 4 } ; player }'}, 'ernie toshack'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; matches ; 4 } ; player } ; ernie toshack }', 'tointer': 'the player record of this unqiue row is ernie toshack .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; matches ; 4 } } ; eq { hop { filter_eq { all_rows ; matches ; 4 } ; player } ; ernie toshack } } = true', 'tointer': 'select the rows whose matches record is equal to 4 . there is only one such row in the table . the player record of this unqiue row is ernie toshack .'} | and { only { filter_eq { all_rows ; matches ; 4 } } ; eq { hop { filter_eq { all_rows ; matches ; 4 } ; player } ; ernie toshack } } = true | select the rows whose matches record is equal to 4 . there is only one such row in the table . the player record of this unqiue row is ernie toshack . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'matches_7': 7, '4_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'ernie toshack_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'matches_7': 'matches', '4_8': '4', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'ernie toshack_10': 'ernie toshack'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'matches_7': [0], '4_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'ernie toshack_10': [3]} | ['player', 'team', 'matches', 'wickets', 'average', 'best bowling'] | [['ray lindwall', 'australia', '5', '27', '19.62', '6 / 20'], ['bill johnston', 'australia', '5', '27', '23.33', '5 / 36'], ['alec bedser', 'england', '5', '18', '38.22', '4 / 81'], ['keith miller', 'australia', '5', '13', '23.15', '4 / 125'], ['ernie toshack', 'australia', '4', '11', '33.09', '5 / 40'], ['norman yardley', 'england', '5', '9', '22.66', '2 / 32'], ['jim laker', 'england', '3', '9', '52.44', '4 / 138']] |
sat subject tests | https://en.wikipedia.org/wiki/SAT_subject_tests | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1637315-1.html.csv | majority | for the sat subject tests in languages , the majority of the mean scores were above 621 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '621', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'mean score', '621'], 'result': True, 'ind': 0, 'tointer': 'for the mean score records of all rows , most of them are greater than 621 .', 'tostr': 'most_greater { all_rows ; mean score ; 621 } = true'} | most_greater { all_rows ; mean score ; 621 } = true | for the mean score records of all rows , most of them are greater than 621 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'mean score_3': 3, '621_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'mean score_3': 'mean score', '621_4': '621'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'mean score_3': [0], '621_4': [0]} | ['test', 'subject', 'mean score', 'standard deviation', 'number of students'] | [['sat subject test in literature', 'literature', '576', '111', '120004'], ['sat subject test in united states history', 'us history', '608', '113', '126681'], ['sat subject test in world history', 'world history', '607', '118', '19688'], ['sat subject test in mathematics level 1', 'mathematics', '610', '100', '82827'], ['sat subject test in mathematics level 2', 'mathematics', '654', '107', '176472'], ['sat subject test in biology e / m', 'biology', 'e - 605 m - 635', '110 108', '86206 in total , 40076 ( e ) 46130 ( m )'], ['sat subject test in chemistry', 'chemistry', '648', '110', '76077'], ['sat subject test in physics', 'physics', '656', '105', '49608'], ['sat subject test in chinese with listening', 'chinese', '758', '67', '7294'], ['sat subject test in french', 'french', '622', '123', '10391'], ['sat subject test in french with listening', 'french', '646', '117', '2370'], ['sat subject test in german', 'german', '622', '135', '777'], ['sat subject test in german with listening', 'german', '611', '122', '770'], ['sat subject test in modern hebrew', 'modern hebrew', '623', '140', '491'], ['sat subject test in italian', 'italian', '666', '122', '737'], ['sat subject test in japanese with listening', 'japanese', '684', '113', '1966'], ['sat subject test in korean with listening', 'korean', '767', '57', '4273'], ['sat subject test in latin', 'latin', '611', '107', '3010'], ['sat subject test in spanish', 'spanish', '647', '117', '37762'], ['sat subject test in spanish with listening', 'spanish', '663', '107', '6399']] |
karin knapp | https://en.wikipedia.org/wiki/Karin_Knapp | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11522060-6.html.csv | count | twelve of the tournaments took place in italy . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'italy', 'result': '12', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'italy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to italy .', 'tostr': 'filter_eq { all_rows ; tournament ; italy }'}], 'result': '12', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; tournament ; italy } }', 'tointer': 'select the rows whose tournament record fuzzily matches to italy . the number of such rows is 12 .'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; tournament ; italy } } ; 12 } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to italy . the number of such rows is 12 .'} | eq { count { filter_eq { all_rows ; tournament ; italy } } ; 12 } = true | select the rows whose tournament record fuzzily matches to italy . 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, 'tournament_5': 5, 'italy_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', 'tournament_5': 'tournament', 'italy_6': 'italy', '12_7': '12'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'tournament_5': [0], 'italy_6': [0], '12_7': [2]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['runner - up', '6 october 2003', 'bari , italy', 'clay', 'bettina pirker', '6 - 2 , 7 - 5'], ['runner - up', '14 june 2005', 'lenzerheide , switzerland', 'clay', 'danica krstajić', '6 - 2 , 7 - 5'], ['runner - up', '1 may 2006', 'catania , italy', 'clay', 'maría josé martínez sánchez', '6 - 3 , 4 - 6 , 6 - 4'], ['winner', '25 july 2006', "monteroni d'arbia , italy", 'clay', 'edina gallovits - hall', '6 - 2 , 6 - 1'], ['runner - up', '31 july 2006', 'martina franca , italy', 'clay', 'margalita chakhnashvili', '6 - 3 , 7 - 5'], ['runner - up', '13 march 2007', 'orange , usa', 'hard', 'naomi cavaday', '6 - 1 , 6 - 1'], ['runner - up', '3 april 2007', 'dinan , france', 'clay ( i )', 'maša zec peškirič', '6 - 4 , 6 - 2'], ['runner - up', '9 april 2007', 'civitavecchia , italy', 'clay', 'darya kustova', '3 - 6 , 6 - 4 , 6 - 4'], ['runner - up', '9 july 2007', 'biella , italy', 'clay', 'agnieszka radwańska', '6 - 3 , 6 - 3'], ['runner - up', '11 october 2010', 'settimo san pietro , italy', 'clay', 'anastasia grymalska', '4 - 6 , 6 - 2 , 7 - 5'], ['winner', '18 october 2010', 'seville , spain', 'clay', 'andrea gámiz', '6 - 0 , 6 - 1'], ['runner - up', '16 november 2010', 'mallorca , spain', 'clay', 'diana enache', '6 - 4 , 6 - 2'], ['winner', '7 june 2011', 'campobasso , italy', 'clay', 'alizé lim', '6 - 2 , 6 - 4'], ['runner - up', '14 june 2011', 'padova , italy', 'clay', 'kristina mladenovic', '3 - 6 , 6 - 4 , 6 - 0'], ['winner', '20 june 2011', 'rome , italy', 'clay', 'laura thorpe', '6 - 3 , 6 - 0'], ['runner - up', '27 august 2012', 'bagnatica , italy', 'clay', 'maria - elena camerin', '7 - 6 ( 5 ) , 6 - 4'], ['winner', '4 september 2012', 'mestre , italy', 'clay', 'estrella cabeza candela', '6 - 1 , 3 - 6 , 6 - 1'], ['runner - up', '12 may 2013', 'trnava , slovakia', 'clay', 'barbora záhlavová - strýcová', '6 - 2 , 6 - 4']] |
2008 - 09 süper lig | https://en.wikipedia.org/wiki/2008%E2%80%9309_S%C3%BCper_Lig | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17356873-1.html.csv | majority | the shirt sponsor for the majority of teams in the 2008 - 09 süper lig is turkcell . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'turkcell', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'shirt sponsor', 'turkcell'], 'result': True, 'ind': 0, 'tointer': 'for the shirt sponsor records of all rows , most of them fuzzily match to turkcell .', 'tostr': 'most_eq { all_rows ; shirt sponsor ; turkcell } = true'} | most_eq { all_rows ; shirt sponsor ; turkcell } = true | for the shirt sponsor records of all rows , most of them fuzzily match to turkcell . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'shirt sponsor_3': 3, 'turkcell_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'shirt sponsor_3': 'shirt sponsor', 'turkcell_4': 'turkcell'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'shirt sponsor_3': [0], 'turkcell_4': [0]} | ['team', 'head coach', 'team captain', 'venue', 'capacity', 'kitmaker', 'shirt sponsor', 'club chairman'] | [['ankaragücü', 'hakan kutlu', 'murat erdoğan', 'ankara 19 mayıs stadium', '19209', 'lotto', 'turkcell', 'cemal azmi aydın'], ['ankaraspor', 'aykut kocaman', 'hürriyet güçer', 'yenikent asaş stadium', '19626', 'nike', 'turkcell', 'ruhi kurnaz'], ['antalyaspor', 'mehmet özdilek', 'uğur kavuk', 'antalya atatürk stadium', '11137', 'nike', 'mardan', 'hasan y akıncıoğlu'], ['beşiktaş', 'mustafa denizli', 'matías delgado', 'bjk inönü stadium', '32086', 'umbro', 'cola turka', 'yıldırım demirören'], ['bursaspor', 'ertuğrul sağlam', 'ömer erdoğan', 'bursa atatürk stadium', '18587', 'kappa', 'turkcell', 'ibrahim yazıcı'], ['denizlispor', 'mesut bakkal', 'roman kratochvil', 'denizli atatürk stadium', '15427', 'lescon', 'turkcell', 'ali ipek'], ['eskişehirspor', 'rıza çalımbay', 'emre toraman', 'eskişehir atatürk stadium', '18880', 'nike', 'eti', 'halil ünal'], ['fenerbahçe', 'luis aragonés', 'alex', 'şükrü saracoğlu stadium', '53586', 'adidas', 'avea', 'aziz yıldırım'], ['galatasaray', 'bülent korkmaz', 'ayhan akman', 'ali sami yen stadium', '22800', 'adidas', 'avea', 'adnan polat'], ['gaziantepspor', 'josé couceiro', 'bekir irtegün', 'gaziantep kamil ocak stadium', '16981', 'lescon', 'turkcell', 'ibrahim halil kızıl'], ['gençlerbirliği', 'samet aybaba', 'abdel zaher el saka', 'ankara 19 mayıs stadium', '19209', 'lotto', 'turkcell', 'ilhan cavcav'], ['hacettepe', 'erdoğan arıca', 'orhan şam', 'ankara 19 mayıs stadium', '19209', 'lotto', 'turkcell', 'turgay kalemci'], ['istanbul bb', 'abdullah avcı', 'efe inanç', 'atatürk olympic stadium', '76092', 'lescon', 'kalpen', 'göksel gümüşdağ'], ['kayserispor', 'tolunay kafkas', 'mehmet topuz', 'kadir has stadium 1', '32864', 'adidas', 'turkcell', 'recep mamur'], ['kocaelispor', 'erhan altın', 'serdar topraktepe', 'ismet pasa stadium', '12710', 'umbro', 'erciyas', 'serhan gürkan'], ['konyaspor', 'ünal karaman', 'ömer gündostu', 'konya atatürk stadium', '21968', 'lotto', 'turkcell', 'mehmet ali kuntoğlu'], ['sivasspor', 'bülent uygun', 'mehmet yildiz', 'sivas 4 eylül stadium', '14998', 'adidas', 'turkcell', 'mecnun otyakmaz']] |
1986 - 87 dundee united f.c. season | https://en.wikipedia.org/wiki/1986%E2%80%9387_Dundee_United_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15640438-5.html.csv | ordinal | in the 1986 - 87 dundee united f.c. season , the second time they played against lens was a home game . | {'scope': 'subset', 'row': '2', 'col': '1', 'order': '2', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'lens'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'lens'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; lens }', 'tointer': 'select the rows whose opponent record fuzzily matches to lens .'}, 'date', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; opponent ; lens } ; date ; 2 }'}, 'venue'], 'result': 'h', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; opponent ; lens } ; date ; 2 } ; venue }'}, 'h'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; opponent ; lens } ; date ; 2 } ; venue } ; h } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to lens . select the row whose date record of these rows is 2nd minimum . the venue record of this row is h .'} | eq { hop { nth_argmin { filter_eq { all_rows ; opponent ; lens } ; date ; 2 } ; venue } ; h } = true | select the rows whose opponent record fuzzily matches to lens . select the row whose date record of these rows is 2nd minimum . the venue record of this row is h . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'opponent_6': 6, 'lens_7': 7, 'date_8': 8, '2_9': 9, 'venue_10': 10, 'h_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'opponent_6': 'opponent', 'lens_7': 'lens', 'date_8': 'date', '2_9': '2', 'venue_10': 'venue', 'h_11': 'h'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'opponent_6': [0], 'lens_7': [0], 'date_8': [1], '2_9': [1], 'venue_10': [2], 'h_11': [3]} | ['date', 'opponent', 'venue', 'result', 'attendance'] | [['17 september 1986', 'lens', 'a', '0 - 1', '11330'], ['1 october 1986', 'lens', 'h', '2 - 0', '11645'], ['22 october 1986', 'universitatea craiova', 'h', '3 - 0', '10728'], ['5 november 1986', 'universitatea craiova', 'a', '0 - 1', '35000'], ['26 november 1986', 'hajduk split', 'h', '2 - 0', '11569'], ['10 december 1986', 'hajduk split', 'a', '0 - 0', '26000'], ['4 march 1987', 'barcelona', 'h', '1 - 0', '21322'], ['18 march 1987', 'barcelona', 'a', '2 - 1', '42000'], ['8 april 1987', 'mönchengladbach', 'h', '0 - 0', '15789'], ['22 april 1987', 'mönchengladbach', 'a', '2 - 0', '33500'], ['6 may 1987', 'gothenburg', 'a', '0 - 1', '50053'], ['20 may 1987', 'gothenburg', 'h', '1 - 1', '20911']] |
hubert hahne | https://en.wikipedia.org/wiki/Hubert_Hahne | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1233847-1.html.csv | count | hubert hahne drove with a lola t100 chassis a total of two times . | {'scope': 'all', 'criterion': 'equal', 'value': 'lola t100', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'lola t100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to lola t100 .', 'tostr': 'filter_eq { all_rows ; chassis ; lola t100 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; chassis ; lola t100 } }', 'tointer': 'select the rows whose chassis record fuzzily matches to lola t100 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; chassis ; lola t100 } } ; 2 } = true', 'tointer': 'select the rows whose chassis record fuzzily matches to lola t100 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; chassis ; lola t100 } } ; 2 } = true | select the rows whose chassis record fuzzily matches to lola t100 . 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, 'chassis_5': 5, 'lola t100_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', 'chassis_5': 'chassis', 'lola t100_6': 'lola t100', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'chassis_5': [0], 'lola t100_6': [0], '2_7': [2]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1966', 'tyrrell racing organisation', 'matra ms5 ( f2 )', 'brm straight - 4', '0'], ['1967', 'bayerische motoren werke', 'lola t100', 'bmw straight - 4', '0'], ['1968', 'bayerische motoren werke', 'lola t100', 'bmw straight - 4', '0'], ['1969', 'bayerische motoren werke', 'bmw t269 ( f2 )', 'bmw straight - 4', '0'], ['1970', 'hubert hahne', 'march 701', 'cosworth v8', '0']] |
1990 los angeles raiders season | https://en.wikipedia.org/wiki/1990_Los_Angeles_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16376436-4.html.csv | superlative | the game against the chicago bears on september 30 is the highest attended game in the raider 's 1990 season . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'september 30 , 1990', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'september 30 , 1990'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; september 30 , 1990 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is september 30 , 1990 .'} | eq { hop { argmax { all_rows ; attendance } ; date } ; september 30 , 1990 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is september 30 , 1990 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, 'september 30 , 1990_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'date_6': 'date', 'september 30 , 1990_7': 'september 30 , 1990'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'september 30 , 1990_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 9 , 1990', 'denver broncos', 'w 14 - 9', '54206'], ['2', 'september 16 , 1990', 'seattle seahawks', 'w 17 - 13', '61889'], ['3', 'september 23 , 1990', 'pittsburgh steelers', 'w 20 - 3', '50657'], ['4', 'september 30 , 1990', 'chicago bears', 'w 24 - 10', '80156'], ['5', 'october 7 , 1990', 'buffalo bills', 'l 38 - 24', '80076'], ['6', 'october 14 , 1990', 'seattle seahawks', 'w 24 - 17', '50624'], ['7', 'october 21 , 1990', 'san diego chargers', 'w 24 - 9', '60569'], ['9', 'november 4 , 1990', 'kansas city chiefs', 'l 9 - 7', '70951'], ['10', 'november 11 , 1990', 'green bay packers', 'l 29 - 16', '50855'], ['11', 'november 19 , 1990', 'miami dolphins', 'w 13 - 10', '70553'], ['12', 'november 25 , 1990', 'kansas city chiefs', 'l 27 - 24', '65710'], ['13', 'december 2 , 1990', 'denver broncos', 'w 23 - 20', '74162'], ['14', 'december 10 , 1990', 'detroit lions', 'w 38 - 31', '72190'], ['15', 'december 16 , 1990', 'cincinnati bengals', 'w 24 - 7', '54132'], ['16', 'december 22 , 1990', 'minnesota vikings', 'w 28 - 24', '53899'], ['17', 'december 30 , 1990', 'san diego chargers', 'w 17 - 12', '62593']] |
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/1-15187735-4.html.csv | count | three of the segment a episodes deal with plastic . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'plastic', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment a', 'plastic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment a record fuzzily matches to plastic .', 'tostr': 'filter_eq { all_rows ; segment a ; plastic }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; segment a ; plastic } }', 'tointer': 'select the rows whose segment a record fuzzily matches to plastic . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; segment a ; plastic } } ; 3 } = true', 'tointer': 'select the rows whose segment a record fuzzily matches to plastic . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; segment a ; plastic } } ; 3 } = true | select the rows whose segment a record fuzzily matches to plastic . 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, 'segment a_5': 5, 'plastic_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', 'segment a_5': 'segment a', 'plastic_6': 'plastic', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'segment a_5': [0], 'plastic_6': [0], '3_7': [2]} | ['series ep', 'episode', 'netflix', 'segment a', 'segment b', 'segment c', 'segment d'] | [['4 - 01', '40', 's02e14', 'plastic bottles & s jar', 'mail', 's egg', 'ed handcraft en wood s pen'], ['4 - 02', '41', 's02e15', 'plastic injection moulds', 'automotive oil filters', 'filing cabinets', 'blown glass'], ['4 - 03', '42', 's02e16', 'high - precision cutting tools', 'stained glass', 's semi - trailer', 's recorder'], ['4 - 04', '43', 's02e17', 'conga drums', 'metal plating', 's button ( part 1 )', 's button ( part 2 )'], ['4 - 05', '44', 's02e18', 'grinding wheels', 'compost', 'window blinds', 'milk'], ['4 - 06', '45', 's02e19', 'es brush and push brooms', 's blackboard', 'smoked salmon', 's zipper'], ['4 - 07', '46', 's02e20', '3d commercial signs', 'hardwood floors', 'corrugated polyethylene pipe', 'es mattress'], ['4 - 08', '47', 's02e21', 'ceramic tiles', 'nuts', 'steel forgings', 's skateboard'], ['4 - 09', '48', 's02e22', 'car engines', 'flour', 's recliner', 's envelope'], ['4 - 10', '49', 's02e23', 'plastic cups and cutlery', 'special effects makeup', 'gold', 's harp'], ['4 - 11', '50', 's02e24', 'laminate', 's frozen treat', "children 's building blocks", 's detergent'], ['4 - 12', '51', 's02e25', 's decorative moulding', 'commercial pulleys', 'industrial rubber hose', 'sheet vinyl flooring']] |
1941 vfl season | https://en.wikipedia.org/wiki/1941_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807673-8.html.csv | superlative | the highest away team score for the round 8 1941 victorian football league season was held by footscray . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'away team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; away team score }'}, 'away team'], 'result': 'footscray', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; away team score } ; away team }'}, 'footscray'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; away team score } ; away team } ; footscray } = true', 'tointer': 'select the row whose away team score record of all rows is maximum . the away team record of this row is footscray .'} | eq { hop { argmax { all_rows ; away team score } ; away team } ; footscray } = true | select the row whose away team score record of all rows is maximum . the away team record of this row is footscray . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'away team score_5': 5, 'away team_6': 6, 'footscray_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'away team score_5': 'away team score', 'away team_6': 'away team', 'footscray_7': 'footscray'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'away team score_5': [0], 'away team_6': [1], 'footscray_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '10.13 ( 73 )', 'st kilda', '6.11 ( 47 )', 'punt road oval', '6000', '21 june 1941'], ['hawthorn', '6.8 ( 44 )', 'melbourne', '12.12 ( 84 )', 'glenferrie oval', '2000', '21 june 1941'], ['collingwood', '8.12 ( 60 )', 'essendon', '7.10 ( 52 )', 'victoria park', '6000', '21 june 1941'], ['carlton', '10.17 ( 77 )', 'fitzroy', '12.13 ( 85 )', 'princes park', '4000', '21 june 1941'], ['south melbourne', '8.16 ( 64 )', 'north melbourne', '6.6 ( 42 )', 'lake oval', '5000', '21 june 1941'], ['geelong', '10.18 ( 78 )', 'footscray', '13.15 ( 93 )', 'kardinia park', '5000', '21 june 1941']] |
2010 - 11 atlanta hawks season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27734577-11.html.csv | majority | during this period of the 2010-11 atlanta hawks season , the atlanta hawks lost the majority of their games . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'score', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; score ; l } = true'} | most_eq { all_rows ; score ; l } = true | for the score records of all rows , most of them fuzzily match to l . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, 'l_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', 'l_4': 'l'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], 'l_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['76', 'april 1', 'boston', 'w 88 - 83 ( ot )', 'jamal crawford ( 20 )', 'al horford ( 15 )', 'jamal crawford , al horford ( 4 )', 'philips arena 19763', '44 - 32'], ['77', 'april 3', 'houston', 'l 109 - 114 ( ot )', 'joe johnson ( 25 )', 'josh smith ( 11 )', 'joe johnson , josh smith ( 7 )', 'toyota center 15993', '44 - 33'], ['78', 'april 5', 'san antonio', 'l 90 - 97 ( ot )', 'joe johnson ( 21 )', 'al horford ( 9 )', 'al horford ( 5 )', 'philips arena 17277', '44 - 34'], ['79', 'april 8', 'indiana', 'l 102 - 114 ( ot )', 'jeff teague ( 21 )', 'zaza pachulia ( 11 )', 'jamal crawford ( 3 )', 'conseco fieldhouse 15879', '44 - 35'], ['80', 'april 9', 'washington', 'l 83 - 115 ( ot )', 'al horford ( 21 )', 'al horford ( 10 )', 'jeff teague ( 5 )', 'verizon center 19771', '44 - 36']] |
list of paris saint - germain f.c. players | https://en.wikipedia.org/wiki/List_of_Paris_Saint-Germain_F.C._players | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24565004-11.html.csv | aggregation | the average number of appearances for these five paris saint-germain players is 98.2 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '98.2', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'appearances'], 'result': '98.2', 'ind': 0, 'tostr': 'avg { all_rows ; appearances }'}, '98.2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; appearances } ; 98.2 } = true', 'tointer': 'the average of the appearances record of all rows is 98.2 .'} | round_eq { avg { all_rows ; appearances } ; 98.2 } = true | the average of the appearances record of all rows is 98.2 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'appearances_4': 4, '98.2_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'appearances_4': 'appearances', '98.2_5': '98.2'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'appearances_4': [0], '98.2_5': [1]} | ['name', 'position', 'period', 'appearances', 'goals', 'nationality square'] | [['robert jacques', 'forward', '1985 - 1986', '28', '6', 'france'], ['christophe jallet', 'defender', '2009 -', '180', '9', 'france'], ['gérard janvion', 'defender', '1983 - 1985', '50', '0', 'france'], ['philippe jean', 'defender', '1977 - 1979', '14', '0', 'france'], ['philippe jeannol', 'defender', '1984 - 1991', '219', '15', 'france']] |
paul kelly ( fighter ) | https://en.wikipedia.org/wiki/Paul_Kelly_%28fighter%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16881318-2.html.csv | count | among the ufc events that paul kelly ( fighter ) participated in , 4 of them started at 5:00 . | {'scope': 'subset', 'criterion': 'equal', 'value': '5:00', 'result': '4', 'col': '7', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': 'ufc'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'ufc'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; event ; ufc }', 'tointer': 'select the rows whose event record fuzzily matches to ufc .'}, 'time', '5:00'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose event record fuzzily matches to ufc . among these rows , select the rows whose time record fuzzily matches to 5:00 .', 'tostr': 'filter_eq { filter_eq { all_rows ; event ; ufc } ; time ; 5:00 }'}], 'result': '4', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; event ; ufc } ; time ; 5:00 } }', 'tointer': 'select the rows whose event record fuzzily matches to ufc . among these rows , select the rows whose time record fuzzily matches to 5:00 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; event ; ufc } ; time ; 5:00 } } ; 4 } = true', 'tointer': 'select the rows whose event record fuzzily matches to ufc . among these rows , select the rows whose time record fuzzily matches to 5:00 . the number of such rows is 4 .'} | eq { count { filter_eq { filter_eq { all_rows ; event ; ufc } ; time ; 5:00 } } ; 4 } = true | select the rows whose event record fuzzily matches to ufc . among these rows , select the rows whose time record fuzzily matches to 5:00 . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'event_6': 6, 'ufc_7': 7, 'time_8': 8, '5:00_9': 9, '4_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'event_6': 'event', 'ufc_7': 'ufc', 'time_8': 'time', '5:00_9': '5:00', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'event_6': [0], 'ufc_7': [0], 'time_8': [1], '5:00_9': [1], '4_10': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '14 - 5', 'henrique santana', 'tko ( punches )', 'uwc 22', '1', '3:47', 'essex , england , united kingdom'], ['win', '13 - 5', 'richard griffin', 'submission ( guillotine choke )', 'ucmma 31', '2', '2:52', 'london , england , united kingdom'], ['loss', '12 - 5', 'ryan healy', 'decision ( unanimous )', 'sfl 2', '3', '5:00', 'chandigarh , india'], ['loss', '12 - 4', 'donald cerrone', 'submission ( rear naked choke )', 'ufc 126', '2', '3:48', 'las vegas , nevada , united states'], ['win', '12 - 3', "tj o'brien", 'tko ( elbows )', 'ufc 123', '2', '3:16', 'auburn hills , michigan , united states'], ['loss', '11 - 3', 'jacob volkmann', 'decision ( unanimous )', 'ufc live : jones vs matyushenko', '3', '5:00', 'san diego , california , united states'], ['win', '11 - 2', 'matt veach', 'submission ( guillotine choke )', 'ufc 112', '2', '3:41', 'abu dhabi , united arab emirates'], ['loss', '10 - 2', 'dennis siver', 'tko ( spinning back kick and punches )', 'ufc 105', '2', '2:53', 'manchester , england'], ['win', '10 - 1', 'rolando delgado', 'decision ( unanimous )', 'ufc 99', '3', '5:00', 'cologne , germany'], ['win', '9 - 1', 'troy mandaloniz', 'decision ( unanimous )', 'ufc 95', '3', '5:00', 'london , england'], ['loss', '8 - 1', 'marcus davis', 'submission ( guillotine choke )', 'ufc 89', '2', '2:16', 'birmingham , england'], ['win', '8 - 0', 'paul taylor', 'decision ( unanimous )', 'ufc 80', '3', '5:00', 'newcastle upon tyne , england'], ['win', '7 - 0', 'jordan james', 'tko ( punches )', 'cage gladiators 4 : prepare for glory', '2', '2:40', 'liverpool , england'], ['win', '6 - 0', 'sami berik', 'submission ( rear naked choke )', 'cage warriors : enter the rough house 3', '1', '1:27', 'nottingham , england'], ['win', '5 - 0', 'marius liaukevicius', 'submission ( arm triangle choke )', 'clash of warriors', '1', '1:10', 'england'], ['win', '4 - 0', 'bruce davis', 'tko ( cut )', 'house of pain fight night 6 : the real deal', '1', '3:38', 'swansea , wales'], ['win', '3 - 0', 'james neal', 'tko ( punches )', 'ultimate force', '1', '3:02', 'south yorkshire , england'], ['win', '2 - 0', 'nigel whitear', 'tko ( punches )', 'fx3 - battle of britain', '1', '0:54', 'england'], ['win', '1 - 0', 'ian mcaleese', 'tko ( punches )', 'cwfc - quest 2', '1', '1:21', 'england']] |
1977 - 78 new york rangers season | https://en.wikipedia.org/wiki/1977%E2%80%9378_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17310913-3.html.csv | unique | the new york ranger played the st louis blues only once in november 1977 . | {'scope': 'all', 'row': '13', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'st louis blues', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'st louis blues'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to st louis blues .', 'tostr': 'filter_eq { all_rows ; opponent ; st louis blues }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; opponent ; st louis blues } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to st louis blues . there is only one such row in the table .'} | only { filter_eq { all_rows ; opponent ; st louis blues } } = true | select the rows whose opponent record fuzzily matches to st louis blues . 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, 'opponent_4': 4, 'st louis blues_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'opponent_4': 'opponent', 'st louis blues_5': 'st louis blues'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'opponent_4': [0], 'st louis blues_5': [0]} | ['game', 'november', 'opponent', 'score', 'record'] | [['11', '2', 'colorado rockies', '6 - 2', '4 - 6 - 1'], ['12', '4', 'vancouver canucks', '5 - 1', '5 - 6 - 1'], ['13', '5', 'los angeles kings', '3 - 1', '5 - 7 - 1'], ['14', '9', 'buffalo sabres', '8 - 4', '6 - 7 - 1'], ['15', '12', 'detroit red wings', '3 - 1', '6 - 8 - 1'], ['16', '13', 'atlanta flames', '5 - 2', '6 - 9 - 1'], ['17', '16', 'chicago black hawks', '5 - 2', '7 - 9 - 1'], ['18', '19', 'pittsburgh penguins', '5 - 5', '7 - 9 - 2'], ['19', '20', 'vancouver canucks', '3 - 0', '7 - 10 - 2'], ['20', '23', 'colorado rockies', '6 - 3', '8 - 10 - 2'], ['21', '26', 'boston bruins', '3 - 2', '8 - 11 - 2'], ['22', '27', 'buffalo sabres', '3 - 2', '8 - 12 - 2'], ['23', '30', 'st louis blues', '4 - 0', '9 - 12 - 2']] |
1979 new orleans saints season | https://en.wikipedia.org/wiki/1979_New_Orleans_Saints_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18842968-2.html.csv | superlative | the highest attendance when the saints played the 49ers was 65551 . | {'scope': 'subset', 'col_superlative': '5', 'row_superlative': '11', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '2,3', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'san francisco 49ers'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'san francisco 49ers'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; san francisco 49ers }', 'tointer': 'select the rows whose opponent record fuzzily matches to san francisco 49ers .'}, 'attendance'], 'result': '65551', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; opponent ; san francisco 49ers } ; attendance }', 'tointer': 'select the rows whose opponent record fuzzily matches to san francisco 49ers . the maximum attendance record of these rows is 65551 .'}, '65551'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; opponent ; san francisco 49ers } ; attendance } ; 65551 }', 'tointer': 'select the rows whose opponent record fuzzily matches to san francisco 49ers . the maximum attendance record of these rows is 65551 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'san francisco 49ers'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; san francisco 49ers }', 'tointer': 'select the rows whose opponent record fuzzily matches to san francisco 49ers .'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'argmax { filter_eq { all_rows ; opponent ; san francisco 49ers } ; attendance }'}, 'date'], 'result': 'november 11 , 1979', 'ind': 4, 'tostr': 'hop { argmax { filter_eq { all_rows ; opponent ; san francisco 49ers } ; attendance } ; date }'}, 'november 11 , 1979'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; opponent ; san francisco 49ers } ; attendance } ; date } ; november 11 , 1979 }', 'tointer': 'the date record of the row with superlative attendance record is november 11 , 1979 .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { max { filter_eq { all_rows ; opponent ; san francisco 49ers } ; attendance } ; 65551 } ; eq { hop { argmax { filter_eq { all_rows ; opponent ; san francisco 49ers } ; attendance } ; date } ; november 11 , 1979 } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to san francisco 49ers . the maximum attendance record of these rows is 65551 . the date record of the row with superlative attendance record is november 11 , 1979 .'} | and { eq { max { filter_eq { all_rows ; opponent ; san francisco 49ers } ; attendance } ; 65551 } ; eq { hop { argmax { filter_eq { all_rows ; opponent ; san francisco 49ers } ; attendance } ; date } ; november 11 , 1979 } } = true | select the rows whose opponent record fuzzily matches to san francisco 49ers . the maximum attendance record of these rows is 65551 . the date record of the row with superlative attendance record is november 11 , 1979 . | 8 | 7 | {'and_6': 6, 'result_7': 7, 'eq_2': 2, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_8': 8, 'opponent_9': 9, 'san francisco 49ers_10': 10, 'attendance_11': 11, '65551_12': 12, 'str_eq_5': 5, 'str_hop_4': 4, 'argmax_3': 3, 'attendance_13': 13, 'date_14': 14, 'november 11 , 1979_15': 15} | {'and_6': 'and', 'result_7': 'true', 'eq_2': 'eq', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_8': 'all_rows', 'opponent_9': 'opponent', 'san francisco 49ers_10': 'san francisco 49ers', 'attendance_11': 'attendance', '65551_12': '65551', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'argmax_3': 'argmax', 'attendance_13': 'attendance', 'date_14': 'date', 'november 11 , 1979_15': 'november 11 , 1979'} | {'and_6': [7], 'result_7': [], 'eq_2': [6], 'max_1': [2], 'filter_str_eq_0': [1, 3], 'all_rows_8': [0], 'opponent_9': [0], 'san francisco 49ers_10': [0], 'attendance_11': [1], '65551_12': [2], 'str_eq_5': [6], 'str_hop_4': [5], 'argmax_3': [4], 'attendance_13': [3], 'date_14': [4], 'november 11 , 1979_15': [5]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 2 , 1979', 'atlanta falcons', 'l 40 - 34', '70940'], ['2', 'september 9 , 1979', 'green bay packers', 'l 28 - 19', '53184'], ['3', 'september 16 , 1979', 'philadelphia eagles', 'l 26 - 14', '54212'], ['4', 'september 23 , 1979', 'san francisco 49ers', 'w 30 - 21', '39727'], ['5', 'september 30 , 1979', 'new york giants', 'w 24 - 14', '51543'], ['6', 'october 7 , 1979', 'los angeles rams', 'l 35 - 17', '68986'], ['7', 'october 14 , 1979', 'tampa bay buccaneers', 'w 42 - 14', '67640'], ['8', 'october 21 , 1979', 'detroit lions', 'w 17 - 7', '57428'], ['9', 'october 28 , 1979', 'washington redskins', 'w 14 - 10', '52133'], ['10', 'november 4 , 1979', 'denver broncos', 'l 10 - 3', '74482'], ['11', 'november 11 , 1979', 'san francisco 49ers', 'w 31 - 20', '65551'], ['12', 'november 18 , 1979', 'seattle seahawks', 'l 38 - 24', '60055'], ['13', 'november 25 , 1979', 'atlanta falcons', 'w 37 - 6', '42815'], ['14', 'december 3 , 1979', 'oakland raiders', 'l 42 - 35', '65541'], ['15', 'december 9 , 1979', 'san diego chargers', 'l 35 - 0', '61059'], ['16', 'december 16 , 1979', 'los angeles rams', 'w 29 - 14', '53879']] |
1984 denver broncos season | https://en.wikipedia.org/wiki/1984_Denver_Broncos_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16729063-2.html.csv | majority | during the 1984 season , denver broncos won all their games in the month of october . | {'scope': 'subset', 'col': '4', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'october'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'result', 'w'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to october . for the result records of these rows , all of them fuzzily match to w .', 'tostr': 'all_eq { filter_eq { all_rows ; date ; october } ; result ; w } = true'} | all_eq { filter_eq { all_rows ; date ; october } ; result ; w } = true | select the rows whose date record fuzzily matches to october . for the result records of these rows , all of them fuzzily match to w . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'october_5': 5, 'result_6': 6, 'w_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'october_5': 'october', 'result_6': 'result', 'w_7': 'w'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'october_5': [0], 'result_6': [1], 'w_7': [1]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 2', 'cincinnati bengals', 'w 20 - 17', 'mile high stadium', '1 - 0', '74178'], ['2', 'september 9', 'chicago bears', 'l 0 - 27', 'soldier field', '1 - 1', '54335'], ['3', 'september 16', 'cleveland browns', 'w 24 - 14', 'cleveland stadium', '2 - 1', '61980'], ['4', 'september 23', 'kansas city chiefs', 'w 21 - 0', 'mile high stadium', '3 - 1', '74263'], ['5', 'september 30', 'los angeles raiders', 'w 16 - 13', 'mile high stadium', '4 - 1', '74833'], ['6', 'october 7', 'detroit lions', 'w 28 - 7', 'pontiac silverdome', '5 - 1', '55836'], ['7', 'october 15', 'green bay packers', 'w 17 - 14', 'mile high stadium', '6 - 1', '62546'], ['8', 'october 21', 'buffalo bills', 'w 37 - 7', 'rich stadium', '7 - 1', '31204'], ['9', 'october 28', 'los angeles raiders', 'w 22 - 19 ( ot )', 'los angeles memorial coliseum', '8 - 1', '91020'], ['10', 'november 4', 'new england patriots', 'w 26 - 19', 'mile high stadium', '9 - 1', '74908'], ['11', 'november 11', 'san diego chargers', 'w 16 - 13', 'jack murphy stadium', '10 - 1', '53162'], ['12', 'november 18', 'minnesota vikings', 'w 42 - 21', 'mile high stadium', '11 - 1', '74716'], ['13', 'november 25', 'seattle seahawks', 'l 24 - 27', 'mile high stadium', '11 - 2', '74922'], ['14', 'december 2', 'kansas city chiefs', 'l 13 - 16', 'arrowhead stadium', '11 - 3', '38494'], ['15', 'december 9', 'san diego chargers', 'w 16 - 13', 'mile high stadium', '12 - 3', '74867']] |
list of interplanetary voyages | https://en.wikipedia.org/wiki/List_of_interplanetary_voyages | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13698001-8.html.csv | ordinal | the shortest journey time of a spacecraft to jupiter was the 547 days of voyager 1 . | {'scope': 'subset', 'row': '15', 'col': '5', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'voyager 1'}} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'spacecraft', 'voyager 1'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; spacecraft ; voyager 1 }', 'tointer': 'select the rows whose spacecraft record fuzzily matches to voyager 1 .'}, 'time elapsed', '1'], 'result': '547 days ( 1 yr , 6 mo , 1 d )', 'ind': 1, 'tostr': 'nth_min { filter_eq { all_rows ; spacecraft ; voyager 1 } ; time elapsed ; 1 }', 'tointer': 'select the rows whose spacecraft record fuzzily matches to voyager 1 . the 1st minimum time elapsed record of these rows is 547 days ( 1 yr , 6 mo , 1 d ) .'}, '547 days ( 1 yr , 6 mo , 1 d )'], 'result': True, 'ind': 2, 'tostr': 'eq { nth_min { filter_eq { all_rows ; spacecraft ; voyager 1 } ; time elapsed ; 1 } ; 547 days ( 1 yr , 6 mo , 1 d ) } = true', 'tointer': 'select the rows whose spacecraft record fuzzily matches to voyager 1 . the 1st minimum time elapsed record of these rows is 547 days ( 1 yr , 6 mo , 1 d ) .'} | eq { nth_min { filter_eq { all_rows ; spacecraft ; voyager 1 } ; time elapsed ; 1 } ; 547 days ( 1 yr , 6 mo , 1 d ) } = true | select the rows whose spacecraft record fuzzily matches to voyager 1 . the 1st minimum time elapsed record of these rows is 547 days ( 1 yr , 6 mo , 1 d ) . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'nth_min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'spacecraft_5': 5, 'voyager 1_6': 6, 'time elapsed_7': 7, '1_8': 8, '547 days (1 yr , 6 mo , 1 d)_9': 9} | {'eq_2': 'eq', 'result_3': 'true', 'nth_min_1': 'nth_min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'spacecraft_5': 'spacecraft', 'voyager 1_6': 'voyager 1', 'time elapsed_7': 'time elapsed', '1_8': '1', '547 days (1 yr , 6 mo , 1 d)_9': '547 days ( 1 yr , 6 mo , 1 d )'} | {'eq_2': [3], 'result_3': [], 'nth_min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'spacecraft_5': [0], 'voyager 1_6': [0], 'time elapsed_7': [1], '1_8': [1], '547 days (1 yr , 6 mo , 1 d)_9': [2]} | ['spacecraft', 'destination', 'launched', 'closest approach', 'time elapsed'] | [['pioneer 10', 'jupiter', '3 march 1972', '3 december 1973', '641 days ( 1 yr , 9 mos , 1 d )'], ['pioneer 11', 'jupiter', '6 april 1973', '4 december 1974', '608 days ( 1 yr , 7 mo , 29 d )'], ['pioneer 11', 'saturn', '6 april 1973', '1 september 1979', '2340 days ( 6 yr , 4 mo , 27 d )'], ['mars 4', 'mars', '21 july 1973', '10 february 1974', '205 days ( 6 months , 21 days )'], ['mars 6', 'mars', '5 august 1973', '12 march 1974', '220 days ( 7 months , 8 days )'], ['mars 7', 'mars', '9 august 1973', '9 march 1974', '213 days ( 7 months , 1 day )'], ['mariner 10', 'venus', '3 november 1973', '5 february 1974', '95 days ( 3 months , 3 days )'], ['mariner 10', 'mercury', '3 november 1973', '29 march 1974', '147 days ( 4 months , 27 days )'], ['mariner 10', 'mercury', '3 november 1973', '21 september 1974', '323 days ( 10 months , 19 days )'], ['mariner 10', 'mercury', '3 november 1973', '16 march 1975', '499 days ( 1 yr , 4 mo , 14 d )'], ['voyager 2', 'jupiter', '20 august 1977', '9 july 1979', '689 days ( 1 yr , 10 mo , 20 d )'], ['voyager 2', 'saturn', '20 august 1977', '5 august 1981', '1447 days ( 3 yr , 11 mo , 17 d )'], ['voyager 2', 'uranus', '20 august 1977', '24 january 1986', '3080 days ( 8 yr , 5 mo , 5 d )'], ['voyager 2', 'neptune', '20 august 1977', '25 august 1989', '4389 days ( 12 yr , 6 days )'], ['voyager 1', 'jupiter', '5 september 1977', '5 march 1979', '547 days ( 1 yr , 6 mo , 1 d )'], ['voyager 1', 'saturn', '5 september 1977', '12 november 1980', '1165 days ( 3 yr , 2 mo , 8 d )'], ['ice', 'comet 21p / giacobini - zinner', '12 august 1978', '11 september 1985', '2588 days ( 7 yr , 1 mo )'], ['ice', 'comet 1p / halley', '12 august 1978', '28 march 1986', '2786 days ( 7 yr , 7 mo , 17 d )'], ['venera 11', 'venus', '9 september 1978', '25 december 1978', '108 days ( 3 months , 17 days )'], ['venera 12', 'venus', '14 september 1978', '19 december 1978', '97 days ( 3 months , 6 days )']] |
fittipaldi automotive | https://en.wikipedia.org/wiki/Fittipaldi_Automotive | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1262596-2.html.csv | unique | 1979 was the only year that alex ribeiro was the driver for fittipaldi automotive . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'alex ribeiro', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver', 'alex ribeiro'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose driver record fuzzily matches to alex ribeiro .', 'tostr': 'filter_eq { all_rows ; driver ; alex ribeiro }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; driver ; alex ribeiro } }', 'tointer': 'select the rows whose driver record fuzzily matches to alex ribeiro . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver', 'alex ribeiro'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose driver record fuzzily matches to alex ribeiro .', 'tostr': 'filter_eq { all_rows ; driver ; alex ribeiro }'}, 'year'], 'result': '1979', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; driver ; alex ribeiro } ; year }'}, '1979'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; driver ; alex ribeiro } ; year } ; 1979 }', 'tointer': 'the year record of this unqiue row is 1979 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; driver ; alex ribeiro } } ; eq { hop { filter_eq { all_rows ; driver ; alex ribeiro } ; year } ; 1979 } } = true', 'tointer': 'select the rows whose driver record fuzzily matches to alex ribeiro . there is only one such row in the table . the year record of this unqiue row is 1979 .'} | and { only { filter_eq { all_rows ; driver ; alex ribeiro } } ; eq { hop { filter_eq { all_rows ; driver ; alex ribeiro } ; year } ; 1979 } } = true | select the rows whose driver record fuzzily matches to alex ribeiro . there is only one such row in the table . the year record of this unqiue row is 1979 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'driver_7': 7, 'alex ribeiro_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1979_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'driver_7': 'driver', 'alex ribeiro_8': 'alex ribeiro', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1979_10': '1979'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'driver_7': [0], 'alex ribeiro_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1979_10': [3]} | ['year', 'event', 'venue', 'driver', 'result'] | [['1975', 'brdc international trophy', 'silverstone', 'wilson fittipaldi', 'ret'], ['1978', 'brdc international trophy', 'silverstone', 'emerson fittipaldi', '2'], ['1979', 'gran premio dino ferrari', 'imola', 'alex ribeiro', 'ret'], ['1980', 'spanish grand prix', 'jarama', 'emerson fittipaldi', '5'], ['1980', 'spanish grand prix', 'jarama', 'keke rosberg', 'ret'], ['1981', 'south african grand prix', 'kyalami', 'keke rosberg', '4'], ['1981', 'south african grand prix', 'kyalami', 'chico serra', '9']] |
list of entertainment events in greater moncton | https://en.wikipedia.org/wiki/List_of_entertainment_events_in_Greater_Moncton | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11758927-2.html.csv | count | four of the events were in the category of arts . | {'scope': 'all', 'criterion': 'equal', 'value': 'arts', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'arts'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to arts .', 'tostr': 'filter_eq { all_rows ; category ; arts }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; category ; arts } }', 'tointer': 'select the rows whose category record fuzzily matches to arts . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; category ; arts } } ; 4 } = true', 'tointer': 'select the rows whose category record fuzzily matches to arts . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; category ; arts } } ; 4 } = true | select the rows whose category record fuzzily matches to arts . 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, 'category_5': 5, 'arts_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', 'category_5': 'category', 'arts_6': 'arts', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'category_5': [0], 'arts_6': [0], '4_7': [2]} | ['event name', 'established', 'category', 'sub category', 'main venue'] | [['dieppe kite international', '2001', 'sporting', 'kite flying', 'dover park'], ['the frye festival', '2000', 'arts', 'literary', 'university of moncton'], ['hubcap comedy festival', '2000', 'arts', 'comedy', 'various'], ['touchdown atlantic', '2010', 'sporting', 'football', 'moncton stadium'], ['atlantic nationals automotive extravaganza', '2000', 'transportation', 'automotive', 'moncton coliseum'], ['world wine & food expo', '1990', 'arts', 'food & drink', 'moncton coliseum'], ['shediac lobster festival', '1950', 'arts', 'food & drink', 'shediac festival grounds'], ['mosaã ¯ q multicultural festival', '2004', 'festival', 'multicultural', 'moncton city hall plaza']] |
satpura thermal power station | https://en.wikipedia.org/wiki/Satpura_Thermal_Power_Station | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28672269-1.html.csv | majority | all units at the satpura thermal power station have a status of running . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'running', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'status', 'running'], 'result': True, 'ind': 0, 'tointer': 'for the status records of all rows , all of them fuzzily match to running .', 'tostr': 'all_eq { all_rows ; status ; running } = true'} | all_eq { all_rows ; status ; running } = true | for the status records of all rows , all of them fuzzily match to running . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'status_3': 3, 'running_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'status_3': 'status', 'running_4': 'running'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'status_3': [0], 'running_4': [0]} | ['stage', 'unit number', 'installed capacity ( mw )', 'date of commissioning', 'status', 'tg set provider', 'boiler provider'] | [['first', '1', '62.5', 'october , 1967', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['first', '2', '62.5', 'march , 1968', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['first', '3', '62.5', 'may , 1968', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['first', '4', '62.5', 'july , 1968', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['first', '5', '62.5', 'april , 1970', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['second', '6', '200', 'july , 1979', 'running', 'bhel , india', 'bhel , india'], ['second', '7', '210', 'september , 1980', 'running', 'bhel , india', 'bhel , india'], ['second', '8', '210', 'january , 1983', 'running', 'bhel , india', 'bhel , india']] |
2008 iaaf world indoor championships - women 's 60 metres | https://en.wikipedia.org/wiki/2008_IAAF_World_Indoor_Championships_%E2%80%93_Women%27s_60_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16652101-4.html.csv | aggregation | the average reaction time in the women 's 2008 iaaf indoor world championships 60m is 0.161 seconds . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '0.161', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'react'], 'result': '0.161', 'ind': 0, 'tostr': 'avg { all_rows ; react }'}, '0.161'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; react } ; 0.161 } = true', 'tointer': 'the average of the react record of all rows is 0.161 .'} | round_eq { avg { all_rows ; react } ; 0.161 } = true | the average of the react record of all rows is 0.161 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'react_4': 4, '0.161_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'react_4': 'react', '0.161_5': '0.161'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'react_4': [0], '0.161_5': [1]} | ['lane', 'name', 'country', 'mark', 'react'] | [['6', 'angela williams', 'united states', '7.06 wl', '0.142'], ['5', 'jeanette kwakye', 'united kingdom', '7.08 nr', '0.163'], ['3', 'tahesia harrigan', 'british virgin islands', '7.09 nr', '0.149'], ['1', 'kim gevaert', 'belgium', '7.22', '0.149'], ['7', 'yevgeniya polyakova', 'russia', '7.24', '0.156'], ['8', 'oludamola osayomi', 'nigeria', '7.26', '0.169'], ['4', 'ene franca idoko', 'nigeria', '7.30', '0.132'], ['2', 'alexis joyce', 'united states', '7.37', '0.229']] |
2006 - 07 isu junior grand prix | https://en.wikipedia.org/wiki/2006%E2%80%9307_ISU_Junior_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12392804-3.html.csv | majority | all of the teams at the 2006 - 07 isu junior grand prix won at least one medal . | {'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': '1', 'subset': None} | {'func': 'all_greater_eq', 'args': ['all_rows', 'total', '1'], 'result': True, 'ind': 0, 'tointer': 'for the total records of all rows , all of them are greater than or equal to 1 .', 'tostr': 'all_greater_eq { all_rows ; total ; 1 } = true'} | all_greater_eq { all_rows ; total ; 1 } = true | for the total records of all rows , all of them are greater than or equal to 1 . | 1 | 1 | {'all_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'total_3': 3, '1_4': 4} | {'all_greater_eq_0': 'all_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'total_3': 'total', '1_4': '1'} | {'all_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'total_3': [0], '1_4': [0]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'united states', '24', '12', '8', '44'], ['2', 'russia', '5', '5', '6', '16'], ['3', 'canada', '1', '2', '7', '10'], ['4', 'japan', '1', '4', '3', '8'], ['5', 'estonia', '1', '2', '1', '4'], ['5', 'italy', '0', '3', '1', '4'], ['6', 'south korea', '0', '0', '3', '3'], ['7', 'france', '0', '1', '1', '2'], ['7', 'ukraine', '0', '1', '1', '2'], ['8', 'spain', '0', '1', '0', '1'], ['8', 'china', '0', '1', '0', '1'], ['8', 'czech republic', '0', '0', '1', '1']] |
scottish parliament general election , 2007 | https://en.wikipedia.org/wiki/Scottish_Parliament_general_election%2C_2007 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11105214-1.html.csv | superlative | the dundee east constituency had the smallest swing to gain during the scottish parliament general election of 2007 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'swing to gain'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; swing to gain }'}, 'constituency'], 'result': 'dundee east', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; swing to gain } ; constituency }'}, 'dundee east'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; swing to gain } ; constituency } ; dundee east } = true', 'tointer': 'select the row whose swing to gain record of all rows is minimum . the constituency record of this row is dundee east .'} | eq { hop { argmin { all_rows ; swing to gain } ; constituency } ; dundee east } = true | select the row whose swing to gain record of all rows is minimum . the constituency record of this row is dundee east . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'swing to gain_5': 5, 'constituency_6': 6, 'dundee east_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'swing to gain_5': 'swing to gain', 'constituency_6': 'constituency', 'dundee east_7': 'dundee east'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'swing to gain_5': [0], 'constituency_6': [1], 'dundee east_7': [2]} | ['rank', 'constituency', 'winning party 2003', 'swing to gain', "labour 's place 2003", 'result'] | [['1', 'dundee east', 'snp', '0.17', '2nd', 'snp hold'], ['2', 'edinburgh south', 'liberal democrats', '0.26', '2nd', 'ld hold'], ['3', 'ochil', 'snp', '0.49', '2nd', 'snp hold'], ['4', 'strathkelvin and bearsden', 'independent', '0.62', '2nd', 'lab gain'], ['5', 'aberdeen north', 'snp', '0.92', '2nd', 'snp hold'], ['6', 'inverness east , nairn and lochaber', 'snp', '1.51', '2nd', 'snp hold'], ['7', 'tweeddale , ettrick and lauderdale', 'liberal democrats', '2.70', '3rd', 'ld hold'], ['8', 'ayr', 'conservative', '2.99', '2nd', 'con hold'], ['9', 'edinburgh pentlands', 'conservative', '3.16', '2nd', 'con hold'], ['10', 'caithness , sutherland and easter ross', 'liberal democrats', '4.96', '2nd', 'ld hold']] |
sidecarcross world championship | https://en.wikipedia.org/wiki/Sidecarcross_World_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16729457-16.html.csv | comparative | jan hendrickx / tim smeuninx scored a higher number of points than marko happich / meinrad schelbert . | {'row_1': '3', 'row_2': '8', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver / passenger', 'jan hendrickx / tim smeuninx'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose driver / passenger record fuzzily matches to jan hendrickx / tim smeuninx .', 'tostr': 'filter_eq { all_rows ; driver / passenger ; jan hendrickx / tim smeuninx }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; driver / passenger ; jan hendrickx / tim smeuninx } ; points }', 'tointer': 'select the rows whose driver / passenger record fuzzily matches to jan hendrickx / tim smeuninx . take the points record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver / passenger', 'marko happich / meinrad schelbert'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose driver / passenger record fuzzily matches to marko happich / meinrad schelbert .', 'tostr': 'filter_eq { all_rows ; driver / passenger ; marko happich / meinrad schelbert }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; driver / passenger ; marko happich / meinrad schelbert } ; points }', 'tointer': 'select the rows whose driver / passenger record fuzzily matches to marko happich / meinrad schelbert . take the points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; driver / passenger ; jan hendrickx / tim smeuninx } ; points } ; hop { filter_eq { all_rows ; driver / passenger ; marko happich / meinrad schelbert } ; points } }', 'tointer': 'select the rows whose driver / passenger record fuzzily matches to jan hendrickx / tim smeuninx . take the points record of this row . select the rows whose driver / passenger record fuzzily matches to marko happich / meinrad schelbert . take the points record of this row . the first record is greater than the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver / passenger', 'jan hendrickx / tim smeuninx'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose driver / passenger record fuzzily matches to jan hendrickx / tim smeuninx .', 'tostr': 'filter_eq { all_rows ; driver / passenger ; jan hendrickx / tim smeuninx }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; driver / passenger ; jan hendrickx / tim smeuninx } ; points }', 'tointer': 'select the rows whose driver / passenger record fuzzily matches to jan hendrickx / tim smeuninx . take the points record of this row .'}, '405'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; driver / passenger ; jan hendrickx / tim smeuninx } ; points } ; 405 }', 'tointer': 'the points record of the first row is 405 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver / passenger', 'marko happich / meinrad schelbert'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose driver / passenger record fuzzily matches to marko happich / meinrad schelbert .', 'tostr': 'filter_eq { all_rows ; driver / passenger ; marko happich / meinrad schelbert }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; driver / passenger ; marko happich / meinrad schelbert } ; points }', 'tointer': 'select the rows whose driver / passenger record fuzzily matches to marko happich / meinrad schelbert . take the points record of this row .'}, '317'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; driver / passenger ; marko happich / meinrad schelbert } ; points } ; 317 }', 'tointer': 'the points record of the second row is 317 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; driver / passenger ; jan hendrickx / tim smeuninx } ; points } ; 405 } ; eq { hop { filter_eq { all_rows ; driver / passenger ; marko happich / meinrad schelbert } ; points } ; 317 } }', 'tointer': 'the points record of the first row is 405 . the points record of the second row is 317 .'}], 'result': True, 'ind': 8, 'tostr': 'and { greater { hop { filter_eq { all_rows ; driver / passenger ; jan hendrickx / tim smeuninx } ; points } ; hop { filter_eq { all_rows ; driver / passenger ; marko happich / meinrad schelbert } ; points } } ; and { eq { hop { filter_eq { all_rows ; driver / passenger ; jan hendrickx / tim smeuninx } ; points } ; 405 } ; eq { hop { filter_eq { all_rows ; driver / passenger ; marko happich / meinrad schelbert } ; points } ; 317 } } } = true', 'tointer': 'select the rows whose driver / passenger record fuzzily matches to jan hendrickx / tim smeuninx . take the points record of this row . select the rows whose driver / passenger record fuzzily matches to marko happich / meinrad schelbert . take the points record of this row . the first record is greater than the second record . the points record of the first row is 405 . the points record of the second row is 317 .'} | and { greater { hop { filter_eq { all_rows ; driver / passenger ; jan hendrickx / tim smeuninx } ; points } ; hop { filter_eq { all_rows ; driver / passenger ; marko happich / meinrad schelbert } ; points } } ; and { eq { hop { filter_eq { all_rows ; driver / passenger ; jan hendrickx / tim smeuninx } ; points } ; 405 } ; eq { hop { filter_eq { all_rows ; driver / passenger ; marko happich / meinrad schelbert } ; points } ; 317 } } } = true | select the rows whose driver / passenger record fuzzily matches to jan hendrickx / tim smeuninx . take the points record of this row . select the rows whose driver / passenger record fuzzily matches to marko happich / meinrad schelbert . take the points record of this row . the first record is greater than the second record . the points record of the first row is 405 . the points record of the second row is 317 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'greater_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'driver / passenger_11': 11, 'jan hendrickx / tim smeuninx_12': 12, 'points_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'driver / passenger_15': 15, 'marko happich / meinrad schelbert_16': 16, 'points_17': 17, 'and_7': 7, 'eq_5': 5, '405_18': 18, 'eq_6': 6, '317_19': 19} | {'and_8': 'and', 'result_9': 'true', 'greater_4': 'greater', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'driver / passenger_11': 'driver / passenger', 'jan hendrickx / tim smeuninx_12': 'jan hendrickx / tim smeuninx', 'points_13': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'driver / passenger_15': 'driver / passenger', 'marko happich / meinrad schelbert_16': 'marko happich / meinrad schelbert', 'points_17': 'points', 'and_7': 'and', 'eq_5': 'eq', '405_18': '405', 'eq_6': 'eq', '317_19': '317'} | {'and_8': [9], 'result_9': [], 'greater_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'driver / passenger_11': [0], 'jan hendrickx / tim smeuninx_12': [0], 'points_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'driver / passenger_15': [1], 'marko happich / meinrad schelbert_16': [1], 'points_17': [3], 'and_7': [8], 'eq_5': [7], '405_18': [5], 'eq_6': [7], '317_19': [6]} | ['position', 'driver / passenger', 'equipment', 'bike no', 'points'] | [['1', 'daniãl willemsen / sven verbrugge 1', 'zabel - wsp', '1', '487'], ['2', 'janis daiders / lauris daiders', 'zabel - vmc', '8', '478'], ['3', 'jan hendrickx / tim smeuninx', 'zabel - vmc', '3', '405'], ['4', 'maris rupeiks / kaspars stupelis 2', 'zabel - wsp', '5', '349'], ['5', 'etienne bax / ben van den bogaart', 'zabel - vmc', '4', '347'], ['6', 'ben adriaenssen / guennady auvray', 'ktm - vmc', '6', '346'], ['7', 'ewgeny scherbinin / haralds kurpnieks', 'zabel - wsp', '20', '321'], ['8', 'marko happich / meinrad schelbert', 'zabel - vmc', '15', '317'], ['9', 'joris hendrickx / kaspars liepins', 'ktm - vmc', '2', '315']] |
2008 - 09 süper lig | https://en.wikipedia.org/wiki/2008%E2%80%9309_S%C3%BCper_Lig | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17356873-2.html.csv | comparative | in the süper lig , the date of mesut bakkal 's vacancy was one day before samet aybaba 's vacancy . | {'row_1': '8', 'row_2': '9', 'col': '4', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1 day', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'outgoing manager', 'mesut bakkal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose outgoing manager record fuzzily matches to mesut bakkal .', 'tostr': 'filter_eq { all_rows ; outgoing manager ; mesut bakkal }'}, 'date of vacancy'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; outgoing manager ; mesut bakkal } ; date of vacancy }', 'tointer': 'select the rows whose outgoing manager record fuzzily matches to mesut bakkal . take the date of vacancy record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'outgoing manager', 'samet aybaba'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose outgoing manager record fuzzily matches to samet aybaba .', 'tostr': 'filter_eq { all_rows ; outgoing manager ; samet aybaba }'}, 'date of vacancy'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; outgoing manager ; samet aybaba } ; date of vacancy }', 'tointer': 'select the rows whose outgoing manager record fuzzily matches to samet aybaba . take the date of vacancy record of this row .'}], 'result': '-1 day', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; outgoing manager ; mesut bakkal } ; date of vacancy } ; hop { filter_eq { all_rows ; outgoing manager ; samet aybaba } ; date of vacancy } }'}, '-1 day'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; outgoing manager ; mesut bakkal } ; date of vacancy } ; hop { filter_eq { all_rows ; outgoing manager ; samet aybaba } ; date of vacancy } } ; -1 day } = true', 'tointer': 'select the rows whose outgoing manager record fuzzily matches to mesut bakkal . take the date of vacancy record of this row . select the rows whose outgoing manager record fuzzily matches to samet aybaba . take the date of vacancy record of this row . the second record is 1 day larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; outgoing manager ; mesut bakkal } ; date of vacancy } ; hop { filter_eq { all_rows ; outgoing manager ; samet aybaba } ; date of vacancy } } ; -1 day } = true | select the rows whose outgoing manager record fuzzily matches to mesut bakkal . take the date of vacancy record of this row . select the rows whose outgoing manager record fuzzily matches to samet aybaba . take the date of vacancy record of this row . the second record is 1 day larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'outgoing manager_8': 8, 'mesut bakkal_9': 9, 'date of vacancy_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'outgoing manager_12': 12, 'samet aybaba_13': 13, 'date of vacancy_14': 14, '-1 day_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'outgoing manager_8': 'outgoing manager', 'mesut bakkal_9': 'mesut bakkal', 'date of vacancy_10': 'date of vacancy', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'outgoing manager_12': 'outgoing manager', 'samet aybaba_13': 'samet aybaba', 'date of vacancy_14': 'date of vacancy', '-1 day_15': '-1 day'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'outgoing manager_8': [0], 'mesut bakkal_9': [0], 'date of vacancy_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'outgoing manager_12': [1], 'samet aybaba_13': [1], 'date of vacancy_14': [3], '-1 day_15': [5]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment'] | [['konyaspor', 'raşit çetiner', 'sacked', '17 september 2008', 'giray bulak', '24 september 2008'], ['kocaelispor', 'engin ipekoğlu', 'sacked', '25 september 2008', 'yılmaz vural', '28 september 2008'], ['beşiktaş', 'ertuğrul sağlam', 'resigned', '7 october 2008', 'mustafa denizli', '9 october 2008'], ['ankaragücü', 'hakan kutlu', 'sacked', '20 october 2008', 'ünal karaman', '24 october 2008'], ['antalyaspor', 'jozef jarabinský', 'sacked', '28 october 2008', 'mehmet özdilek', '28 october 2008'], ['hacettepe', 'osman özdemir', 'resigned', '2 november 2008', 'erdoğan arıca', '3 november 2008'], ['denizlispor', 'ali yalçın', 'resigned', '2 november 2008', 'ümit kayıhan', '10 november 2008'], ['gençlerbirliği', 'mesut bakkal', 'resigned', '3 november 2008', 'samet aybaba', '5 november 2008'], ['bursaspor', 'samet aybaba', 'resigned', '4 november 2008', 'güvenç kurtar', '4 november 2008'], ['ankaragücü', 'ünal karaman', 'resigned', '8 december 2008', 'hakan kutlu', '2 january 2009'], ['bursaspor', 'güvenç kurtar', 'resigned', '23 december 2008', 'ertuğrul sağlam', '2 january 2009'], ['kocaelispor', 'yılmaz vural', 'resigned', '29 december 2008', 'erhan altın', '17 january 2009'], ['denizlispor', 'ümit kayıhan', 'sacked', '5 february 2009', 'mesut bakkal', '6 february 2009'], ['galatasaray', 'michael skibbe', 'sacked', '23 february 2009', 'bülent korkmaz', '23 february 2009'], ['hacettepe', 'erdoğan arıca', 'resigned', '2 march 2009', 'ergün penbe', '2 march 2009'], ['gaziantepspor', 'nurullah sağlam', 'resigned', '9 march 2009', 'josé couceiro', '6 april 2009'], ['konyaspor', 'giray bulak', 'sacked', '19 may 2009', 'ünal karaman', '20 may 2009']] |
10k run | https://en.wikipedia.org/wiki/10K_run | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17370134-2.html.csv | comparative | peter kamais lotagor raced his top-10 time in the 10k run record before moses ndiema masai did . | {'row_1': '6', 'row_2': '9', 'col': '2', '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', 'athlete', 'peter kamais lotagor'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose athlete record fuzzily matches to peter kamais lotagor .', 'tostr': 'filter_eq { all_rows ; athlete ; peter kamais lotagor }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; athlete ; peter kamais lotagor } ; time }', 'tointer': 'select the rows whose athlete record fuzzily matches to peter kamais lotagor . take the time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'athlete', 'moses ndiema masai'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose athlete record fuzzily matches to moses ndiema masai .', 'tostr': 'filter_eq { all_rows ; athlete ; moses ndiema masai }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; athlete ; moses ndiema masai } ; time }', 'tointer': 'select the rows whose athlete record fuzzily matches to moses ndiema masai . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; athlete ; peter kamais lotagor } ; time } ; hop { filter_eq { all_rows ; athlete ; moses ndiema masai } ; time } } = true', 'tointer': 'select the rows whose athlete record fuzzily matches to peter kamais lotagor . take the time record of this row . select the rows whose athlete record fuzzily matches to moses ndiema masai . take the time record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; athlete ; peter kamais lotagor } ; time } ; hop { filter_eq { all_rows ; athlete ; moses ndiema masai } ; time } } = true | select the rows whose athlete record fuzzily matches to peter kamais lotagor . take the time record of this row . select the rows whose athlete record fuzzily matches to moses ndiema masai . take the time 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, 'athlete_7': 7, 'peter kamais lotagor_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'athlete_11': 11, 'moses ndiema masai_12': 12, 'time_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', 'athlete_7': 'athlete', 'peter kamais lotagor_8': 'peter kamais lotagor', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'athlete_11': 'athlete', 'moses ndiema masai_12': 'moses ndiema masai', 'time_13': 'time'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'athlete_7': [0], 'peter kamais lotagor_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'athlete_11': [1], 'moses ndiema masai_12': [1], 'time_13': [3]} | ['rank', 'time', 'athlete', 'nation', 'date', 'race'] | [['1', '26:44', 'leonard patrick komon', 'kenya', '26 september 2010', 'singelloop utrecht'], ['2', '27:01', 'micah kipkemboi kogo', 'kenya', '29 march 2009', 'parelloop brunssum'], ['3', '27:02', 'haile gebrselassie', 'ethiopia', '11 december 2002', 'doha , qatar'], ['4 =', '27:04', 'joseph kimani', 'kenya', '4 july 1996', 'peachtree road race'], ['4 =', '27:04', 'josphat kiprono menjo', 'kenya', '18 april 2010', 'cursa de bombers'], ['6', '27:09', 'peter kamais lotagor', 'kenya', '6 september 2009', 'tilburg 10k'], ['7 =', '27:11', 'sammy kipketer', 'kenya', '30 march 2002', 'crescent city classic'], ['7 =', '27:11', 'sammy kirop kitwara', 'kenya', '26 september 2010', 'singelloop utrecht'], ['9 =', '27:19', 'moses ndiema masai', 'kenya', '28 february 2010', "world 's best 10k"], ['9 =', '27:19', 'geoffrey kiprono mutai', 'kenya', '26 june 2011', 'boston 10k']] |
1972 vfl season | https://en.wikipedia.org/wiki/1972_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826385-13.html.csv | count | in the 1972 vfl season , among the games where home team scored below 15.00 , 3 of them had attendance over 15000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '15000', 'result': '3', 'col': '6', 'subset': {'col': '2', 'criterion': 'less_than', 'value': '15'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'home team score', '15'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; home team score ; 15 }', 'tointer': 'select the rows whose home team score record is less than 15 .'}, 'crowd', '15000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team score record is less than 15 . among these rows , select the rows whose crowd record is greater than 15000 .', 'tostr': 'filter_greater { filter_less { all_rows ; home team score ; 15 } ; crowd ; 15000 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_greater { filter_less { all_rows ; home team score ; 15 } ; crowd ; 15000 } }', 'tointer': 'select the rows whose home team score record is less than 15 . among these rows , select the rows whose crowd record is greater than 15000 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_less { all_rows ; home team score ; 15 } ; crowd ; 15000 } } ; 3 } = true', 'tointer': 'select the rows whose home team score record is less than 15 . among these rows , select the rows whose crowd record is greater than 15000 . the number of such rows is 3 .'} | eq { count { filter_greater { filter_less { all_rows ; home team score ; 15 } ; crowd ; 15000 } } ; 3 } = true | select the rows whose home team score record is less than 15 . among these rows , select the rows whose crowd record is greater than 15000 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'home team score_6': 6, '15_7': 7, 'crowd_8': 8, '15000_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'home team score_6': 'home team score', '15_7': '15', 'crowd_8': 'crowd', '15000_9': '15000', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'home team score_6': [0], '15_7': [0], 'crowd_8': [1], '15000_9': [1], '3_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '21.14 ( 140 )', 'north melbourne', '10.16 ( 76 )', 'glenferrie oval', '8201', '1 july 1972'], ['carlton', '10.10 ( 70 )', 'collingwood', '9.8 ( 62 )', 'princes park', '36133', '1 july 1972'], ['richmond', '14.8 ( 92 )', 'geelong', '25.18 ( 168 )', 'mcg', '22595', '1 july 1972'], ['st kilda', '13.10 ( 88 )', 'fitzroy', '6.17 ( 53 )', 'moorabbin oval', '18355', '1 july 1972'], ['south melbourne', '12.12 ( 84 )', 'essendon', '13.9 ( 87 )', 'lake oval', '12984', '1 july 1972'], ['melbourne', '16.15 ( 111 )', 'footscray', '11.8 ( 74 )', 'vfl park', '14180', '1 july 1972']] |
1999 indianapolis colts season | https://en.wikipedia.org/wiki/1999_Indianapolis_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14901683-1.html.csv | ordinal | in the 1999 indianapolis colts season , in their fourth game at the rca dome , the attendance was 56860 . | {'scope': 'subset', 'row': '8', 'col': '2', 'order': '4', 'col_other': '8', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'rca dome'}} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'rca dome'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; game site ; rca dome }', 'tointer': 'select the rows whose game site record fuzzily matches to rca dome .'}, 'date', '4'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; game site ; rca dome } ; date ; 4 }'}, 'attendance'], 'result': '56860', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; game site ; rca dome } ; date ; 4 } ; attendance }'}, '56860'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; game site ; rca dome } ; date ; 4 } ; attendance } ; 56860 } = true', 'tointer': 'select the rows whose game site record fuzzily matches to rca dome . select the row whose date record of these rows is 4th minimum . the attendance record of this row is 56860 .'} | eq { hop { nth_argmin { filter_eq { all_rows ; game site ; rca dome } ; date ; 4 } ; attendance } ; 56860 } = true | select the rows whose game site record fuzzily matches to rca dome . select the row whose date record of these rows is 4th minimum . the attendance record of this row is 56860 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'num_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'game site_6': 6, 'rca dome_7': 7, 'date_8': 8, '4_9': 9, 'attendance_10': 10, '56860_11': 11} | {'eq_3': 'eq', 'result_4': 'true', 'num_hop_2': 'num_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'game site_6': 'game site', 'rca dome_7': 'rca dome', 'date_8': 'date', '4_9': '4', 'attendance_10': 'attendance', '56860_11': '56860'} | {'eq_3': [4], 'result_4': [], 'num_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'game site_6': [0], 'rca dome_7': [0], 'date_8': [1], '4_9': [1], 'attendance_10': [2], '56860_11': [3]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'tv time', 'attendance'] | [['1', 'september 12 , 1999', 'buffalo bills', 'w 31 - 14', '1 - 0', 'rca dome', 'cbs 1:00 pm', '56238'], ['2', 'september 19 , 1999', 'new england patriots', 'l 28 - 31', '1 - 1', 'foxboro stadium', 'cbs 1:00 pm', '59640'], ['3', 'september 26 , 1999', 'san diego chargers', 'w 27 - 19', '2 - 1', 'qualcomm stadium', 'cbs 4:15 pm', '56942'], ['4', '-', '-', '-', '-', '-', '-', ''], ['5', 'october 10 , 1999', 'miami dolphins', 'l 31 - 34', '2 - 2', 'rca dome', 'cbs 1:00 pm', '56810'], ['6', 'october 17 , 1999', 'new york jets', 'w 16 - 13', '3 - 2', 'the meadowlands', 'cbs 1:00 pm', '78112'], ['7', 'october 24 , 1999', 'cincinnati bengals', 'w 31 - 10', '4 - 2', 'rca dome', 'cbs 1:00 pm', '55996'], ['8', 'october 31 , 1999', 'dallas cowboys', 'w 34 - 24', '5 - 2', 'rca dome', 'fox 4:15 pm', '56860'], ['9', 'november 7 , 1999', 'kansas city chiefs', 'w 25 - 17', '6 - 2', 'rca dome', 'cbs 1:00 pm', '56689'], ['10', 'november 14 , 1999', 'new york giants', 'w 27 - 19', '7 - 2', 'giants stadium', 'cbs 1:00 pm', '78081'], ['11', 'november 21 , 1999', 'philadelphia eagles', 'w 44 - 17', '8 - 2', 'veterans stadium', 'cbs 1:00 pm', '65521'], ['12', 'november 28 , 1999', 'new york jets', 'w 13 - 6', '9 - 2', 'rca dome', 'cbs 4:15 pm', '56689'], ['13', 'december 5 , 1999', 'miami dolphins', 'w 37 - 34', '10 - 2', 'pro player stadium', 'cbs 1:00 pm', '74096'], ['14', 'december 12 , 1999', 'new england patriots', 'w 20 - 15', '11 - 2', 'rca dome', 'cbs 1:00 pm', '56975'], ['15', 'december 19 , 1999', 'washington redskins', 'w 24 - 21', '12 - 2', 'rca dome', 'fox 1:00 pm', '57013'], ['16', 'december 26 , 1999', 'cleveland browns', 'w 29 - 28', '13 - 2', 'cleveland browns stadium', 'cbs 1:00 pm', '72618'], ['17', 'january 2 , 2000', 'buffalo bills', 'l 6 - 31', '13 - 3', 'ralph wilson stadium', 'cbs 1:00 pm', '61959']] |
rowing at the 2008 summer olympics - men 's double sculls | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_double_sculls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662686-3.html.csv | majority | in the rowing competition at the 2008 summer olympics - men 's double sculls , most completed the competition in under 7:00:00 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '7:00:00', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'time', '7:00:00'], 'result': True, 'ind': 0, 'tointer': 'for the time records of all rows , most of them are less than 7:00:00 .', 'tostr': 'most_less { all_rows ; time ; 7:00:00 } = true'} | most_less { all_rows ; time ; 7:00:00 } = true | for the time records of all rows , most of them are less than 7:00:00 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'time_3': 3, '7:00:00_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'time_3': 'time', '7:00:00_4': '7:00:00'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'time_3': [0], '7:00:00_4': [0]} | ['rank', 'rowers', 'country', 'time', 'notes'] | [['1', 'matthew wells , stephen rowbotham', 'great britain', '6:26.33', 'sa / b'], ['2', 'ante kušurin , mario vekić', 'croatia', '6:27.38', 'sa / b'], ['3', 'tõnu endrekson , jüri jaanson', 'estonia', '6:27.95', 'sa / b'], ['4', 'alexander kornilov , alexey svirin', 'russia', '6:44.46', 'r'], ['5', 'haidar nozad , hussein jebur', 'iraq', '7:00:46', 'r']] |
mahmoud amnah | https://en.wikipedia.org/wiki/Mahmoud_Amnah | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12881471-3.html.csv | unique | mahmoud amnah 's competition on january 26 , 2005 , is the only one to take place in kuwait . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'kuwait', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'kuwait'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to kuwait .', 'tostr': 'filter_eq { all_rows ; venue ; kuwait }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; kuwait } }', 'tointer': 'select the rows whose venue record fuzzily matches to kuwait . 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', 'kuwait'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to kuwait .', 'tostr': 'filter_eq { all_rows ; venue ; kuwait }'}, 'date'], 'result': '26 jan 2005', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; kuwait } ; date }'}, '26 jan 2005'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; kuwait } ; date } ; 26 jan 2005 }', 'tointer': 'the date record of this unqiue row is 26 jan 2005 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; venue ; kuwait } } ; eq { hop { filter_eq { all_rows ; venue ; kuwait } ; date } ; 26 jan 2005 } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to kuwait . there is only one such row in the table . the date record of this unqiue row is 26 jan 2005 .'} | and { only { filter_eq { all_rows ; venue ; kuwait } } ; eq { hop { filter_eq { all_rows ; venue ; kuwait } ; date } ; 26 jan 2005 } } = true | select the rows whose venue record fuzzily matches to kuwait . there is only one such row in the table . the date record of this unqiue row is 26 jan 2005 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'kuwait_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '26 jan 2005_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', 'kuwait_8': 'kuwait', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '26 jan 2005_10': '26 jan 2005'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'kuwait_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '26 jan 2005_10': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['08 oct 2004', 'doha , qatar', '1 - 0', '2 - 1', 'international friendly'], ['26 jan 2005', 'kuwait city , kuwait', '1 - 1', '2 - 3', 'international friendly'], ['04 dec 2005', 'al - gharafa stadium , doha , qatar', '1 - 0', '2 - 2', 'west asian games 2005'], ['10 dec 2005', 'qatar sc stadium , doha , qatar', '1 - 0', '2 - 2', 'west asian games 2005'], ['17 may 2008', 'abbasiyyin stadium , damascus , syria', '1 - 0', '2 - 1', 'international friendly']] |
ryan briscoe | https://en.wikipedia.org/wiki/Ryan_Briscoe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1390721-8.html.csv | count | ryan briscoe drove a total of five times for team penske . | {'scope': 'all', 'criterion': 'equal', 'value': 'team penske', 'result': '5', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'team penske'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to team penske .', 'tostr': 'filter_eq { all_rows ; team ; team penske }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; team ; team penske } }', 'tointer': 'select the rows whose team record fuzzily matches to team penske . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; team ; team penske } } ; 5 } = true', 'tointer': 'select the rows whose team record fuzzily matches to team penske . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; team ; team penske } } ; 5 } = true | select the rows whose team record fuzzily matches to team penske . 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, 'team_5': 5, 'team penske_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', 'team_5': 'team', 'team penske_6': 'team penske', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'team penske_6': [0], '5_7': [2]} | ['year', 'chassis', 'engine', 'start', 'finish', 'team'] | [['2005', 'panoz', 'toyota', '24', '10', 'chip ganassi racing'], ['2007', 'dallara', 'honda', '7', '5', 'luczo - dragon racing'], ['2008', 'dallara', 'honda', '3', '23', 'team penske'], ['2009', 'dallara', 'honda', '2', '15', 'team penske'], ['2010', 'dallara', 'honda', '4', '24', 'team penske'], ['2011', 'dallara', 'honda', '26', '27', 'team penske'], ['2012', 'dallara', 'chevrolet', '1', '5', 'team penske'], ['2013', 'dallara', 'honda', '23', '12', 'chip ganassi racing']] |
list of high schools in indiana | https://en.wikipedia.org/wiki/List_of_high_schools_in_Indiana | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1984697-85.html.csv | count | five of the listed high schools in indiana are in the town of wabash . | {'scope': 'all', 'criterion': 'equal', 'value': 'wabash', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city / town', 'wabash'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city / town record fuzzily matches to wabash .', 'tostr': 'filter_eq { all_rows ; city / town ; wabash }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; city / town ; wabash } }', 'tointer': 'select the rows whose city / town record fuzzily matches to wabash . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; city / town ; wabash } } ; 4 } = true', 'tointer': 'select the rows whose city / town record fuzzily matches to wabash . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; city / town ; wabash } } ; 4 } = true | select the rows whose city / town record fuzzily matches to wabash . 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, 'city / town_5': 5, 'wabash_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', 'city / town_5': 'city / town', 'wabash_6': 'wabash', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'city / town_5': [0], 'wabash_6': [0], '4_7': [2]} | ['school', 'city / town', 'website', 'size', 'principal', 'grades', 'idoe profile'] | [['emmanuel christian school', 'wabash', '-', '105', 'doug phillips', 'pk - 12', 'snapshot'], ['manchester junior - senior high school', 'north manchester', 'website', '715', 'ms nancy alspaugh', '07 - 12', 'snapshot'], ['northfield junior - senior high school', 'wabash', 'website', '604', 'mike keaffaber', '07 - 12', 'snapshot'], ['southwood junior - senior high school', 'wabash', 'website', '634', 'tim drake', '07 - 12', 'snapshot'], ['wabash high school', 'wabash', 'website', '462', 'josh blossom', '09 - 12', 'snapshot']] |
1975 oakland raiders season | https://en.wikipedia.org/wiki/1975_Oakland_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18207285-2.html.csv | aggregation | the average points scored by the raiders in 1975 was around 25-30 points . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '26.79', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'raiders points'], 'result': '26.79', 'ind': 0, 'tostr': 'avg { all_rows ; raiders points }'}, '26.79'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; raiders points } ; 26.79 } = true', 'tointer': 'the average of the raiders points record of all rows is 26.79 .'} | round_eq { avg { all_rows ; raiders points } ; 26.79 } = true | the average of the raiders points record of all rows is 26.79 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'raiders points_4': 4, '26.79_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'raiders points_4': 'raiders points', '26.79_5': '26.79'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'raiders points_4': [0], '26.79_5': [1]} | ['game', 'date', 'opponent', 'result', 'raiders points', 'opponents', 'raiders first downs', 'record', 'attendance'] | [['1', 'sept 22', 'miami dolphins', 'win', '31', '21', '17', '1 - 0', '78744'], ['2', 'sept 28', 'baltimore colts', 'win', '31', '20', '18', '2 - 0', '40657'], ['3', 'oct 5', 'san diego chargers', 'win', '6', '0', '17', '3 - 0', '31095'], ['4', 'oct 12', 'kansas city chiefs', 'loss', '10', '42', '23', '3 - 1', '60425'], ['5', 'oct 19', 'cincinnati bengals', 'loss', '10', '14', '18', '3 - 2', '48122'], ['6', 'oct 26', 'san diego chargers', 'win', '25', '0', '23', '4 - 2', '42796'], ['7', 'nov 2', 'denver broncos', 'win', '42', '17', '21', '5 - 2', '52505'], ['8', 'nov 9', 'new orleans saints', 'win', '48', '10', '34', '6 - 2', '51267'], ['9', 'nov 16', 'cleveland browns', 'win', '38', '17', '22', '7 - 2', '50461'], ['10', 'nov 23', 'washington redskins', 'win', '26', '23', '26', '8 - 2', '53582'], ['11', 'nov 30', 'atlanta falcons', 'win', '37', '34', '33', '9 - 2', '50860'], ['12', 'dec 8', 'denver broncos', 'win', '17', '10', '16', '10 - 2', '51075'], ['13', 'dec 14', 'houston oilers', 'loss', '26', '27', '23', '10 - 3', '50719'], ['14', 'dec 21', 'kansas city chiefs', 'win', '28', '20', '24', '11 - 3', '48604']] |
lukáš melich | https://en.wikipedia.org/wiki/Luk%C3%A1%C5%A1_Melich | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12582968-1.html.csv | unique | the only time lukas did not place 15th or higher was at the 2008 olympic games when he placed 29th . | {'scope': 'all', 'row': '7', 'col': '4', 'col_other': '1,2', 'criterion': 'greater_than', 'value': '15th', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'position', '15th'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record is greater than 15th .', 'tostr': 'filter_greater { all_rows ; position ; 15th }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; position ; 15th } }', 'tointer': 'select the rows whose position record is greater than 15th . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'position', '15th'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record is greater than 15th .', 'tostr': 'filter_greater { all_rows ; position ; 15th }'}, 'year'], 'result': '2008', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; position ; 15th } ; year }'}, '2008'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; position ; 15th } ; year } ; 2008 }', 'tointer': 'the year record of this unqiue row is 2008 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'position', '15th'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record is greater than 15th .', 'tostr': 'filter_greater { all_rows ; position ; 15th }'}, 'competition'], 'result': 'olympic games', 'ind': 4, 'tostr': 'hop { filter_greater { all_rows ; position ; 15th } ; competition }'}, 'olympic games'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_greater { all_rows ; position ; 15th } ; competition } ; olympic games }', 'tointer': 'the competition record of this unqiue row is olympic games .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_greater { all_rows ; position ; 15th } ; year } ; 2008 } ; eq { hop { filter_greater { all_rows ; position ; 15th } ; competition } ; olympic games } }', 'tointer': 'the year record of this unqiue row is 2008 . the competition record of this unqiue row is olympic games .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_greater { all_rows ; position ; 15th } } ; and { eq { hop { filter_greater { all_rows ; position ; 15th } ; year } ; 2008 } ; eq { hop { filter_greater { all_rows ; position ; 15th } ; competition } ; olympic games } } } = true', 'tointer': 'select the rows whose position record is greater than 15th . there is only one such row in the table . the year record of this unqiue row is 2008 . the competition record of this unqiue row is olympic games .'} | and { only { filter_greater { all_rows ; position ; 15th } } ; and { eq { hop { filter_greater { all_rows ; position ; 15th } ; year } ; 2008 } ; eq { hop { filter_greater { all_rows ; position ; 15th } ; competition } ; olympic games } } } = true | select the rows whose position record is greater than 15th . there is only one such row in the table . the year record of this unqiue row is 2008 . the competition record of this unqiue row is olympic games . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_9': 9, 'position_10': 10, '15th_11': 11, 'and_6': 6, 'eq_3': 3, 'num_hop_2': 2, 'year_12': 12, '2008_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'competition_14': 14, 'olympic games_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_9': 'all_rows', 'position_10': 'position', '15th_11': '15th', 'and_6': 'and', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_12': 'year', '2008_13': '2008', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'competition_14': 'competition', 'olympic games_15': 'olympic games'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_greater_0': [1, 2, 4], 'all_rows_9': [0], 'position_10': [0], '15th_11': [0], 'and_6': [7], 'eq_3': [6], 'num_hop_2': [3], 'year_12': [2], '2008_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'competition_14': [4], 'olympic games_15': [5]} | ['year', 'competition', 'venue', 'position', 'notes'] | [['1998', 'world junior championships', 'annecy , france', '10th', '61.51 m'], ['1999', 'european junior championships', 'riga , latvia', '5th', '64.20 m'], ['2001', 'european u23 championships', 'amsterdam , netherlands', '11th', '66.41 m'], ['2003', 'universiade', 'daegu , south korea', '4th', '71.26 m'], ['2005', 'world championships', 'helsinki , finland', '14th', '74.53 m'], ['2006', 'european championships', 'gothenburg , sweden', '15th', '73.77 m'], ['2008', 'olympic games', 'beijing , pr china', '29th', '70.56 m'], ['2009', 'world championships', 'berlin , germany', '14th', '74.47 m'], ['2012', 'olympic games', 'london , great britain', '6th', '77.17 m'], ['2013', 'world championships', 'moscow , russia', '3rd', '79.36 m']] |
1984 pga championship | https://en.wikipedia.org/wiki/1984_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18155811-3.html.csv | aggregation | total prize money of the top 10 finishers in the 1984 pga championship was 414749 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '414749', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'money'], 'result': '414749', 'ind': 0, 'tostr': 'sum { all_rows ; money }'}, '414749'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; money } ; 414749 } = true', 'tointer': 'the sum of the money record of all rows is 414749 .'} | round_eq { sum { all_rows ; money } ; 414749 } = true | the sum of the money record of all rows is 414749 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'money_4': 4, '414749_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'money_4': 'money', '414749_5': '414749'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'money_4': [0], '414749_5': [1]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'lee trevino', 'united states', '69 + 68 + 67 + 69 = 273', '- 15', '125000'], ['t2', 'gary player', 'south africa', '74 + 63 + 69 + 71 = 277', '- 11', '62500'], ['t2', 'lanny wadkins', 'united states', '68 + 69 + 68 + 72 = 277', '- 11', '62500'], ['4', 'calvin peete', 'united states', '71 + 70 + 69 + 68 = 278', '- 10', '35000'], ['5', 'seve ballesteros', 'spain', '70 + 69 + 70 + 70 = 279', '- 9', '25000'], ['t6', 'gary hallberg', 'united states', '69 + 71 + 68 + 72 = 280', '- 8', '17125'], ['t6', 'larry mize', 'united states', '71 + 69 + 67 + 73 = 280', '- 8', '17125'], ['t6', 'scott simpson', 'united states', '69 + 69 + 72 + 70 = 280', '- 8', '17125'], ['t6', 'hal sutton', 'united states', '74 + 73 + 64 + 69 = 280', '- 8', '17125'], ['t10', 'russ cochran', 'united states', '73 + 68 + 73 + 67 = 281', '- 7', '12083'], ['t10', 'tsuneyuki nakajima', 'japan', '72 + 68 + 67 + 74 = 281', '- 7', '12083'], ['t10', 'victor regalado', 'mexico', '69 + 69 + 73 + 70 = 281', '- 7', '12083']] |
1994 - 95 cleveland cavaliers season | https://en.wikipedia.org/wiki/1994%E2%80%9395_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16188254-3.html.csv | comparative | in the 1994 - 1995 season of the cleveland cavaliers , mark price scored more as a leading scorer on the november 10 game , compared to the game on the 22nd . | {'row_1': '3', 'row_2': '9', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november 10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to november 10 .', 'tostr': 'filter_eq { all_rows ; date ; november 10 }'}, 'leading scorer'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; november 10 } ; leading scorer }', 'tointer': 'select the rows whose date record fuzzily matches to november 10 . take the leading scorer record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november 22'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to november 22 .', 'tostr': 'filter_eq { all_rows ; date ; november 22 }'}, 'leading scorer'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; november 22 } ; leading scorer }', 'tointer': 'select the rows whose date record fuzzily matches to november 22 . take the leading scorer record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; november 10 } ; leading scorer } ; hop { filter_eq { all_rows ; date ; november 22 } ; leading scorer } } = true', 'tointer': 'select the rows whose date record fuzzily matches to november 10 . take the leading scorer record of this row . select the rows whose date record fuzzily matches to november 22 . take the leading scorer record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; november 10 } ; leading scorer } ; hop { filter_eq { all_rows ; date ; november 22 } ; leading scorer } } = true | select the rows whose date record fuzzily matches to november 10 . take the leading scorer record of this row . select the rows whose date record fuzzily matches to november 22 . take the leading scorer record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'november 10_8': 8, 'leading scorer_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'november 22_12': 12, 'leading scorer_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'november 10_8': 'november 10', 'leading scorer_9': 'leading scorer', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'november 22_12': 'november 22', 'leading scorer_13': 'leading scorer'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'november 10_8': [0], 'leading scorer_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'november 22_12': [1], 'leading scorer_13': [3]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['november 5', 'cleveland', '115 - 107', 'charlotte', 'mark price , 27 points', 'charlotte coliseum 23698', '1 - 0'], ['november 8', 'houston', '100 - 98', 'cleveland', 'terrell brandon , 19 points', 'gund arena 20562', '1 - 1'], ['november 10', 'milwaukee', '88 - 108', 'cleveland', 'mark price , 18 points', 'gund arena 19203', '2 - 1'], ['november 12', 'indiana', '93 - 86', 'cleveland', 'mark price , 15 points', 'gund arena 20401', '2 - 2'], ['november 15', 'charlotte', '86 - 89', 'cleveland', 'tyrone hill , 22 points', 'gund arena 19959', '3 - 2'], ['november 17', 'cleveland', '81 - 80', 'portland', 'mark price , 30 points', 'memorial coliseum 12888', '4 - 2'], ['november 18', 'cleveland', '80 - 82', 'la lakers', 'hot rod williams , 16 points', 'great western forum 10177', '4 - 3'], ['november 20', 'cleveland', '88 - 96', 'sacramento', 'hot rod williams , 17 points', 'arco arena 17317', '4 - 4'], ['november 22', 'minnesota', '79 - 112', 'cleveland', 'mark price , 17 points', 'gund arena 19125', '5 - 4'], ['november 23', 'cleveland', '87 - 100', 'miami', '2 way tie , 17 points', 'miami arena 14498', '5 - 5'], ['november 25', 'cleveland', '96 - 94', 'washington', 'tyrone hill , 25 points', 'usair arena 12756', '6 - 5'], ['november 26', 'golden state', '87 - 101', 'cleveland', 'mark price , 31 points', 'gund arena 20562', '7 - 5'], ['november 30', 'la lakers', '79 - 117', 'cleveland', '3 way tie , 16 points', 'gund arena 19014', '8 - 5']] |
list of pro bowl broadcasters | https://en.wikipedia.org/wiki/List_of_Pro_Bowl_broadcasters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10656249-6.html.csv | majority | from 2000-2003 , al michaels was the play-by-play announcer for all of abc 's pro bowl broadcasts . | {'scope': 'subset', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'al michaels', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'al michaels'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'play - by - play', 'al michaels'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; play - by - play ; al michaels }', 'tointer': 'select the rows whose play - by - play record fuzzily matches to al michaels .'}, 'play - by - play', 'al michaels'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose play - by - play record fuzzily matches to al michaels . for the play - by - play records of these rows , all of them fuzzily match to al michaels .', 'tostr': 'all_eq { filter_eq { all_rows ; play - by - play ; al michaels } ; play - by - play ; al michaels } = true'} | all_eq { filter_eq { all_rows ; play - by - play ; al michaels } ; play - by - play ; al michaels } = true | select the rows whose play - by - play record fuzzily matches to al michaels . for the play - by - play records of these rows , all of them fuzzily match to al michaels . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'play - by - play_4': 4, 'al michaels_5': 5, 'play - by - play_6': 6, 'al michaels_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'play - by - play_4': 'play - by - play', 'al michaels_5': 'al michaels', 'play - by - play_6': 'play - by - play', 'al michaels_7': 'al michaels'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'play - by - play_4': [0], 'al michaels_5': [0], 'play - by - play_6': [1], 'al michaels_7': [1]} | ['year', 'network', 'play - by - play', 'color commentator ( s )', 'sideline reporter ( s )'] | [['2000', 'abc', 'al michaels', 'boomer esiason', 'lesley visser and dan fouts'], ['2001', 'abc', 'al michaels', 'dan fouts and dennis miller', 'eric dickerson and melissa stark'], ['2002', 'abc', 'al michaels', 'dan fouts and dennis miller', 'eric dickerson and melissa stark'], ['2003', 'abc', 'al michaels', 'dan fouts', 'melissa stark and lynn swann'], ['2004', 'espn', 'mike patrick', 'joe theismann and paul maguire', 'suzy kolber and chris mortensen'], ['2005', 'espn', 'mike patrick', 'joe theismann and paul maguire', 'suzy kolber and michelle tafoya'], ['2006', 'espn', 'mike patrick', 'joe theismann and paul maguire', 'suzy kolber and michelle tafoya'], ['2007', 'cbs', 'greg gumbel', 'phil simms and dan dierdorf', 'shannon sharpe'], ['2008', 'fox', 'kenny albert', 'daryl johnston', 'tony siragusa and brian baldinger'], ['2009', 'nbc', 'al michaels', 'cris collinsworth', 'andrea kremer and tiki barber']] |
list of whose line is it anyway ? uk episodes | https://en.wikipedia.org/wiki/List_of_Whose_Line_Is_It_Anyway%3F_UK_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14934885-5.html.csv | count | in the uk 's whose line is it anyway , ryan stiles was performer 3 five times . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'ryan stiles', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'performer 3', 'ryan stiles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose performer 3 record fuzzily matches to ryan stiles .', 'tostr': 'filter_eq { all_rows ; performer 3 ; ryan stiles }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; performer 3 ; ryan stiles } }', 'tointer': 'select the rows whose performer 3 record fuzzily matches to ryan stiles . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; performer 3 ; ryan stiles } } ; 5 } = true', 'tointer': 'select the rows whose performer 3 record fuzzily matches to ryan stiles . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; performer 3 ; ryan stiles } } ; 5 } = true | select the rows whose performer 3 record fuzzily matches to ryan stiles . 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, 'performer 3_5': 5, 'ryan stiles_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', 'performer 3_5': 'performer 3', 'ryan stiles_6': 'ryan stiles', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'performer 3_5': [0], 'ryan stiles_6': [0], '5_7': [2]} | ['date', 'episode', 'performer 1', 'performer 2', 'performer 3', 'performer 4'] | [['24 january 1992', '1', 'jim sweeney', 'steve steen', 'stephen frost', 'tony slattery'], ['31 january 1992', '2', 'greg proops', 'paul merton', 'ryan stiles', 'josie lawrence'], ['7 february 1992', '3', 'jim sweeney', 'paul merton', 'steve steen', 'tony slattery'], ['14 february 1992', '4', 'jim sweeney', 'stephen frost', 'josie lawrence', 'tony slattery'], ['21 february 1992', '5', 'greg proops', 'ryan stiles', 'chip esten', 'tony slattery'], ['28 february 1992', '6', 'london compilation', 'london compilation', 'london compilation', 'london compilation'], ['7 march 1992', '7', 'greg proops', 'ryan stiles', 'colin mochrie', 'brad sherwood'], ['14 march 1992', '8', 'greg proops', 'archie hahn', 'ryan stiles', 'chip esten'], ['21 march 1992', '9', 'ron west', 'ryan stiles', 'colin mochrie', 'greg proops'], ['28 march 1992', '10', 'sam johnson', 'jane brucker', 'ryan stiles', 'chip esten'], ['3 april 1992', '11', 'jim meskimen', 'christopher smith', 'ryan stiles', 'chip esten'], ['10 april 1992', '12', 'greg proops', 'ron west', 'ryan stiles', 'brad sherwood'], ['17 april 1992', '13', 'new york compilation', 'new york compilation', 'new york compilation', 'new york compilation']] |
2004 - 05 toronto raptors season | https://en.wikipedia.org/wiki/2004%E2%80%9305_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15872814-6.html.csv | majority | in the 2004-05 toronto raptors season , when the game was at the air canada centre , rafer alston had the high assists most of the time . | {'scope': 'subset', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rafer alston', 'subset': {'col': '8', 'criterion': 'fuzzily_match', 'value': 'air canada centre'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'air canada centre'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; air canada centre }', 'tointer': 'select the rows whose location attendance record fuzzily matches to air canada centre .'}, 'high assists', 'rafer alston'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose location attendance record fuzzily matches to air canada centre . for the high assists records of these rows , most of them fuzzily match to rafer alston .', 'tostr': 'most_eq { filter_eq { all_rows ; location attendance ; air canada centre } ; high assists ; rafer alston } = true'} | most_eq { filter_eq { all_rows ; location attendance ; air canada centre } ; high assists ; rafer alston } = true | select the rows whose location attendance record fuzzily matches to air canada centre . for the high assists records of these rows , most of them fuzzily match to rafer alston . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'location attendance_4': 4, 'air canada centre_5': 5, 'high assists_6': 6, 'rafer alston_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'location attendance_4': 'location attendance', 'air canada centre_5': 'air canada centre', 'high assists_6': 'high assists', 'rafer alston_7': 'rafer alston'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'location attendance_4': [0], 'air canada centre_5': [0], 'high assists_6': [1], 'rafer alston_7': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['46', 'february 2', 'indiana', 'w 98 - 97 ( ot )', 'chris bosh ( 25 )', 'chris bosh ( 15 )', 'milt palacio ( 7 )', 'conseco fieldhouse 14783', '19 - 27'], ['47', 'february 4', 'washington', 'w 103 - 100 ( ot )', 'jalen rose ( 26 )', 'chris bosh ( 11 )', 'rafer alston ( 8 )', 'air canada centre 15546', '20 - 27'], ['48', 'february 6', 'dallas', 'l 113 - 122 ( ot )', 'chris bosh ( 29 )', 'chris bosh ( 8 )', 'rafer alston ( 8 )', 'air canada centre 17896', '20 - 28'], ['49', 'february 8', 'cleveland', 'l 91 - 104 ( ot )', 'jalen rose ( 21 )', 'loren woods ( 9 )', 'milt palacio ( 9 )', 'gund arena 17036', '20 - 29'], ['50', 'february 9', 'milwaukee', 'l 107 - 110 ( ot )', 'jalen rose ( 26 )', 'chris bosh ( 9 )', 'rafer alston ( 12 )', 'air canada centre 14269', '20 - 30'], ['51', 'february 11', 'philadelphia', 'l 91 - 106 ( ot )', 'jalen rose ( 23 )', 'jalen rose ( 10 )', 'chris bosh , morris peterson , jalen rose ( 5 )', 'air canada centre 19800', '20 - 31'], ['52', 'february 13', 'la clippers', 'w 109 - 106 ( ot )', 'chris bosh ( 26 )', 'chris bosh ( 10 )', 'rafer alston ( 8 )', 'air canada centre 15721', '21 - 31'], ['53', 'february 16', 'chicago', 'l 115 - 121 ( ot )', 'chris bosh ( 28 )', 'chris bosh , jalen rose ( 7 )', 'rafer alston ( 8 )', 'air canada centre 15881', '21 - 32'], ['54', 'february 22', 'new jersey', 'w 100 - 82 ( ot )', 'jalen rose ( 30 )', 'chris bosh ( 12 )', 'rafer alston ( 6 )', 'continental airlines arena 14080', '22 - 32'], ['55', 'february 25', 'milwaukee', 'w 106 - 102 ( ot )', 'chris bosh ( 27 )', 'chris bosh , donyell marshall ( 8 )', 'rafer alston ( 7 )', 'bradley center 15883', '23 - 32']] |
comparison of e - book formats | https://en.wikipedia.org/wiki/Comparison_of_e-book_formats | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12115370-1.html.csv | unique | plain text is the only e-book format that does not support images . | {'scope': 'all', 'row': '11', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'no', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'image support', 'no'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose image support record fuzzily matches to no .', 'tostr': 'filter_eq { all_rows ; image support ; no }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; image support ; no } }', 'tointer': 'select the rows whose image support record fuzzily matches to no . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'image support', 'no'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose image support record fuzzily matches to no .', 'tostr': 'filter_eq { all_rows ; image support ; no }'}, 'format'], 'result': 'plain text', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; image support ; no } ; format }'}, 'plain text'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; image support ; no } ; format } ; plain text }', 'tointer': 'the format record of this unqiue row is plain text .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; image support ; no } } ; eq { hop { filter_eq { all_rows ; image support ; no } ; format } ; plain text } } = true', 'tointer': 'select the rows whose image support record fuzzily matches to no . there is only one such row in the table . the format record of this unqiue row is plain text .'} | and { only { filter_eq { all_rows ; image support ; no } } ; eq { hop { filter_eq { all_rows ; image support ; no } ; format } ; plain text } } = true | select the rows whose image support record fuzzily matches to no . there is only one such row in the table . the format record of this unqiue row is plain text . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'image support_7': 7, 'no_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'format_9': 9, 'plain text_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'image support_7': 'image support', 'no_8': 'no', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'format_9': 'format', 'plain text_10': 'plain text'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'image support_7': [0], 'no_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'format_9': [2], 'plain text_10': [3]} | ['format', 'filename extension', 'image support', 'interactivity support', 'word wrap support', 'open standard'] | [['djvu', 'djvu', 'yes', 'no', 'no', 'yes'], ['epub ( idpf )', 'epub', 'yes', 'yes', 'yes', 'yes'], ['fictionbook', 'fb2', 'yes', 'no', 'yes', 'yes'], ['html', 'html', 'yes', 'no', 'yes', 'yes'], ['kindle', 'azw', 'yes', 'yes', 'yes', 'no'], ['microsoft reader', 'lit', 'yes', 'no', 'yes', 'no'], ['mobipocket', 'prc , mobi', 'yes', 'yes', 'yes', 'no'], ['multimedia ebook', 'exe', 'yes', 'yes', 'no', 'yes'], ['newton book', 'pkg', 'yes', 'yes', 'yes', 'yes'], ['ereader', 'pdb', 'yes', 'no', 'yes', 'no'], ['plain text', 'txt', 'no', 'no', 'yes', 'yes'], ['plucker', 'pdb', 'yes', 'yes', 'yes', 'yes'], ['portable document format', 'pdf', 'yes', 'yes', 'yes though not all readers implement support', 'yes'], ['postscript', 'ps', 'yes', 'no', 'no', 'yes'], ['tome raider', 'tr2 , tr3', 'yes', 'no', 'yes', 'no'], ['openxps', 'oxps , xps', 'yes', 'no', 'no', 'yes']] |
shinichi ito | https://en.wikipedia.org/wiki/Shinichi_Ito | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12185077-3.html.csv | count | shinichi ito was ranked 21st for a total of three different years . | {'scope': 'all', 'criterion': 'equal', 'value': '21st', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rank', '21st'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rank record fuzzily matches to 21st .', 'tostr': 'filter_eq { all_rows ; rank ; 21st }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; rank ; 21st } }', 'tointer': 'select the rows whose rank record fuzzily matches to 21st . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; rank ; 21st } } ; 3 } = true', 'tointer': 'select the rows whose rank record fuzzily matches to 21st . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; rank ; 21st } } ; 3 } = true | select the rows whose rank record fuzzily matches to 21st . 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, 'rank_5': 5, '21st_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', 'rank_5': 'rank', '21st_6': '21st', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'rank_5': [0], '21st_6': [0], '3_7': [2]} | ['year', 'class', 'team', 'machine', 'points', 'rank', 'wins'] | [['1988', '500cc', 'seed - honda', 'nsr500', '0', 'nc', '0'], ['1989', '500cc', 'hrc - honda', 'nsr500', '6', '32nd', '0'], ['1990', '500cc', 'pentax - honda', 'nsr500', '7', '26th', '0'], ['1991', '500cc', 'pentax - honda', 'nsr500', '0', 'nc', '0'], ['1992', '500cc', 'hrc - honda', 'nsr500', '10', '16th', '0'], ['1993', '500cc', 'rothmans - honda', 'nsr500', '119', '7th', '0'], ['1994', '500cc', 'hrc - honda', 'nsr500', '141', '7th', '0'], ['1995', '500cc', 'repsol - honda', 'nsr500', '127', '5th', '0'], ['1996', '500cc', 'repsol - honda', 'nsr500v', '77', '12th', '0'], ['1999', '500cc', 'lucky strike - honda', 'nsr500', '9', '21st', '0'], ['2002', 'motogp', 'repsol - honda', 'rc211v', '13', '21st', '0'], ['2002', 'motogp', 'kanemoto - honda', 'nsr500', '13', '21st', '0'], ['2005', 'motogp', 'marlboro - ducati', 'gp5', '0', 'nc', '0'], ['2007', 'motogp', "pramac d'antin ducati", 'gp7', '1', '26th', '0'], ['2011', 'motogp', 'repsol - honda', 'rc212v', '3', '22nd', '0']] |
eastern indiana athletic conference | https://en.wikipedia.org/wiki/Eastern_Indiana_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18773999-3.html.csv | count | four schools in the eastern indiana athletic conference all joined in the year 1956 . | {'scope': 'all', 'criterion': 'equal', 'value': '1956', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year joined', '1956'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year joined record is equal to 1956 .', 'tostr': 'filter_eq { all_rows ; year joined ; 1956 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; year joined ; 1956 } }', 'tointer': 'select the rows whose year joined record is equal to 1956 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; year joined ; 1956 } } ; 4 } = true', 'tointer': 'select the rows whose year joined record is equal to 1956 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; year joined ; 1956 } } ; 4 } = true | select the rows whose year joined record is equal to 1956 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year joined_5': 5, '1956_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year joined_5': 'year joined', '1956_6': '1956', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year joined_5': [0], '1956_6': [0], '4_7': [2]} | ['school', 'city', 'team name', 'county', 'year joined', 'year left'] | [['aurora', 'aurora', 'red devils', '15 dearborn', '1956', '1978'], ['brookville', 'brookville', 'greyhounds', '24 franklin', '1956 1973', '1966 1989'], ['cambridge city', 'cambridge city', 'wampus cats', '89 wayne', '1956', '1962'], ['hagerstown', 'hagerstown', 'tigers', '89 wayne', '1956', '1962'], ['north dearborn', 'guilford', 'vikings', '15 dearborn', '1962', '1973'], ['north vernon', 'north vernon', 'panthers', '40 jennings', '1962', '1968'], ['jennings county', 'north vernon', 'panthers', '40 jennings', '1968', '1973']] |
progressive conservative party of canada | https://en.wikipedia.org/wiki/Progressive_Conservative_Party_of_Canada | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-123462-2.html.csv | unique | only in 1993 did the progressive conservative party of canada win less than 10 seats . | {'scope': 'all', 'row': '16', 'col': '3', 'col_other': '1', 'criterion': 'less_than', 'value': '10', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'of seats won', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose of seats won record is less than 10 .', 'tostr': 'filter_less { all_rows ; of seats won ; 10 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; of seats won ; 10 } }', 'tointer': 'select the rows whose of seats won record is less than 10 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'of seats won', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose of seats won record is less than 10 .', 'tostr': 'filter_less { all_rows ; of seats won ; 10 }'}, 'election'], 'result': '1993', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; of seats won ; 10 } ; election }'}, '1993'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; of seats won ; 10 } ; election } ; 1993 }', 'tointer': 'the election record of this unqiue row is 1993 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; of seats won ; 10 } } ; eq { hop { filter_less { all_rows ; of seats won ; 10 } ; election } ; 1993 } } = true', 'tointer': 'select the rows whose of seats won record is less than 10 . there is only one such row in the table . the election record of this unqiue row is 1993 .'} | and { only { filter_less { all_rows ; of seats won ; 10 } } ; eq { hop { filter_less { all_rows ; of seats won ; 10 } ; election } ; 1993 } } = true | select the rows whose of seats won record is less than 10 . there is only one such row in the table . the election record of this unqiue row is 1993 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'of seats won_7': 7, '10_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'election_9': 9, '1993_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'of seats won_7': 'of seats won', '10_8': '10', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'election_9': 'election', '1993_10': '1993'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'of seats won_7': [0], '10_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'election_9': [2], '1993_10': [3]} | ['election', 'of candidates nominated', 'of seats won', 'of total votes', '% of popular vote'] | [['1945', '203', '65', '1448744', '27.62 %'], ['1949', '249', '41', '1734261', '29.62 %'], ['1953', '248', '50', '1749579', '31.01 %'], ['1957', '256', '109', '2564732', '38.81 %'], ['1958', '265', '208', '3908633', '53.56 %'], ['1962', '265', '114', '2865542', '37.22 %'], ['1963', '265', '93', '2582322', '32.72 %'], ['1965', '265', '95', '2500113', '32.41 %'], ['1968', '262', '72', '2548949', '31.36 %'], ['1972', '265', '107', '3388980', '35.02 %'], ['1974', '264', '95', '3371319', '35.46 %'], ['1979', '282', '136', '4111606', '35.89 %'], ['1980', '282', '103', '3552994', '32.49 %'], ['1984', '282', '211', '6278818', '50.03 %'], ['1988', '295', '169', '5667543', '43.02 %'], ['1993', '295', '2', '2178303', '16.04 %'], ['1997', '301', '20', '2446705', '18.84 %'], ['2000', '291', '12', '1566994', '12.19 %']] |
roberto moreno | https://en.wikipedia.org/wiki/Roberto_Moreno | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226554-3.html.csv | unique | roberto moreno scored 1 point in only one race that he participated in from 1982 to 1995 . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': 'n/a', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; points ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; points ; 1 } } = true', 'tointer': 'select the rows whose points record is equal to 1 . there is only one such row in the table .'} | only { filter_eq { all_rows ; points ; 1 } } = true | select the rows whose points record is equal to 1 . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_eq_0': 0, 'all_rows_3': 3, 'points_4': 4, '1_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_eq_0': 'filter_eq', 'all_rows_3': 'all_rows', 'points_4': 'points', '1_5': '1'} | {'only_1': [2], 'result_2': [], 'filter_eq_0': [1], 'all_rows_3': [0], 'points_4': [0], '1_5': [0]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1982', 'john player lotus', 'lotus 91', 'cosworth v8', '0'], ['1987', 'team ags', 'ags jh22', 'cosworth v8', '1'], ['1989', 'coloni spa', 'coloni fc188b', 'cosworth v8', '0'], ['1989', 'coloni spa', 'coloni c3', 'cosworth v8', '0'], ['1990', 'eurobrun racing', 'eurobrun er189', 'judd v8', '6'], ['1990', 'eurobrun racing', 'eurobrun er189b', 'judd v8', '6'], ['1990', 'benetton formula', 'benetton b190', 'ford v8', '6'], ['1991', 'camel benetton ford', 'benetton b190b', 'ford v8', '8'], ['1991', 'camel benetton ford', 'benetton b191', 'ford v8', '8'], ['1991', 'team 7up jordan', 'jordan 191', 'ford v8', '8'], ['1991', 'minardi team', 'minardi m191', 'ferrari v12', '8'], ['1992', 'andrea moda formula', 'andrea moda s921', 'judd v10', '0'], ['1995', 'parmalat forti ford', 'forti fg01', 'ford v8', '0']] |
mahmoud shelbaieh | https://en.wikipedia.org/wiki/Mahmoud_Shelbaieh | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10935209-1.html.csv | ordinal | the 1st game mahmoud shelbaieh played in the 2004 afc asian cup qualification was on september 26 , 2003 . | {'scope': 'subset', 'row': '6', 'col': '1', 'order': '1', 'col_other': '5', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': {'col': '5', 'criterion': 'equal', 'value': '2004 afc asian cup qualification'}} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '2004 afc asian cup qualification'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; competition ; 2004 afc asian cup qualification }', 'tointer': 'select the rows whose competition record fuzzily matches to 2004 afc asian cup qualification .'}, 'date', '1'], 'result': 'september 26 , 2003', 'ind': 1, 'tostr': 'nth_min { filter_eq { all_rows ; competition ; 2004 afc asian cup qualification } ; date ; 1 }', 'tointer': 'select the rows whose competition record fuzzily matches to 2004 afc asian cup qualification . the 1st minimum date record of these rows is september 26 , 2003 .'}, 'september 26 , 2003'], 'result': True, 'ind': 2, 'tostr': 'eq { nth_min { filter_eq { all_rows ; competition ; 2004 afc asian cup qualification } ; date ; 1 } ; september 26 , 2003 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to 2004 afc asian cup qualification . the 1st minimum date record of these rows is september 26 , 2003 .'} | eq { nth_min { filter_eq { all_rows ; competition ; 2004 afc asian cup qualification } ; date ; 1 } ; september 26 , 2003 } = true | select the rows whose competition record fuzzily matches to 2004 afc asian cup qualification . the 1st minimum date record of these rows is september 26 , 2003 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'nth_min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'competition_5': 5, '2004 afc asian cup qualification_6': 6, 'date_7': 7, '1_8': 8, 'september 26 , 2003_9': 9} | {'eq_2': 'eq', 'result_3': 'true', 'nth_min_1': 'nth_min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'competition_5': 'competition', '2004 afc asian cup qualification_6': '2004 afc asian cup qualification', 'date_7': 'date', '1_8': '1', 'september 26 , 2003_9': 'september 26 , 2003'} | {'eq_2': [3], 'result_3': [], 'nth_min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], '2004 afc asian cup qualification_6': [0], 'date_7': [1], '1_8': [1], 'september 26 , 2003_9': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['april 25 , 2001', 'tashkent', '2 - 0', 'win', '2002 fifa world cup qualification'], ['february 9 , 2002', "ta ' qali", '2 - 1', 'loss', 'friendly'], ['september 1 , 2002', 'damascus', '1 - 0', 'win', '2002 west asian football federation championship'], ['december 7 , 2002', 'manama', '3 - 0', 'win', 'friendly ( 2 goals )'], ['december 23 , 2002', 'kuwait city', '2 - 1', 'win', 'friendly'], ['september 26 , 2003', 'amman', '3 - 2', 'win', '2004 afc asian cup qualification'], ['november 18 , 2003', 'amman', '3 - 0', 'win', '2004 afc asian cup qualification'], ['february 18 , 2004', 'amman', '5 - 0', 'win', '2006 fifa world cup qualification'], ['may 30 , 2004', 'annaba', '1 - 1', 'draw', 'friendly'], ['june 21 , 2004', 'tehran', '2 - 0', 'win', '2004 west asian football federation championship'], ['july 31 , 2004', 'chongqing', '1 - 1 aet ( 1:1 , 1:1 ) 4:3 pso', 'loss', '2004 afc asian cup'], ['august 21 , 2004', 'amman', '2 - 2', 'draw', 'friendly ( 2 goals )'], ['october 8 , 2004', 'bangkok', '3 - 2', 'win', 'friendly'], ['october 20 , 2004', 'tripoli', '3 - 0', 'win', 'friendly'], ['february 22 , 2006', 'amman', '3 - 0', 'win', '2007 afc asian cup qualification'], ['october 28 , 2007', 'amman', '2 - 0', 'win', '2010 fifa world cup qualification'], ['january 24 , 2008', 'dubai', '1 - 1', 'draw', 'friendly'], ['january 28 , 2008', 'amman', '4 - 1', 'win', 'friendly'], ['december 30 , 2009', 'jinan', '2 - 2', 'draw', 'friendly ( 2 goals )']] |
british rail railbuses | https://en.wikipedia.org/wiki/British_Rail_Railbuses | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1081459-1.html.csv | majority | of the british rail railbuses that were introduced in 1958 , most were withdrawn before 1970 . | {'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1970', 'subset': {'col': '3', 'criterion': 'equal', 'value': '1958'}} | {'func': 'most_less', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'introduced', '1958'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; introduced ; 1958 }', 'tointer': 'select the rows whose introduced record is equal to 1958 .'}, 'withdrawn', '1970'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose introduced record is equal to 1958 . for the withdrawn records of these rows , most of them are less than 1970 .', 'tostr': 'most_less { filter_eq { all_rows ; introduced ; 1958 } ; withdrawn ; 1970 } = true'} | most_less { filter_eq { all_rows ; introduced ; 1958 } ; withdrawn ; 1970 } = true | select the rows whose introduced record is equal to 1958 . for the withdrawn records of these rows , most of them are less than 1970 . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_eq_0': 0, 'all_rows_3': 3, 'introduced_4': 4, '1958_5': 5, 'withdrawn_6': 6, '1970_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_eq_0': 'filter_eq', 'all_rows_3': 'all_rows', 'introduced_4': 'introduced', '1958_5': '1958', 'withdrawn_6': 'withdrawn', '1970_7': '1970'} | {'most_less_1': [2], 'result_2': [], 'filter_eq_0': [1], 'all_rows_3': [0], 'introduced_4': [0], '1958_5': [0], 'withdrawn_6': [1], '1970_7': [1]} | ['number range', 'builder', 'introduced', 'no built', 'region', 'withdrawn'] | [['79958 - 59', 'bristol / eastern coach works', '1958', '2', 'scotland', '1966'], ['79960 - 64', 'wmd donauwãrth', '1958', '5', 'eastern region / london midland', '1967'], ['79965 - 69', 'd wickham & co', '1958', '5', 'scotland', '1966'], ['79970 - 74', 'park royal vehicles', '1958', '5', 'london midland / scotland', '1968'], ['79975 - 79', 'ac cars', '1958', '5', 'scotland / western region', '1968'], ['999507 elliot', 'wickham', '1958', '1', 'departmental', '1997'], ['998900 - 998901', 'drewry', '1950', '2', 'departmental', '1990']] |
sea patrol ( season 3 ) | https://en.wikipedia.org/wiki/Sea_Patrol_%28season_3%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18712423-3.html.csv | count | 3 of the sea patrol season 3 episodes directed by steve mann were written by john ridley . | {'scope': 'subset', 'criterion': 'equal', 'value': 'john ridley', 'result': '3', 'col': '5', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'steve mann'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'steve mann'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; directed by ; steve mann }', 'tointer': 'select the rows whose directed by record fuzzily matches to steve mann .'}, 'written by', 'john ridley'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose directed by record fuzzily matches to steve mann . among these rows , select the rows whose written by record fuzzily matches to john ridley .', 'tostr': 'filter_eq { filter_eq { all_rows ; directed by ; steve mann } ; written by ; john ridley }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; directed by ; steve mann } ; written by ; john ridley } }', 'tointer': 'select the rows whose directed by record fuzzily matches to steve mann . among these rows , select the rows whose written by record fuzzily matches to john ridley . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; directed by ; steve mann } ; written by ; john ridley } } ; 3 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to steve mann . among these rows , select the rows whose written by record fuzzily matches to john ridley . the number of such rows is 3 .'} | eq { count { filter_eq { filter_eq { all_rows ; directed by ; steve mann } ; written by ; john ridley } } ; 3 } = true | select the rows whose directed by record fuzzily matches to steve mann . among these rows , select the rows whose written by record fuzzily matches to john ridley . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'directed by_6': 6, 'steve mann_7': 7, 'written by_8': 8, 'john ridley_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'directed by_6': 'directed by', 'steve mann_7': 'steve mann', 'written by_8': 'written by', 'john ridley_9': 'john ridley', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'directed by_6': [0], 'steve mann_7': [0], 'written by_8': [1], 'john ridley_9': [1], '3_10': [3]} | ['series episode', 'season episode', 'title', 'directed by', 'written by', 'original air date', 'viewers ( millions )'] | [['27', '1', 'catch and release', 'ian barry', 'adam h todd', '18 may 2009', '1.33'], ['28', '2', 'monkey business', 'steve mann', 'felicity packard', '25 may 2009', '1.385'], ['29', '3', 'china dolls', 'ian barry', 'philip dalkin', '1 june 2009', '1.282'], ['30', '4', 'guns', 'steve mann', 'john ridley', '8 june 2009', '1.366'], ['31', '5', 'ghost net', 'ian barry', 'jeff truman', '15 june 2009', '1.358'], ['32', '6', 'oh danny boy', 'steve mann', 'john ridley', '22 june 2009', '1.309'], ['33', '7', 'half life', 'steve mann', 'john ridley', '29 june 2009', '1.333'], ['34', '8', 'red sky morning', 'ian barry', 'tony morphett', '6 july 2009', '1.215'], ['35', '9', 'pearls before swine', 'ian barry', 'matt ford', '13 july 2009', '1.350'], ['36', '10', 'safeguard', 'steve mann', 'jeff truman', '20 july 2009', '1.281'], ['37', '11', 'secret cargo', 'ian barry', 'adam h todd', '20 july 2009', '1.197'], ['38', '12', 'black gold', 'steve mann', 'jeff truman', '27 july 2009', '1.279']] |
leung hing kit | https://en.wikipedia.org/wiki/Leung_Hing_Kit | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18698934-2.html.csv | superlative | the soccer match played at estádio campo desportivo , macau had the highest total . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'result'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; result }'}, 'venue'], 'result': 'estádio campo desportivo , macau', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; result } ; venue }'}, 'estádio campo desportivo , macau'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; result } ; venue } ; estádio campo desportivo , macau } = true', 'tointer': 'select the row whose result record of all rows is maximum . the venue record of this row is estádio campo desportivo , macau .'} | eq { hop { argmax { all_rows ; result } ; venue } ; estádio campo desportivo , macau } = true | select the row whose result record of all rows is maximum . the venue record of this row is estádio campo desportivo , macau . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'result_5': 5, 'venue_6': 6, 'estádio campo desportivo , macau_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'result_5': 'result', 'venue_6': 'venue', 'estádio campo desportivo , macau_7': 'estádio campo desportivo , macau'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'result_5': [0], 'venue_6': [1], 'estádio campo desportivo , macau_7': [2]} | ['date', 'venue', 'result', 'scored', 'competition'] | [['20 june 2010', 'estádio campo desportivo , macau', '5 - 1', '0', '2010 hong kong - macau interport'], ['2 november 2010', 'siu sai wan sports ground , hong kong', '0 - 4', '0', 'friendly'], ['26 january 2011', 'sai tso wan recreation ground , hong kong', '1 - 0', '1', 'friendly'], ['9 february 2011', 'po kong village park , hong kong', '1 - 4', '0', 'friendly'], ['3 june 2010', 'xianghe sports center , beijing', '2 - 2', '0', 'friendly']] |
david brabham | https://en.wikipedia.org/wiki/David_Brabham | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1148454-4.html.csv | comparative | david brabham and his team drove more laps in the race in 1993 as opposed to the race in 1997 . | {'row_1': '2', 'row_2': '4', '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', 'year', '1993'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1993 .', 'tostr': 'filter_eq { all_rows ; year ; 1993 }'}, 'laps'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1993 } ; laps }', 'tointer': 'select the rows whose year record fuzzily matches to 1993 . take the laps record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1997'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1997 .', 'tostr': 'filter_eq { all_rows ; year ; 1997 }'}, 'laps'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1997 } ; laps }', 'tointer': 'select the rows whose year record fuzzily matches to 1997 . take the laps record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 1993 } ; laps } ; hop { filter_eq { all_rows ; year ; 1997 } ; laps } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 1993 . take the laps record of this row . select the rows whose year record fuzzily matches to 1997 . take the laps record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; year ; 1993 } ; laps } ; hop { filter_eq { all_rows ; year ; 1997 } ; laps } } = true | select the rows whose year record fuzzily matches to 1993 . take the laps record of this row . select the rows whose year record fuzzily matches to 1997 . take the laps 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, 'year_7': 7, '1993_8': 8, 'laps_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '1997_12': 12, 'laps_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', 'year_7': 'year', '1993_8': '1993', 'laps_9': 'laps', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '1997_12': '1997', 'laps_13': 'laps'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '1993_8': [0], 'laps_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '1997_12': [1], 'laps_13': [3]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['1992', "toyota team tom 's", 'geoff lees ukyo katayama', 'c1', '192', 'dnf', 'dnf'], ['1993', 'twr jaguar racing', 'john nielsen david coulthard', 'gt', '306', 'dsq', 'dsq'], ['1996', 'gulf racing gtc racing', 'pierre - henri raphanel lindsay owen - jones', 'gt1', '335', '5th', '4th'], ['1997', 'david price racing', 'perry mccarthy doc bundy', 'gt1', '145', 'dnf', 'dnf'], ['1998', 'panoz motorsports', 'andy wallace jamie davies', 'gt1', '335', '7th', '7th'], ['1999', 'panoz motorsports', 'éric bernard butch leitzinger', 'lmp', '336', '7th', '6th'], ['2000', 'panoz motorsports', 'jan magnussen mario andretti', 'lmp900', '315', '15th', '8th'], ['2001', 'panoz motorsports', 'jan magnussen franck lagorce', 'lmp900', '85', 'dnf', 'dnf'], ['2002', 'panoz motor sports', 'jan magnussen bryan herta', 'lmp900', '90', 'dnf', 'dnf'], ['2003', 'team bentley', 'mark blundell johnny herbert', 'lmgtp', '375', '2nd', '2nd'], ['2004', 'zytek engineering , ltd', 'andy wallace hayanari shimoda', 'lmp1', '167', 'dnf', 'dnf'], ['2005', 'aston martin racing', 'stéphane sarrazin darren turner', 'gt1', '333', '9th', '3rd'], ['2006', 'russian age racing team modena', 'antonio garcía nelson piquet , jr', 'gt1', '343', '9th', '4th'], ['2007', 'aston martin racing', 'darren turner rickard rydell', 'gt1', '343', '5th', '1st'], ['2008', 'aston martin racing', 'antonio garcía darren turner', 'gt1', '344', '13th', '1st'], ['2009', 'peugeot sport total', 'marc gené alexander wurz', 'lmp1', '382', '1st', '1st'], ['2010', 'highcroft racing', 'marino franchitti marco werner', 'lmp2', '296', '25th', '9th'], ['2012', 'jrm', 'peter dumbreck karun chandhok', 'lmp1', '357', '6th', '6th']] |
1998 new england patriots season | https://en.wikipedia.org/wiki/1998_New_England_Patriots_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10696170-1.html.csv | count | in the 1998 new england patriots season , for players picked after round 3 , there were 3 players picked before the overall pick of 200 . | {'scope': 'subset', 'criterion': 'less_than', 'value': '200', 'result': '3', 'col': '2', 'subset': {'col': '1', 'criterion': 'greater_than', 'value': '3'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'round', '3'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; round ; 3 }', 'tointer': 'select the rows whose round record is greater than 3 .'}, 'overall', '200'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose round record is greater than 3 . among these rows , select the rows whose overall record is less than 200 .', 'tostr': 'filter_less { filter_greater { all_rows ; round ; 3 } ; overall ; 200 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_less { filter_greater { all_rows ; round ; 3 } ; overall ; 200 } }', 'tointer': 'select the rows whose round record is greater than 3 . among these rows , select the rows whose overall record is less than 200 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_greater { all_rows ; round ; 3 } ; overall ; 200 } } ; 3 } = true', 'tointer': 'select the rows whose round record is greater than 3 . among these rows , select the rows whose overall record is less than 200 . the number of such rows is 3 .'} | eq { count { filter_less { filter_greater { all_rows ; round ; 3 } ; overall ; 200 } } ; 3 } = true | select the rows whose round record is greater than 3 . among these rows , select the rows whose overall record is less than 200 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'round_6': 6, '3_7': 7, 'overall_8': 8, '200_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'round_6': 'round', '3_7': '3', 'overall_8': 'overall', '200_9': '200', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'round_6': [0], '3_7': [0], 'overall_8': [1], '200_9': [1], '3_10': [3]} | ['round', 'overall', 'player', 'position', 'college'] | [['1', '18', 'robert edwards', 'running back', 'georgia'], ['1', '22', 'tebucky jones', 'safety', 'syracuse'], ['2', '52', 'tony simmons', 'wide receiver', 'wisconsin'], ['2', '54', 'rod rutledge', 'tight end', 'alabama'], ['3', '81', 'chris floyd', 'fullback', 'michigan'], ['3', '83', 'greg spires', 'defensive end', 'florida state'], ['4', '115', 'leonta rheams', 'defensive tackle', 'houston'], ['5', '145', 'ron merkerson', 'linebacker', 'colorado'], ['6', '176', 'harold shaw', 'fullback', 'southern miss'], ['7', '211', 'jason andersen', 'offensive guard', 'byu']] |
churchill downs debutante stakes | https://en.wikipedia.org/wiki/Churchill_Downs_Debutante_Stakes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12168673-1.html.csv | ordinal | cashier 's dream recorded the fastest time in the churchill downs debutante stakes race . | {'row': '12', 'col': '6', 'order': '1', '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', 'time', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; time ; 1 }'}, 'winner'], 'result': "cashier 's dream", 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; time ; 1 } ; winner }'}, "cashier 's dream"], 'result': True, 'ind': 2, 'tostr': "eq { hop { nth_argmin { all_rows ; time ; 1 } ; winner } ; cashier 's dream } = true", 'tointer': "select the row whose time record of all rows is 1st minimum . the winner record of this row is cashier 's dream ."} | eq { hop { nth_argmin { all_rows ; time ; 1 } ; winner } ; cashier 's dream } = true | select the row whose time record of all rows is 1st minimum . the winner record of this row is cashier 's dream . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, '1_6': 6, 'winner_7': 7, "cashier 's dream_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', 'time_5': 'time', '1_6': '1', 'winner_7': 'winner', "cashier 's dream_8": "cashier 's dream"} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], '1_6': [0], 'winner_7': [1], "cashier 's dream_8": [2]} | ['year', 'winner', 'jockey', 'trainer', 'owner', 'time'] | [['2012', 'blueeyesintherein', 'leandro goncalves', 'gary simms', 'self / king / morgenson / travis , et al', '1:11.71'], ['2011', 'flashy lassie', 'kent desormeaux', 'gary simms', 'barry l king', '1:10.89'], ['2010', 'just louise', 'robby albarado', 'dale romans', 'eldon farm equine', '1:11.85'], ['2009', 'decelerator', 'julien leparoux', 'd wayne lukas', 'westrock stables', '1:11.28'], ['2008', 'garden district', 'robby albarado', 'todd a pletcher', 'twin creeks racing stable', '1:11.07'], ['2007', 'rated fiesty', 'shaun bridgmohan', 'steve asmussen', 'heiligbrodt racing et al', '1:09.27'], ['2006', 'richwoman', 'shaun bridgmohan', 'steve asmussen', 'heiligbrodt racing', '1:10.50'], ['2005', 'effectual', 'robby albarado', 'steve asmussen', 'gainesway / george bolton', '1:03.95'], ['2004', 'classic elegance', 'pat day', 'd wayne lukas', 'bob & beverly lewis', '1:04.18'], ['2003', 'be gentle', 'cornelio velasquez', 'd wayne lukas', 'thomas f van meter ii', '1:03.96'], ['2002', 'awesome humor', 'pat day', 'w elliott walden', 'winstar farm', '1:03.45'], ['2001', "cashier 's dream", 'donnie meche', 'steve asmussen', 'team valor', '1:02.52'], ['2000', 'gold mover', 'craig perret', 'mark a hennig', 'edward p evans', '1:03.79'], ['1999', 'chilukki', 'willie martinez', 'bob baffert', 'stonerside stable', '1:03.66'], ['1998', 'silverbulletday', 'gary stevens', 'bob baffert', 'michael e pegram', '1:04.70'], ['1997', 'love lock', 'pat day', 'd wayne lukas', 'michael tabor', '1:03.84'], ['1996', 'move', 'pat day', 'frank l brothers', 'cherry valley farm', '1:05.66'], ['1995', 'golden attraction', 'donna barton', 'd wayne lukas', 'overbrook farm', '1:04.19']] |
list of royal pains episodes | https://en.wikipedia.org/wiki/List_of_Royal_Pains_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23117208-5.html.csv | comparative | more people watched the first episode than the last episode of royal pains . | {'row_1': '1', 'row_2': '11', 'col': '8', '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', 'no in season', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose no in season record fuzzily matches to 1 .', 'tostr': 'filter_eq { all_rows ; no in season ; 1 }'}, 'viewers ( millions )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; no in season ; 1 } ; viewers ( millions ) }', 'tointer': 'select the rows whose no in season record fuzzily matches to 1 . take the viewers ( millions ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'no in season', '12'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose no in season record fuzzily matches to 12 .', 'tostr': 'filter_eq { all_rows ; no in season ; 12 }'}, 'viewers ( millions )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; no in season ; 12 } ; viewers ( millions ) }', 'tointer': 'select the rows whose no in season record fuzzily matches to 12 . take the viewers ( millions ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; no in season ; 1 } ; viewers ( millions ) } ; hop { filter_eq { all_rows ; no in season ; 12 } ; viewers ( millions ) } } = true', 'tointer': 'select the rows whose no in season record fuzzily matches to 1 . take the viewers ( millions ) record of this row . select the rows whose no in season record fuzzily matches to 12 . take the viewers ( millions ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; no in season ; 1 } ; viewers ( millions ) } ; hop { filter_eq { all_rows ; no in season ; 12 } ; viewers ( millions ) } } = true | select the rows whose no in season record fuzzily matches to 1 . take the viewers ( millions ) record of this row . select the rows whose no in season record fuzzily matches to 12 . take the viewers ( millions ) record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'no in season_7': 7, '1_8': 8, 'viewers (millions)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'no in season_11': 11, '12_12': 12, 'viewers (millions)_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'no in season_7': 'no in season', '1_8': '1', 'viewers (millions)_9': 'viewers ( millions )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'no in season_11': 'no in season', '12_12': '12', 'viewers (millions)_13': 'viewers ( millions )'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'no in season_7': [0], '1_8': [0], 'viewers (millions)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'no in season_11': [1], '12_12': [1], 'viewers (millions)_13': [3]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'prod code', 'viewers ( millions )'] | [['47', '1', 'after the fireworks', 'emile levisetti', 'andrew lenchewski', 'june 6 , 2012', 'rp401', '3.95'], ['48', '2', 'imperfect storm', 'emile levisetti', 'michael rauch', 'june 13 , 2012', 'rp402', '4.14'], ['49', '3', 'a guesthouse divided', 'jay chandrasekhar', 'constance m burge & jack bernstein', 'june 20 , 2012', 'rp403', '3.87'], ['50', '4', 'dawn of the med', 'michael watkins', 'carol flint & jon sherman', 'june 27 , 2012', 'rp404', '4.18'], ['51', '5', 'you give love a bad name', 'michael rauch', 'michael rauch & jessica ball', 'july 11 , 2012', 'rp405', '4.15'], ['52', '6', 'about face', 'matthew penn', 'constance m burge', 'july 18 , 2012', 'rp406', '4.25'], ['53', '7', 'fools russian', 'allison liddi - brown', 'carol flint', 'july 25 , 2012', 'rp407', '3.92'], ['54', '8', 'manimal', 'mark feuerstein', 'jon sherman', 'august 1 , 2012', 'rp408', '2.96'], ['55', '9', 'business and pleasure', 'constantine makris', 'andrew lenchewski & jeff drayer', 'august 15 , 2012', 'rp409', '3.95'], ['56', '10', "who 's your daddy", 'michael watkins', 'michael rauch & jon sherman', 'august 22 , 2012', 'rp410', '3.91'], ['58', '12', 'hurts like a mother', 'tawnia mckiernan', 'jessica ball & aubrey karr', 'september 5 , 2012', 'rp412', '3.59']] |
longyan | https://en.wikipedia.org/wiki/Longyan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1204998-2.html.csv | superlative | xinluo district has the highest density of all districts and counties in longyan . | {'scope': 'all', 'col_superlative': '8', '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', 'density'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; density }'}, 'english name'], 'result': 'xinluo district', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; density } ; english name }'}, 'xinluo district'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; density } ; english name } ; xinluo district } = true', 'tointer': 'select the row whose density record of all rows is maximum . the english name record of this row is xinluo district .'} | eq { hop { argmax { all_rows ; density } ; english name } ; xinluo district } = true | select the row whose density record of all rows is maximum . the english name record of this row is xinluo district . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'density_5': 5, 'english name_6': 6, 'xinluo district_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'density_5': 'density', 'english name_6': 'english name', 'xinluo district_7': 'xinluo district'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'density_5': [0], 'english name_6': [1], 'xinluo district_7': [2]} | ['english name', 'simplified', 'traditional', 'pinyin', 'hakka', 'area', 'population', 'density'] | [['xinluo district', '新罗区', '新羅區', 'xīnluó qū', 'sîn - lò - khî', '2685', '662429', '247'], ['zhangping city', '漳平市', '漳平市', 'zhāngpíng shì', 'chông - phìn - sṳ', '2975', '240194', '81'], ['changting county', '长汀县', '長汀縣', 'chángtīng xiàn', 'tshòng - tin - yen', '3099', '393390', '127'], ['yongding county', '永定县', '永定縣', 'yǒngdìng xiàn', 'yún - thin - yen', '2216', '362658', '164'], ['shanghang county', '上杭县', '上杭縣', 'shàngháng xiàn', 'sông - hông - yen', '2879', '374047', '130'], ['wuping county', '武平县', '武平縣', 'wǔpíng xiàn', 'vú - phìn - yen', '2630', '278182', '106'], ['liancheng county', '连城县', '連城縣', 'liánchéng xiàn', 'lièn - sàng - yen', '2596', '248645', '96']] |
1968 vfl season | https://en.wikipedia.org/wiki/1968_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10808933-5.html.csv | majority | the majority of the games played in the 1968 vfl season had more than 15000 fans present . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '15000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'crowd', '15000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than 15000 .', 'tostr': 'most_greater { all_rows ; crowd ; 15000 } = true'} | most_greater { all_rows ; crowd ; 15000 } = true | for the crowd records of all rows , most of them are greater than 15000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '15000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '15000_4': '15000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '15000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '6.13 ( 49 )', 'st kilda', '9.7 ( 61 )', 'arden street oval', '14409', '11 may 1968'], ['essendon', '16.16 ( 112 )', 'fitzroy', '11.15 ( 81 )', 'windy hill', '18500', '11 may 1968'], ['collingwood', '17.11 ( 113 )', 'hawthorn', '11.16 ( 82 )', 'victoria park', '20688', '11 may 1968'], ['carlton', '16.15 ( 111 )', 'footscray', '5.9 ( 39 )', 'princes park', '14490', '11 may 1968'], ['south melbourne', '8.10 ( 58 )', 'richmond', '13.25 ( 103 )', 'lake oval', '17783', '11 may 1968'], ['melbourne', '9.9 ( 63 )', 'geelong', '10.10 ( 70 )', 'mcg', '31862', '11 may 1968']] |
economy of south america | https://en.wikipedia.org/wiki/Economy_of_South_America | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1222653-10.html.csv | unique | ecuador is the only country in south america in which an equal exchange rate between their currency and the american dollar exists . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', '1 usd =', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1 usd = record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; 1 usd = ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; 1 usd = ; 1 } }', 'tointer': 'select the rows whose 1 usd = 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', '1 usd =', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1 usd = record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; 1 usd = ; 1 }'}, 'country'], 'result': 'ecuador', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; 1 usd = ; 1 } ; country }'}, 'ecuador'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; 1 usd = ; 1 } ; country } ; ecuador }', 'tointer': 'the country record of this unqiue row is ecuador .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; 1 usd = ; 1 } } ; eq { hop { filter_eq { all_rows ; 1 usd = ; 1 } ; country } ; ecuador } } = true', 'tointer': 'select the rows whose 1 usd = record is equal to 1 . there is only one such row in the table . the country record of this unqiue row is ecuador .'} | and { only { filter_eq { all_rows ; 1 usd = ; 1 } } ; eq { hop { filter_eq { all_rows ; 1 usd = ; 1 } ; country } ; ecuador } } = true | select the rows whose 1 usd = record is equal to 1 . there is only one such row in the table . the country record of this unqiue row is ecuador . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, '1 usd =_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'country_9': 9, 'ecuador_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', '1 usd =_7': '1 usd =', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'country_9': 'country', 'ecuador_10': 'ecuador'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], '1 usd =_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'country_9': [2], 'ecuador_10': [3]} | ['country', 'currency', '1 euro =', '1 usd =', 'central bank'] | [['argentina', 'argentine peso ( ars )', '5.72079', '4.34950', 'central bank of argentina'], ['bolivia', 'bolivian boliviano ( bob )', '9.02081', '6.86000', 'central bank of bolivia'], ['brazil', 'brazilian real ( brl )', '2.25592', '1.71577', 'central bank of brazil'], ['chile', 'chilean peso ( clp )', '635.134', '483.050', 'central bank of chile'], ['colombia', 'colombian peso ( cop )', '2353.40', '1790.00', 'bank of the republic'], ['ecuador', 'us dollar ( usd )', '1.46611', '1', 'federal reserve'], ['guyana', 'guyanese dollar ( gyd )', '264.192', '200.950', 'bank of guyana'], ['paraguay', 'paraguayan guaraní ( pyg )', '4500.00', '5916.27', 'central bank of paraguay'], ['peru', 'peruvian nuevo sol ( pen )', '3.53004', '2.68500', 'central reserve bank of peru'], ['suriname', 'surinamese dollar ( srd )', '4.27296', '3.25000', 'central bank of suriname'], ['uruguay', 'uruguayan peso ( uyu )', '25.3797', '19.3000', 'central bank of uruguay'], ['venezuela', 'venezuelan bolívar fuerte ( vef )', '5.65462', '4.30000', 'central bank of venezuela']] |
eurobasket 1965 | https://en.wikipedia.org/wiki/EuroBasket_1965 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13841481-3.html.csv | count | in eurobasket 1965 , when there were move than 4 wins , there were two times when there were 2 losses . | {'scope': 'subset', 'criterion': 'equal', 'value': '2', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '4'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'wins', '4'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; wins ; 4 }', 'tointer': 'select the rows whose wins record is greater than 4 .'}, 'loses', '2'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose wins record is greater than 4 . among these rows , select the rows whose loses record is equal to 2 .', 'tostr': 'filter_eq { filter_greater { all_rows ; wins ; 4 } ; loses ; 2 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater { all_rows ; wins ; 4 } ; loses ; 2 } }', 'tointer': 'select the rows whose wins record is greater than 4 . among these rows , select the rows whose loses record is equal to 2 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater { all_rows ; wins ; 4 } ; loses ; 2 } } ; 2 } = true', 'tointer': 'select the rows whose wins record is greater than 4 . among these rows , select the rows whose loses record is equal to 2 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_greater { all_rows ; wins ; 4 } ; loses ; 2 } } ; 2 } = true | select the rows whose wins record is greater than 4 . among these rows , select the rows whose loses record is equal to 2 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'wins_6': 6, '4_7': 7, 'loses_8': 8, '2_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'wins_6': 'wins', '4_7': '4', 'loses_8': 'loses', '2_9': '2', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'wins_6': [0], '4_7': [0], 'loses_8': [1], '2_9': [1], '2_10': [3]} | ['pos', 'matches', 'wins', 'loses', 'results', 'points', 'diff'] | [['1', '7', '7', '0', '546:370', '14', '+ 176'], ['2', '7', '5', '2', '487:466', '10', '+ 21'], ['3', '7', '5', '2', '522:443', '10', '+ 79'], ['4', '7', '4', '3', '395:439', '8', '46'], ['5', '7', '3', '4', '394:458', '6', '64'], ['6', '7', '2', '5', '389:454', '4', '65'], ['7', '7', '2', '5', '477:464', '4', '+ 13'], ['8', '7', '0', '7', '364:478', '0', '114']] |
1930 vfl season | https://en.wikipedia.org/wiki/1930_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10767641-9.html.csv | aggregation | the average crowd attendance for games in the 1930 vfl season was 17724 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '17724', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '17724', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '17724'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 17724 } = true', 'tointer': 'the average of the crowd record of all rows is 17724 .'} | round_eq { avg { all_rows ; crowd } ; 17724 } = true | the average of the crowd record of all rows is 17724 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '17724_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '17724_5': '17724'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '17724_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '5.13 ( 43 )', 'richmond', '14.20 ( 104 )', 'arden street oval', '11000', '28 june 1930'], ['geelong', '14.12 ( 96 )', 'south melbourne', '11.6 ( 72 )', 'corio oval', '9000', '28 june 1930'], ['fitzroy', '18.11 ( 119 )', 'hawthorn', '13.17 ( 95 )', 'brunswick street oval', '11000', '28 june 1930'], ['melbourne', '17.12 ( 114 )', 'essendon', '11.22 ( 88 )', 'mcg', '28344', '28 june 1930'], ['footscray', '5.14 ( 44 )', 'collingwood', '19.10 ( 124 )', 'western oval', '14000', '28 june 1930'], ['st kilda', '12.5 ( 77 )', 'carlton', '13.14 ( 92 )', 'junction oval', '33000', '28 june 1930']] |
1983 tampa bay buccaneers season | https://en.wikipedia.org/wiki/1983_Tampa_Bay_Buccaneers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11440693-2.html.csv | count | 3 of the games of the '83 tampa bay buccaneers season resulted in overtime . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'ot', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'ot'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to ot .', 'tostr': 'filter_eq { all_rows ; result ; ot }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; ot } }', 'tointer': 'select the rows whose result record fuzzily matches to ot . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; ot } } ; 3 } = true', 'tointer': 'select the rows whose result record fuzzily matches to ot . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; result ; ot } } ; 3 } = true | select the rows whose result record fuzzily matches to ot . 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, 'result_5': 5, 'ot_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', 'result_5': 'result', 'ot_6': 'ot', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'ot_6': [0], '3_7': [2]} | ['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'] | [['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'], ['1', 'september 4 , 1983', 'detroit lions', 'l 11 - 0', '1:00', 'tampa stadium', '62154', '0 - 1'], ['2', 'september 11 , 1983', 'chicago bears', 'l 17 - 10', '1:00', 'soldier field', '58156', '0 - 2'], ['3', 'september 18 , 1983', 'minnesota vikings', 'l 19 - 16 ot', '4:00', 'tampa stadium', '57567', '0 - 3'], ['4', 'september 25 , 1983', 'cincinnati bengals', 'l 23 - 17', '1:00', 'tampa stadium', '56023', '0 - 4'], ['5', 'october 2 , 1983', 'green bay packers', 'l 55 - 14', '1:00', 'lambeau field', '54272', '0 - 5'], ['6', 'october 9 , 1983', 'dallas cowboys', 'l 27 - 24 ot', '4:00', 'texas stadium', '63308', '0 - 6'], ['7', 'october 16 , 1983', 'st louis cardinals', 'l 34 - 27', '1:00', 'tampa stadium', '48224', '0 - 7'], ['8', 'october 23 , 1983', 'new orleans saints', 'l 24 - 21', '4:00', 'tampa stadium', '48242', '0 - 8'], ['9', 'october 30 , 1983', 'pittsburgh steelers', 'l 17 - 12', '1:00', 'three rivers stadium', '57648', '0 - 9'], ['10', 'november 6 , 1983', 'minnesota vikings', 'w 17 - 12', '1:00', 'hubert h humphrey metrodome', '59239', '1 - 9'], ['11', 'november 13 , 1983', 'cleveland browns', 'l 20 - 0', '1:00', 'cleveland stadium', '56091', '1 - 10'], ['12', 'november 20 , 1983', 'chicago bears', 'l 27 - 0', '1:00', 'tampa stadium', '36816', '1 - 11'], ['13', 'november 27 , 1983', 'houston oilers', 'w 33 - 24', '1:00', 'tampa stadium', '38625', '2 - 11'], ['14', 'december 4 , 1983', 'san francisco 49ers', 'l 35 - 21', '4:00', 'candlestick park', '49773', '2 - 12'], ['15', 'december 12 , 1983', 'green bay packers', 'l 12 - 9 ot', '9:00', 'tampa stadium', '50763', '2 - 13'], ['16', 'december 18 , 1983', 'detroit lions', 'l 23 - 20', '4:00', 'pontiac silverdome', '78392', '2 - 14']] |
mahendra singh dhoni | https://en.wikipedia.org/wiki/Mahendra_Singh_Dhoni | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1695229-6.html.csv | aggregation | mahendra singh dhoni scored an average of 143 runs . | {'scope': 'all', 'col': '1', 'type': 'average', 'result': '143', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'runs'], 'result': '143', 'ind': 0, 'tostr': 'avg { all_rows ; runs }'}, '143'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; runs } ; 143 } = true', 'tointer': 'the average of the runs record of all rows is 143 .'} | round_eq { avg { all_rows ; runs } ; 143 } = true | the average of the runs record of all rows is 143 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'runs_4': 4, '143_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'runs_4': 'runs', '143_5': '143'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'runs_4': [0], '143_5': [1]} | ['runs', 'match', 'stadium', 'city / country', 'year'] | [['runs', 'match', 'stadium', 'city / country', 'year'], ['148', '5', 'iqbal stadium', 'faisalabad , pakistan', '2006'], ['110', '38', 'sardar patel stadium', 'ahmedabad , india', '2009'], ['100', '40', 'brabourne stadium', 'mumbai , india', '2009'], ['132', '42', 'eden gardens', 'kolkata , india', '2010'], ['144', '63', 'eden gardens', 'kolkata , india', '2011'], ['224', '74', 'ma chidambaram stadium', 'chennai , india', '2013']] |
amber heard | https://en.wikipedia.org/wiki/Amber_Heard | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10784468-3.html.csv | count | amber heard won a total of 3 awards that she was nominated for . | {'scope': 'all', 'criterion': 'equal', 'value': 'won', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to won .', 'tostr': 'filter_eq { all_rows ; result ; won }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; won } }', 'tointer': 'select the rows whose result record fuzzily matches to won . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; won } } ; 3 } = true', 'tointer': 'select the rows whose result record fuzzily matches to won . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; result ; won } } ; 3 } = true | select the rows whose result record fuzzily matches to won . 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, 'result_5': 5, 'won_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', 'result_5': 'result', 'won_6': 'won', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'won_6': [0], '3_7': [2]} | ['year', 'nominated work', 'event', 'award', 'result'] | [['2008', 'herself', 'young hollywood awards', 'breakthrough performance award', 'won'], ['2009', 'zombieland', 'detroit film critics society awards', 'best ensemble', 'nominated'], ['2010', 'herself', 'mtv movie awards', 'best scared - as - st performance', 'nominated'], ['2010', 'herself', 'dallas international film festival', 'dallas star award', 'won'], ['2011', 'the rum diary', 'hollywood film festival', 'spotlight award', 'won']] |
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