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ambala ( lok sabha constituency ) | https://en.wikipedia.org/wiki/Ambala_%28Lok_Sabha_constituency%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17922000-1.html.csv | count | in the district of ambala , only two constituencies had a number of electorates ( 2009 ) exceeding 150000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '150000', 'result': '2', 'col': '5', 'subset': {'col': '5', 'criterion': 'greater_than', 'value': '150000'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'number of electorates ( 2009 )', '150000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; number of electorates ( 2009 ) ; 150000 }', 'tointer': 'select the rows whos... | eq { count { filter_greater { filter_greater { all_rows ; number of electorates ( 2009 ) ; 150000 } ; number of electorates ( 2009 ) ; 150000 } } ; 2 } = true | select the rows whose number of electorates ( 2009 ) record is greater than 150000 . among these rows , select the rows whose number of electorates ( 2009 ) record is greater than 150000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'number of electorates (2009)_6': 6, '150000_7': 7, 'number of electorates (2009)_8': 8, '150000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'number of electorates (2009)_6': 'number of electorates ( 2009 )', '150000_7': '150000', 'number of electorates (2009)_8': 'number of electorates ( 2009 )', '1500... | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'number of electorates (2009)_6': [0], '150000_7': [0], 'number of electorates (2009)_8': [1], '150000_9': [1], '2_10': [3]} | ['constituency number', 'name', 'reserved for ( sc / st / none )', 'district', 'number of electorates ( 2009 )'] | [['1', 'kalka', 'none', 'panchkula', '114353'], ['2', 'panchkula', 'none', 'panchkula', '130932'], ['3', 'naraingarh', 'none', 'ambala', '133850'], ['4', 'ambala cantonment', 'none', 'ambala', '134401'], ['5', 'ambala city', 'none', 'ambala', '172404'], ['6', 'mulana', 'sc', 'ambala', '157696'], ['7', 'sadhaura', 'sc',... |
little league world series ( new england region ) | https://en.wikipedia.org/wiki/Little_League_World_Series_%28New_England_Region%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13011547-1.html.csv | majority | in the little league world series during the years 2001 to 2012 , lincoln ll won most often in rhode island . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'lincoln ll lincoln', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'rhode island', 'lincoln ll lincoln'], 'result': True, 'ind': 0, 'tointer': 'for the rhode island records of all rows , most of them fuzzily match to lincoln ll lincoln .', 'tostr': 'most_eq { all_rows ; rhode island ; lincoln ll lincoln } = true'} | most_eq { all_rows ; rhode island ; lincoln ll lincoln } = true | for the rhode island records of all rows , most of them fuzzily match to lincoln ll lincoln . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'rhode island_3': 3, 'lincoln ll lincoln_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'rhode island_3': 'rhode island', 'lincoln ll lincoln_4': 'lincoln ll lincoln'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'rhode island_3': [0], 'lincoln ll lincoln_4': [0]} | ['year', 'connecticut', 'maine', 'massachusetts', 'new hampshire', 'rhode island', 'vermont'] | [['2001', 'yalesville ll wallingford', 'lincoln county ll damariscotta', 'pittsfield south ll pittsfield', 'manchester east ll manchester', 'lincoln ll lincoln', 'south burlington ll south burlington'], ['2002', 'orange ll orange', 'westbrook ll westbrook', 'jesse burkett ll worcester', 'portsmouth ll portsmouth', 'por... |
cruizer - class brig - sloop | https://en.wikipedia.org/wiki/Cruizer-class_brig-sloop | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16304334-5.html.csv | unique | the magnet cruizer-class brig-sloop is the only one that had a fate of being wrecked . | {'scope': 'all', 'row': '9', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'wrecked', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'fate', 'wrecked'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose fate record fuzzily matches to wrecked .', 'tostr': 'filter_eq { all_rows ; fate ; wrecked }'}], 'result': True, 'ind': 1, 'tostr': 'only { fi... | and { only { filter_eq { all_rows ; fate ; wrecked } } ; eq { hop { filter_eq { all_rows ; fate ; wrecked } ; name } ; magnet } } = true | select the rows whose fate record fuzzily matches to wrecked . there is only one such row in the table . the name record of this unqiue row is magnet . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'fate_7': 7, 'wrecked_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'magnet_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'fate_7': 'fate', 'wrecked_8': 'wrecked', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'magnet_10': 'magnet'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'fate_7': [0], 'wrecked_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'magnet_10': [3]} | ['name', 'ordered', 'builder', 'launched', 'fate'] | [['derwent', '1 october 1806', 'isaac blackburn , turnchapel , plymouth', '23 may 1807', 'sold 1817'], ['eclair', '1 october 1806', 'matthew warren , brightlingsea , essex', '8 july 1807', 'broken up 1831'], ['eclipse', '1 october 1806', 'john king , dover', '4 august 1807', 'sold for mercantile use 1815'], ['barracout... |
list of rizzoli & isles episodes | https://en.wikipedia.org/wiki/List_of_Rizzoli_%26_Isles_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27969432-2.html.csv | aggregation | the rizzoli & isles episodes has a total of 62.28 million viewers . | {'scope': 'all', 'col': '7', 'type': 'sum', 'result': '62.28', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'us viewers ( in millions )'], 'result': '62.28', 'ind': 0, 'tostr': 'sum { all_rows ; us viewers ( in millions ) }'}, '62.28'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; us viewers ( in millions ) } ; 62.28 } = true', 'tointer': '... | round_eq { sum { all_rows ; us viewers ( in millions ) } ; 62.28 } = true | the sum of the us viewers ( in millions ) record of all rows is 62.28 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'us viewers (in millions)_4': 4, '62.28_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'us viewers (in millions)_4': 'us viewers ( in millions )', '62.28_5': '62.28'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'us viewers (in millions)_4': [0], '62.28_5': [1]} | ['no in series', 'title', 'directed by', 'written by', 'original air date', 'production', 'us viewers ( in millions )'] | [['1', 'see one do one teach one', 'michael m robin', 'janet tamaro', 'july 12 , 2010', '296014', '7.55'], ['2', 'boston strangler redux', 'michael m robin', 'janet tamaro', 'july 19 , 2010', '2 m5451', '7.27'], ['3', 'sympathy for the devil', 'roxann dawson', 'joel fields', 'july 26 , 2010', '2 m5452', '6.55'], ['4', ... |
arkansas highway 60 | https://en.wikipedia.org/wiki/Arkansas_Highway_60 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18506777-1.html.csv | ordinal | the aplin has the largest distance in the arkansas highway 60 location sections . | {'row': '9', 'col': '3', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'distance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; distance ; 1 }'}, 'location'], 'result': 'aplin', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; distance ; 1 } ; location }'}, 'aplin'], ... | eq { hop { nth_argmax { all_rows ; distance ; 1 } ; location } ; aplin } = true | select the row whose distance record of all rows is 1st maximum . the location record of this row is aplin . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'distance_5': 5, '1_6': 6, 'location_7': 7, 'aplin_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', 'distance_5': 'distance', '1_6': '1', 'location_7': 'location', 'aplin_8': 'aplin'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'distance_5': [0], '1_6': [0], 'location_7': [1], 'aplin_8': [2]} | ['county', 'location', 'distance', 'total', 'notes'] | [['faulkner', 'conway', '0.0', '0.0', 'eastern terminus'], ['faulkner', 'conway', '1.5', '1.5', '1.8 mile spur to office of emergency services'], ['line', 'county line', '5.5', '7.0', 'toad suck ferry lock & dam'], ['perry', 'bigelow', '7.7', '14.7', 'converge with ar 113'], ['perry', 'houston', '3.8', '18.5', 'north e... |
phoenix suns all - time roster | https://en.wikipedia.org/wiki/Phoenix_Suns_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11482079-8.html.csv | ordinal | lamar green was the third earliest player to join the phoenix suns . | {'row': '16', 'col': '3', 'order': '3', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'from', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; from ; 3 }'}, 'player'], 'result': 'lamar green', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; from ; 3 } ; player }'}, 'lamar green'], 'res... | eq { hop { nth_argmin { all_rows ; from ; 3 } ; player } ; lamar green } = true | select the row whose from record of all rows is 3rd minimum . the player record of this row is lamar green . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'from_5': 5, '3_6': 6, 'player_7': 7, 'lamar green_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', 'from_5': 'from', '3_6': '3', 'player_7': 'player', 'lamar green_8': 'lamar green'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'from_5': [0], '3_6': [0], 'player_7': [1], 'lamar green_8': [2]} | ['player', 'pos', 'from', 'school / country', 'rebs', 'asts'] | [['rubén garcés', 'pf', '2000', 'providence', '22', '4'], ['diante garrett', 'g', '2012', 'iowa state', '15', '31'], ['pat garrity', 'pf', '1998', 'notre dame', '75', '18'], ['kenny gattison', 'pf', '1986', 'old dominion', '271', '36'], ['armen gilliam', 'pf', '1987', 'unlv', '1045', '132'], ['gordan giriček', 'g / f',... |
2008 - 09 chicago bulls season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Chicago_Bulls_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058151-11.html.csv | count | three of the games had the united center as the location . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'united center', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'united center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to united center .', 'tostr': 'filter_eq { all_rows ; location attendance ; un... | eq { count { filter_eq { all_rows ; location attendance ; united center } } ; 3 } = true | select the rows whose location attendance record fuzzily matches to united center . 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, 'location attendance_5': 5, 'united center_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', 'location attendance_5': 'location attendance', 'united center_6': 'united center', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'united center_6': [0], '3_7': [2]} | ['game', 'date', 'team', 'score', 'location attendance', 'series'] | [['1', 'april 18', 'boston', 'w 105 - 103 ( ot )', 'td banknorth garden 18624', '1 - 0'], ['2', 'april 20', 'boston', 'l 115 - 118 ( ot )', 'td banknorth garden 18624', '1 - 1'], ['3', 'april 23', 'boston', 'l 86 - 107 ( ot )', 'united center 23072', '1 - 2'], ['4', 'april 26', 'boston', 'w 121 - 118 ( 2ot )', 'united ... |
bo ' ness and kinneil railway | https://en.wikipedia.org/wiki/Bo%27ness_and_Kinneil_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1174877-18.html.csv | comparative | both the naval store no. 161 and the briggs dundee no. 20 at the bo ' ness kinneil railway were built in the year 1918 . | {'row_1': '4', 'row_2': '5', 'col': '5', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'number & name', 'naval store no 161'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose number & name record fuzzily matches to naval store no 161 .', 'tostr': 'filter_eq { all_rows ;... | and { eq { hop { filter_eq { all_rows ; number & name ; naval store no 161 } ; date } ; hop { filter_eq { all_rows ; number & name ; briggs , dundee no 20 } ; date } } ; and { eq { hop { filter_eq { all_rows ; number & name ; naval store no 161 } ; date } ; 1918 } ; eq { hop { filter_eq { all_rows ; number & name ; bri... | select the rows whose number & name record fuzzily matches to naval store no 161 . take the date record of this row . select the rows whose number & name record fuzzily matches to briggs , dundee no 20 . take the date record of this row . the first record is equal to the second record . the date record of the first row... | 13 | 9 | {'and_8': 8, 'result_9': 9, 'eq_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'number & name_11': 11, 'naval store no 161_12': 12, 'date_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'number & name_15': 15, 'briggs , dundee no 20_16': 16, 'date_17': 17, 'and_7': 7, 'eq_5': 5, '1918... | {'and_8': 'and', 'result_9': 'true', 'eq_4': 'eq', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'number & name_11': 'number & name', 'naval store no 161_12': 'naval store no 161', 'date_13': 'date', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all... | {'and_8': [9], 'result_9': [], 'eq_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'number & name_11': [0], 'naval store no 161_12': [0], 'date_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'number & name_15': [1], 'briggs , dundee no 20_16': [1], 'date_17': [3], '... | ['number & name', 'description', 'current status', 'livery', 'date'] | [['scottish tar distillers no 78', 'rectangular tanker', 'static display in the museum', 'black', '1877'], ['oakbank oil company no 13', '10t tanker', 'static display in the museum', 'black', '1894'], ['no a43', 'shell bp tanker', 'static display in the museum', 'black', '1897'], ['naval store no 161', '14t tanker', 's... |
1979 world figure skating championships | https://en.wikipedia.org/wiki/1979_World_Figure_Skating_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11312764-5.html.csv | unique | at the 1979 world figure skating championships , the only skaters from canada were barbara underhill and paul martini . | {'scope': 'all', 'row': '11', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'canada', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; nation ; canada }'}], 'result': True, 'ind': 1, 'tostr': 'only {... | and { only { filter_eq { all_rows ; nation ; canada } } ; eq { hop { filter_eq { all_rows ; nation ; canada } ; name } ; barbara underhill / paul martini } } = true | select the rows whose nation record fuzzily matches to canada . there is only one such row in the table . the name record of this unqiue row is barbara underhill / paul martini . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nation_7': 7, 'canada_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'barbara underhill / paul martini_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nation_7': 'nation', 'canada_8': 'canada', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'barbara underhill / paul martini_10': 'barbara underhill / paul martini'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nation_7': [0], 'canada_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'barbara underhill / paul martini_10': [3]} | ['rank', 'name', 'nation', 'points', 'places'] | [['1', 'tai babilonia / randy gardner', 'united states', '144.54', '12'], ['2', 'marina cherkasova / sergei shakhrai', 'soviet union', '142.22', '16'], ['3', 'sabine baeãÿ / tassilo thierbach', 'east germany', '137.74', '32'], ['4', 'irina vorobieva / igor lisovski', 'soviet union', '138.72', '33'], ['5', 'marina pesto... |
1965 american football league draft | https://en.wikipedia.org/wiki/1965_American_Football_League_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18652198-19.html.csv | majority | in the 1965 afl draft , a majority of players taken were tackles . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'tackle', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'position', 'tackle'], 'result': True, 'ind': 0, 'tointer': 'for the position records of all rows , most of them fuzzily match to tackle .', 'tostr': 'most_eq { all_rows ; position ; tackle } = true'} | most_eq { all_rows ; position ; tackle } = true | for the position records of all rows , most of them fuzzily match to tackle . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'position_3': 3, 'tackle_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'position_3': 'position', 'tackle_4': 'tackle'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'position_3': [0], 'tackle_4': [0]} | ['pick', 'team', 'player', 'position', 'college'] | [['145', 'denver broncos', 'ron oelschlager', 'halfback', 'kansas'], ['146', 'houston oilers', 'frank fox', 'tackle', 'sam houston state'], ['147', 'oakland raiders', 'frank mcclendon', 'tackle', 'alabama'], ['148', 'new york jets', 'mitch dudek', 'tackle', 'xavier'], ['149', 'kansas city chiefs', 'mike alford', 'cente... |
bears - packers rivalry | https://en.wikipedia.org/wiki/Bears%E2%80%93Packers_rivalry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11650849-7.html.csv | aggregation | the bears - packers rivalry had an average attendance of about 35000 fans per game from 1950-1959 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '35000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '35000', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '35000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 35000 } = true', 'tointer': 'the average of the attendance record of all rows... | round_eq { avg { all_rows ; attendance } ; 35000 } = true | the average of the attendance record of all rows is 35000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '35000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '35000_5': '35000'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '35000_5': [1]} | ['year', 'date', 'winner', 'result', 'loser', 'attendance', 'location'] | [['1950', 'sunday , october 1', 'green bay packers', '31 - 21', 'chicago bears', '24893', 'green bay'], ['1950', 'sunday , october 15', 'chicago bears', '28 - 14', 'green bay packers', '51065', 'chicago'], ['1951', 'sunday , september 30', 'chicago bears', '31 - 20', 'green bay packers', '24666', 'green bay'], ['1951',... |
2008 french road cycling cup | https://en.wikipedia.org/wiki/2008_French_Road_Cycling_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15930479-1.html.csv | count | there was a total of 14 events in the 2008 cup . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '14', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'event'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record is arbitrary .', 'tostr': 'filter_all { all_rows ; event }'}], 'result': '14', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; event } }',... | eq { count { filter_all { all_rows ; event } } ; 14 } = true | select the rows whose event record is arbitrary . the number of such rows is 14 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'event_5': 5, '14_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'event_5': 'event', '14_6': '14'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'event_5': [0], '14_6': [2]} | ['date', 'event', 'winner', 'team', 'series leader'] | [['february 24', 'tour du haut var', 'davide rebellin ( ita )', 'gerolsteiner', 'rinaldo nocentini ( ita )'], ['march 23', 'cholet - pays de loire', 'janek tombak ( est )', 'mitsubishi - jartazi', 'rinaldo nocentini ( ita )'], ['april 6', 'grand prix de rennes', 'mikhaylo khalilov ( ukr )', 'ceramica flaminia - bossini... |
1963 vfl season | https://en.wikipedia.org/wiki/1963_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10783853-1.html.csv | aggregation | in the 1963 vfl season , games drew 174 , 580 fans to various venues . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '174 , 580', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '174 , 580', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '174 , 580'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 174 , 580 } = true', 'tointer': 'the sum of the crowd record of all rows is 174 , 58... | round_eq { sum { all_rows ; crowd } ; 174 , 580 } = true | the sum of the crowd record of all rows is 174 , 580 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '174, 580_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '174, 580_5': '174 , 580'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '174, 580_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '16.26 ( 122 )', 'south melbourne', '9.9 ( 63 )', 'kardinia park', '33953', '20 april 1963'], ['st kilda', '13.5 ( 83 )', 'melbourne', '9.11 ( 65 )', 'junction oval', '31300', '20 april 1963'], ['north melbourne', '11.11 ( 77 )', 'footscray', '5.10 ( 40 )', 'arden street oval', '21960', '20 april 1963'], [... |
1955 - 56 segunda división | https://en.wikipedia.org/wiki/1955%E2%80%9356_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17608926-2.html.csv | comparative | real oviedo recorded more wins than ca osasuna in the 1955 - 56 segunda división . | {'row_1': '2', 'row_2': '1', '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', 'club', 'real oviedo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to real oviedo .', 'tostr': 'filter_eq { all_rows ; club ; real oviedo }'}, 'wins'], 'result': None, 'i... | greater { hop { filter_eq { all_rows ; club ; real oviedo } ; wins } ; hop { filter_eq { all_rows ; club ; ca osasuna } ; wins } } = true | select the rows whose club record fuzzily matches to real oviedo . take the wins record of this row . select the rows whose club record fuzzily matches to ca osasuna . take the wins record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'club_7': 7, 'real oviedo_8': 8, 'wins_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'club_11': 11, 'ca osasuna_12': 12, 'wins_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'club_7': 'club', 'real oviedo_8': 'real oviedo', 'wins_9': 'wins', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'club_11': 'club', 'ca osasuna_12'... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'club_7': [0], 'real oviedo_8': [0], 'wins_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'club_11': [1], 'ca osasuna_12': [1], 'wins_13': [3]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'ca osasuna', '30', '42', '17', '8', '5', '76', '33', '+ 43'], ['2', 'real oviedo', '30', '41', '18', '5', '7', '78', '33', '+ 45'], ['3', 'real zaragoza', '30', '40', '18', '4', '8', '57', '27', '+ 30'], ['4', 'caudal deportivo', '30', '34', '13', '8', '9', '49', '37', '+ 12'], ['5', 'cd sabadell cf', '30', '33... |
1933 pittsburgh pirates ( nfl ) season | https://en.wikipedia.org/wiki/1933_Pittsburgh_Pirates_%28NFL%29_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14683281-1.html.csv | superlative | in the 1933 pittsburgh pirates ( nfl ) season , the earliest game at forbes field was on sunday , september 20th . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'forbes field'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'forbes field'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; game site ; forbes field }', 'tointer': 'select the rows whose game site record fuzzily matches to forbes field .'}, 'date'], 'result':... | eq { min { filter_eq { all_rows ; game site ; forbes field } ; date } ; sunday september 20 } = true | select the rows whose game site record fuzzily matches to forbes field . the minimum date record of these rows is sunday september 20 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'game site_5': 5, 'forbes field_6': 6, 'date_7': 7, 'sunday september 20_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'game site_5': 'game site', 'forbes field_6': 'forbes field', 'date_7': 'date', 'sunday september 20_8': 'sunday september 20'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'game site_5': [0], 'forbes field_6': [0], 'date_7': [1], 'sunday september 20_8': [2]} | ['week', 'date', 'opponent', 'result', 'game site'] | [['1', 'sunday september 20', 'new york giants', 'l 23 - 2', 'forbes field'], ['2', 'sunday september 27', 'chicago cardinals', 'w 14 - 13', 'forbes field'], ['3', 'sunday october 4', 'boston redskins', 'l 21 - 6', 'forbes field'], ['4', 'sunday october 11', 'cincinnati reds', 'w 17 - 3', 'forbes field'], ['5', 'sunday... |
eiza gonzález | https://en.wikipedia.org/wiki/Eiza_Gonz%C3%A1lez | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16264878-4.html.csv | count | elza gonzalez won six awards for her participation in movies . | {'scope': 'all', 'criterion': 'equal', 'value': 'won', 'result': '6', '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': '6', 'ind': 1, 'tostr': 'count { filter_e... | eq { count { filter_eq { all_rows ; result ; won } } ; 6 } = true | select the rows whose result record fuzzily matches to won . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'won_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'won_6': 'won', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'won_6': [0], '6_7': [2]} | ['year', 'award', 'nominated work', 'category', 'result'] | [['2007', 'premios oye !', 'lola érase una vez ( album )', 'artista revelacion', 'nominated'], ['2008', 'premios tv y novelas', 'lola , érase una vez', 'actriz revelacion del año', 'won'], ['2009', 'premio lo nuestro', 'lola érase una vez ( álbum )', 'revelación pop del año', 'won'], ['2011', 'kids choice awards méxico... |
2010 - 11 danish 1st division | https://en.wikipedia.org/wiki/2010%E2%80%9311_Danish_1st_Division | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27782699-3.html.csv | unique | fc hjørring is the only team whose outgoing manager left because they signed by fc fredericia . | {'scope': 'all', 'row': '7', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'signed by fc fredericia', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'signed by fc fredericia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to signed by fc fredericia .', 'tostr': 'filter_eq { all_rows ; mann... | and { only { filter_eq { all_rows ; manner of departure ; signed by fc fredericia } } ; eq { hop { filter_eq { all_rows ; manner of departure ; signed by fc fredericia } ; team } ; fc hjørring } } = true | select the rows whose manner of departure record fuzzily matches to signed by fc fredericia . there is only one such row in the table . the team record of this unqiue row is fc hjørring . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'manner of departure_7': 7, 'signed by fc fredericia_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team_9': 9, 'fc hjørring_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'manner of departure_7': 'manner of departure', 'signed by fc fredericia_8': 'signed by fc fredericia', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team_9': 'team', 'fc hjørring_10': 'fc hjørring'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'manner of departure_7': [0], 'signed by fc fredericia_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team_9': [2], 'fc hjørring_10': [3]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment', 'position in table'] | [['aarhus gf', 'erik rasmussen', 'sacked', '20 may 2010', 'peter sørensen', '1 july 2010', 'pre - season'], ['næstved bk', 'kim poulsen', 'mutual consent', '30 june 2010', 'brian flies', '1 july 2010', 'pre - season'], ['fc roskilde', 'martin jungsgaard', 'end of contract', '30 june 2010', 'carsten broe', '1 july 2010'... |
1971 all - ireland senior hurling championship | https://en.wikipedia.org/wiki/1971_All-Ireland_Senior_Hurling_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13052263-3.html.csv | unique | christy kehoe is the only player who is from wexford county . | {'scope': 'all', 'row': '10', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'wexford', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'wexford'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to wexford .', 'tostr': 'filter_eq { all_rows ; county ; wexford }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; county ; wexford } } ; eq { hop { filter_eq { all_rows ; county ; wexford } ; player } ; christy kehoe } } = true | select the rows whose county record fuzzily matches to wexford . there is only one such row in the table . the player record of this unqiue row is christy kehoe . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'county_7': 7, 'wexford_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'christy kehoe_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'county_7': 'county', 'wexford_8': 'wexford', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'christy kehoe_10': 'christy kehoe'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'county_7': [0], 'wexford_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'christy kehoe_10': [3]} | ['rank', 'player', 'county', 'tally', 'total', 'opposition'] | [['1', "michael ' babs ' keating", 'tipperary', '2 - 12', '18', 'galway'], ['2', 'eddie keher', 'kilkenny', '2 - 11', '17', 'tipperary'], ['3', 'eddie keher', 'kilkenny', '0 - 14', '14', 'london'], ['4', "michael ' babs ' keating", 'tipperary', '3 - 4', '13', 'limerick'], ['4', 'des coen', 'galway', '3 - 4', '13', 'ant... |
figure skating at the asian winter games | https://en.wikipedia.org/wiki/Figure_skating_at_the_Asian_Winter_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12573588-9.html.csv | superlative | japan won the highest number of silver medals in the asian winter games . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', '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', 'silver'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; silver }'}, 'nation'], 'result': 'japan', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; silver } ; nation }'}, 'japan'], 'result': True, 'ind': 2, 'tostr': ... | eq { hop { argmax { all_rows ; silver } ; nation } ; japan } = true | select the row whose silver record of all rows is maximum . the nation record of this row is japan . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'silver_5': 5, 'nation_6': 6, 'japan_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'silver_5': 'silver', 'nation_6': 'nation', 'japan_7': 'japan'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'silver_5': [0], 'nation_6': [1], 'japan_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'china', '13', '9', '13', '35'], ['2', 'japan', '7', '10', '7', '24'], ['3', 'uzbekistan', '1', '2', '3', '6'], ['4', 'kazakhstan', '2', '2', '0', '4'], ['5', 'north korea', '1', '0', '1', '2'], ['6', 'south korea', '0', '0', '2', '2'], ['total', 'total', '24', '23', '26', '73']] |
locomotives of the great western railway | https://en.wikipedia.org/wiki/Locomotives_of_the_Great_Western_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1169521-12.html.csv | count | beyer peacock & co has a total of 3 types of locomotives . | {'scope': 'subset', 'criterion': 'equal', 'value': 'beyer , peacock & co', 'result': '3', 'col': '1', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'beyer , peacock & co'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manufacturer', 'beyer , peacock & co'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; manufacturer ; beyer , peacock & co }', 'tointer': 'select the rows whose manufacturer ... | eq { count { filter_eq { filter_eq { all_rows ; manufacturer ; beyer , peacock & co } ; manufacturer ; beyer , peacock & co } } ; 3 } = true | select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . among these rows , select the rows whose manufacturer record fuzzily matches to beyer , peacock & co . 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, 'manufacturer_6': 6, 'beyer , peacock & co_7': 7, 'manufacturer_8': 8, 'beyer, peacock & co_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', 'manufacturer_6': 'manufacturer', 'beyer , peacock & co_7': 'beyer , peacock & co', 'manufacturer_8': 'manufacturer', 'beyer, peacock & co_9': 'beyer , peacock & co', ... | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'manufacturer_6': [0], 'beyer , peacock & co_7': [0], 'manufacturer_8': [1], 'beyer, peacock & co_9': [1], '3_10': [3]} | ['manufacturer', 'type', 'quantity', 'm & swj nos', 'gwr nos'] | [['beyer , peacock & co', '0 - 4 - 4t', '1', '15', '23'], ['beyer , peacock & co', '2 - 6 - 0', '1', '16', '24'], ['sharp , stewart & co', '4 - 4 - 4t', '2', '17 - 18', '25 , 27'], ['dübs & co', '0 - 6 - 0t', '2', '13 - 14', '825 , 843'], ['beyer , peacock & co', '0 - 6 - 0', '10', '19 - 28', '1003 - 1011 , 1013'], ['n... |
joão barbosa | https://en.wikipedia.org/wiki/Jo%C3%A3o_Barbosa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18864385-1.html.csv | ordinal | 2006 was the third year that joão barbosa drove with the rollcentre racing team . | {'row': '3', 'col': '1', 'order': '3', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'year', '3'], 'result': '2006', 'ind': 0, 'tostr': 'nth_min { all_rows ; year ; 3 }', 'tointer': 'the 3rd minimum year record of all rows is 2006 .'}, '2006'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; year ; 3... | and { eq { nth_min { all_rows ; year ; 3 } ; 2006 } ; eq { hop { nth_argmin { all_rows ; year ; 3 } ; team } ; rollcentre racing } } = true | the 3rd minimum year record of all rows is 2006 . the team record of the row with 3rd minimum year record is rollcentre racing . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'year_8': 8, '3_9': 9, '2006_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'year_12': 12, '3_13': 13, 'team_14': 14, 'rollcentre racing_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'year_8': 'year', '3_9': '3', '2006_10': '2006', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'year_12': 'year', '3_13': '3', 'team_14': 'team', 'rollcentre raci... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'year_8': [0], '3_9': [0], '2006_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'year_12': [2], '3_13': [2], 'team_14': [3], 'rollcentre racing_15': [4]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['2004', 'rollcentre racing', 'martin short rob barff', 'lmp1', '230', 'dnf', 'dnf'], ['2005', 'rollcentre racing', 'martin short vanina ickx', 'lmp1', '318', '16th', '8th'], ['2006', 'rollcentre racing', 'martin short stuart moseley', 'lmp2', '294', '20th', '5th'], ['2007', 'rollcentre racing', 'stuart hall martin sh... |
1950 - 51 fa cup | https://en.wikipedia.org/wiki/1950%E2%80%9351_FA_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17520911-6.html.csv | aggregation | the 1950-1951 fa cup saw home teams during february 's fifth round scoring a combined total of 19 . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '19', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'score'], 'result': '19', 'ind': 0, 'tostr': 'sum { all_rows ; score }'}, '19'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; score } ; 19 } = true', 'tointer': 'the sum of the score record of all rows is 19 .'} | round_eq { sum { all_rows ; score } ; 19 } = true | the sum of the score record of all rows is 19 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'score_4': 4, '19_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'score_4': 'score', '19_5': '19'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'score_4': [0], '19_5': [1]} | ['tie no', 'home team', 'score', 'away team', 'date'] | [['1', 'blackpool', '2 - 0', 'mansfield town', '10 february 1951'], ['2', 'wolverhampton wanderers', '2 - 0', 'huddersfield town', '10 february 1951'], ['3', 'sunderland', '3 - 1', 'norwich city', '10 february 1951'], ['4', 'bristol rovers', '3 - 0', 'hull city', '10 february 1951'], ['5', 'manchester united', '1 - 0',... |
1978 vfl season | https://en.wikipedia.org/wiki/1978_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10887680-20.html.csv | count | three of the venues include the word " oval . " . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'oval', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to oval .', 'tostr': 'filter_eq { all_rows ; venue ; oval }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_e... | eq { count { filter_eq { all_rows ; venue ; oval } } ; 3 } = true | select the rows whose venue record fuzzily matches to oval . 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, 'venue_5': 5, 'oval_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', 'venue_5': 'venue', 'oval_6': 'oval', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'oval_6': [0], '3_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '19.16 ( 130 )', 'melbourne', '21.10 ( 136 )', 'windy hill', '11984', '19 august 1978'], ['south melbourne', '24.11 ( 155 )', 'geelong', '26.11 ( 167 )', 'lake oval', '15259', '19 august 1978'], ['footscray', '9.17 ( 71 )', 'fitzroy', '21.13 ( 139 )', 'western oval', '12525', '19 august 1978'], ['richmond... |
1972 - 73 atlanta flames season | https://en.wikipedia.org/wiki/1972%E2%80%9373_Atlanta_Flames_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14038705-1.html.csv | unique | frank blum was the only player drafted by the atlanta flames in the 6th round . | {'scope': 'all', 'row': '6', 'col': '1', 'col_other': '3', 'criterion': 'equal', 'value': '6', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'round', '6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round record is equal to 6 .', 'tostr': 'filter_eq { all_rows ; round ; 6 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; round... | and { only { filter_eq { all_rows ; round ; 6 } } ; eq { hop { filter_eq { all_rows ; round ; 6 } ; player } ; frank blum } } = true | select the rows whose round record is equal to 6 . there is only one such row in the table . the player record of this unqiue row is frank blum . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'round_7': 7, '6_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'frank blum_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'round_7': 'round', '6_8': '6', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'frank blum_10': 'frank blum'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'round_7': [0], '6_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'frank blum_10': [3]} | ['round', 'pick', 'player', 'nationality', 'college / junior / club team'] | [['1', '2', 'jacques richard', 'canada', 'quebec remparts ( qmjhl )'], ['2', '18', 'dwight bialowas', 'canada', 'regina pats ( wcjhl )'], ['3', '34', 'jean lemieux', 'canada', 'sherbrooke castors ( qmjhl )'], ['4', '50', 'don martineau', 'canada', 'new westminster royals ( wcjhl )'], ['5', '78', 'john martin', 'canada'... |
2002 buffalo bills season | https://en.wikipedia.org/wiki/2002_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16352332-1.html.csv | unique | in the 2002 buffalo bill 's season , kevin thomas was the only cornerback . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'cornerback', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'cornerback'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to cornerback .', 'tostr': 'filter_eq { all_rows ; position ; cornerback }'}], 'result': True, 'ind': 1... | and { only { filter_eq { all_rows ; position ; cornerback } } ; eq { hop { filter_eq { all_rows ; position ; cornerback } ; player } ; kevin thomas } } = true | select the rows whose position record fuzzily matches to cornerback . there is only one such row in the table . the player record of this unqiue row is kevin thomas . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'cornerback_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'kevin thomas_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'cornerback_8': 'cornerback', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'kevin thomas_10': 'kevin thomas'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'cornerback_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'kevin thomas_10': [3]} | ['round', 'pick', 'player', 'position', 'college'] | [['1', '4', 'mike williams', 'tackle', 'texas'], ['2', '36', 'josh reed', 'wide receiver', 'lsu'], ['2', '61', 'ryan denney', 'defensive end', 'byu'], ['3', '97', 'coy wire', 'safety', 'stanford'], ['5', '139', 'justin bannan', 'defensive tackle', 'colorado'], ['6', '176', 'kevin thomas', 'cornerback', 'unlv'], ['7', '... |
1979 cincinnati bengals season | https://en.wikipedia.org/wiki/1979_Cincinnati_Bengals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17643197-2.html.csv | superlative | the game played on week 8 of the 1979 cincinnati bengals season drew the highest crowd attendance . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'week'], 'result': '8', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; week }'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq ... | eq { hop { argmax { all_rows ; attendance } ; week } ; 8 } = true | select the row whose attendance record of all rows is maximum . the week record of this row is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'week_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'week_6': 'week', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'week_6': [1], '8_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 2 , 1979', 'denver broncos', 'l 10 - 0', '74788'], ['2', 'september 9 , 1979', 'buffalo bills', 'l 51 - 24', '43504'], ['3', 'september 16 , 1979', 'new england patriots', 'l 20 - 14', '41805'], ['4', 'september 23 , 1979', 'houston oilers', 'l 30 - 27', '45615'], ['5', 'september 30 , 1979', 'dallas ... |
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 | unique | the iranian team was the only team that took over 7:00:00 to finish in men 's double sculls rowing at the 2008 summer olympics . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '3', 'criterion': 'greater_than', 'value': '7:00:00', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'time', '7:00:00'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record is greater than 7:00:00 .', 'tostr': 'filter_greater { all_rows ; time ; 7:00:00 }'}], 'result': True, 'ind': 1, 'tostr': 'only {... | and { only { filter_greater { all_rows ; time ; 7:00:00 } } ; eq { hop { filter_greater { all_rows ; time ; 7:00:00 } ; country } ; iraq } } = true | select the rows whose time record is greater than 7:00:00 . there is only one such row in the table . the country record of this unqiue row is iraq . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'time_7': 7, '7:00:00_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'country_9': 9, 'iraq_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'time_7': 'time', '7:00:00_8': '7:00:00', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'country_9': 'country', 'iraq_10': 'iraq'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'time_7': [0], '7:00:00_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'country_9': [2], 'iraq_10': [3]} | ['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 , hus... |
nfl starting quarterback playoff records | https://en.wikipedia.org/wiki/NFL_starting_quarterback_playoff_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17788889-4.html.csv | superlative | dave krieg with the seahawks had the highest number of losses as an nfl quarterback with 4 . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '7', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'losses'], 'result': '4', 'ind': 0, 'tostr': 'max { all_rows ; losses }', 'tointer': 'the maximum losses record of all rows is 4 .'}, '4'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; losses } ; 4 }', 'tointer': 'the max... | and { eq { max { all_rows ; losses } ; 4 } ; eq { hop { argmax { all_rows ; losses } ; quarterback } ; dave krieg } } = true | the maximum losses record of all rows is 4 . the quarterback record of the row with superlative losses record is dave krieg . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'losses_8': 8, '4_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'losses_11': 11, 'quarterback_12': 12, 'dave krieg_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'losses_8': 'losses', '4_9': '4', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'losses_11': 'losses', 'quarterback_12': 'quarterback', 'dave krieg_13': 'dave krieg'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'losses_8': [0], '4_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'losses_11': [2], 'quarterback_12': [3], 'dave krieg_13': [4]} | ['quarterback', 'games', 'teams', 'wins', 'losses', 'percent'] | [['brad johnson', '7', 'vikings', '0', '1', '571'], ['brad johnson', '7', 'redskins', '1', '1', '571'], ['brad johnson', '7', 'buccaneers', '3', '1', '571'], ['kerry collins', '7', 'panthers', '1', '1', '429'], ['kerry collins', '7', 'giants', '2', '2', '429'], ['kerry collins', '7', 'titans', '0', '1', '429'], ['dave ... |
2011 capital one world women 's curling championship | https://en.wikipedia.org/wiki/2011_Capital_One_World_Women%27s_Curling_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26745426-2.html.csv | count | two athletes had a shot percentage of 78 % . | {'scope': 'all', 'criterion': 'equal', 'value': '78 %', 'result': '2', 'col': '11', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'shot %', '78 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose shot % record fuzzily matches to 78 % .', 'tostr': 'filter_eq { all_rows ; shot % ; 78 % }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filte... | eq { count { filter_eq { all_rows ; shot % ; 78 % } } ; 2 } = true | select the rows whose shot % record fuzzily matches to 78 % . 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, 'shot %_5': 5, '78%_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', 'shot %_5': 'shot %', '78%_6': '78 %', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'shot %_5': [0], '78%_6': [0], '2_7': [2]} | ['country', 'skip', 'w', 'l', 'pf', 'pa', 'ends won', 'ends lost', 'blank ends', 'stolen ends', 'shot %'] | [['sweden', 'anette norberg', '9', '2', '67', '53', '40', '41', '12', '8', '73 %'], ['china', 'wang bingyu', '8', '3', '64', '43', '44', '30', '14', '16', '82 %'], ['denmark', 'lene nielsen', '7', '4', '77', '55', '47', '33', '15', '14', '78 %'], ['canada', 'amber holland', '7', '4', '68', '55', '42', '40', '12', '7', ... |
wru division five south east | https://en.wikipedia.org/wiki/WRU_Division_Five_South_East | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17625749-2.html.csv | superlative | the club with the most points was the pontyclun rfc in the wru division five south east . | {'scope': 'all', 'col_superlative': '11', 'row_superlative': '2', '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', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'club'], 'result': 'pontyclun rfc', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; club }'}, 'pontyclun rfc'], 'result': True, 'ind': ... | eq { hop { argmax { all_rows ; points } ; club } ; pontyclun rfc } = true | select the row whose points record of all rows is maximum . the club record of this row is pontyclun rfc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'club_6': 6, 'pontyclun rfc_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'club_6': 'club', 'pontyclun rfc_7': 'pontyclun rfc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'club_6': [1], 'pontyclun rfc_7': [2]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['pontyclun rfc', '20', '0', '2', '694', '191', '104', '21', '12', '2', '86'], ['cilfynydd rfc', '20', '1', '4', '635', '330', '90', '37', '10', '2', '74'], ['barry rfc', '20', '2',... |
nauru | https://en.wikipedia.org/wiki/Nauru | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21302-1.html.csv | aggregation | the average population of a district in nauru is 801.29 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '801.29', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'population ( 2005 )'], 'result': '801.29', 'ind': 0, 'tostr': 'avg { all_rows ; population ( 2005 ) }'}, '801.29'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; population ( 2005 ) } ; 801.29 } = true', 'tointer': 'the average of the... | round_eq { avg { all_rows ; population ( 2005 ) } ; 801.29 } = true | the average of the population ( 2005 ) record of all rows is 801.29 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'population (2005)_4': 4, '801.29_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'population (2005)_4': 'population ( 2005 )', '801.29_5': '801.29'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'population (2005)_4': [0], '801.29_5': [1]} | ['nr', 'district', 'former name', 'area ( ha )', 'population ( 2005 )', 'no of villages', 'density persons / ha'] | [['1', 'aiwo', 'aiue', '100', '1092', '8', '10.9'], ['2', 'anabar', 'anebwor', '143', '502', '15', '3.5'], ['3', 'anetan', 'añetañ', '100', '516', '12', '5.2'], ['4', 'anibare', 'anybody', '314', '160', '17', '0.5'], ['5', 'baiti', 'beidi', '123', '572', '15', '4.7'], ['6', 'boe', 'boi', '66', '795', '4', '12.0'], ['7'... |
akapusi qera | https://en.wikipedia.org/wiki/Akapusi_Qera | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11470402-1.html.csv | superlative | japan was the first opponent that akapusi qera has faced off against . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'opponent'], 'result': 'japan', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; opponent }'}, 'japan'], 'result': True, 'ind': 2, 'tostr': 'e... | eq { hop { argmin { all_rows ; date } ; opponent } ; japan } = true | select the row whose date record of all rows is minimum . the opponent record of this row is japan . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'opponent_6': 6, 'japan_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'opponent_6': 'opponent', 'japan_7': 'japan'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'opponent_6': [1], 'japan_7': [2]} | ['date', 'venue', 'opponent', 'result', 'competition'] | [['01 / 07 / 06', 'nagai stadium , osaka', 'japan', 'win - 15 - 29', 'pacific nations cup'], ['14 / 07 / 06', 'adelaide oval , adelaide', 'australia a', 'loss - 47 - 18', 'non - cap friendly'], ['26 / 05 / 07', 'churchill park , lautoka', 'japan', 'win - 30 - 15', 'pacific nations cup'], ['25 / 08 / 07', 'stade municip... |
vitamin k deficiency | https://en.wikipedia.org/wiki/Vitamin_K_deficiency | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20592988-1.html.csv | count | six of the conditions do not affect bleeding time as a response to the condition . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'unaffected', 'result': '6', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'bleeding time', 'unaffected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bleeding time record fuzzily matches to unaffected .', 'tostr': 'filter_eq { all_rows ; bleeding time ; unaffected }'}], 'result':... | eq { count { filter_eq { all_rows ; bleeding time ; unaffected } } ; 6 } = true | select the rows whose bleeding time record fuzzily matches to unaffected . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'bleeding time_5': 5, 'unaffected_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'bleeding time_5': 'bleeding time', 'unaffected_6': 'unaffected', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'bleeding time_5': [0], 'unaffected_6': [0], '6_7': [2]} | ['condition', 'prothrombin time', 'partial thromboplastin time', 'bleeding time', 'platelet count'] | [['vitamin k deficiency or warfarin', 'prolonged', 'normal or mildly prolonged', 'unaffected', 'unaffected'], ['disseminated intravascular coagulation', 'prolonged', 'prolonged', 'prolonged', 'decreased'], ['von willebrand disease', 'unaffected', 'prolonged or unaffected', 'prolonged', 'unaffected'], ['hemophilia', 'un... |
1998 cfl draft | https://en.wikipedia.org/wiki/1998_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16441561-6.html.csv | count | two players drafted were from the college of manitoba . | {'scope': 'all', 'criterion': 'equal', 'value': 'manitoba', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'manitoba'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to manitoba .', 'tostr': 'filter_eq { all_rows ; college ; manitoba }'}], 'result': '2', 'ind': 1, 'tostr':... | eq { count { filter_eq { all_rows ; college ; manitoba } } ; 2 } = true | select the rows whose college record fuzzily matches to manitoba . 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, 'college_5': 5, 'manitoba_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', 'college_5': 'college', 'manitoba_6': 'manitoba', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'college_5': [0], 'manitoba_6': [0], '2_7': [2]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['36', 'hamilton', 'benjie hutchison', 'dl', 'british columbia'], ['37', 'winnipeg', 'john baunemann', 'k', 'manitoba'], ['38', 'winnipeg', 'chad vath', 'lb', 'manitoba'], ['39', 'calgary', 'jodi bednarek', 'lb', 'calgary'], ['40', 'edmonton', 'adam kossack', 'ol', 'hastings college'], ['41', 'montreal', 'kelly irelan... |
2008 - 09 detroit red wings season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Red_Wings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17371135-5.html.csv | count | there were red wings games in november of the 08-09 season in which over 20,000 people attended . | {'scope': 'all', 'criterion': 'greater_than', 'value': '20,000', 'result': '5', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'attendance', '20,000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is greater than 20,000 .', 'tostr': 'filter_greater { all_rows ; attendance ; 20,000 }'}], 'result': '5', 'ind': 1, 't... | eq { count { filter_greater { all_rows ; attendance ; 20,000 } } ; 5 } = true | select the rows whose attendance record is greater than 20,000 . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '20,000_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '20,000_6': '20,000', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '20,000_6': [0], '5_7': [2]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['november 2', 'detroit', '3 - 2', 'vancouver', 'osgood', '18630', '8 - 2 - 2'], ['november 8', 'new jersey', '1 - 3', 'detroit', 'osgood', '20066', '9 - 2 - 2'], ['november 11', 'pittsburgh', '7 - 6', 'detroit', 'osgood', '20066', '9 - 2 - 3'], ['november 13', 'detroit', '4 - 3', 'tampa bay', 'osgood', '20544', '10 -... |
daniel gracie | https://en.wikipedia.org/wiki/Daniel_Gracie | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18377709-2.html.csv | count | daniel grace finished with a time of 5:00 exactly 5 times across various events . | {'scope': 'all', 'criterion': 'equal', 'value': '5:00', 'result': '5', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', '5:00'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to 5:00 .', 'tostr': 'filter_eq { all_rows ; time ; 5:00 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq {... | eq { count { filter_eq { all_rows ; time ; 5:00 } } ; 5 } = true | select the rows whose time record fuzzily matches to 5:00 . 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, 'time_5': 5, '5:00_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', 'time_5': 'time', '5:00_6': '5:00', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'time_5': [0], '5:00_6': [0], '5_7': [2]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '5 - 4 - 1', 'duane bastress', 'tko ( doctor stoppage )', 'bellator 54', '2', '5:00', 'atlantic city , new jersey , united states'], ['loss', '5 - 3 - 1', 'tim carpenter', 'decision ( split )', 'bellator 38', '3', '5:00', 'tunica , mississippi , united states'], ['win', '5 - 2 - 1', 'martin wojcik', 'submissi... |
state assembly elections in india , 2008 | https://en.wikipedia.org/wiki/State_Assembly_elections_in_India%2C_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15329030-1.html.csv | ordinal | the state of madhya pradesh recorded the highest number of seats ( acs ) in the 2008 india 's state assembly elections . | {'row': '4', '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', 'seats ( acs )', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; seats ( acs ) ; 1 }'}, 'state'], 'result': 'madhya pradesh', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; seats ( acs ) ; 1 } ; sta... | eq { hop { nth_argmax { all_rows ; seats ( acs ) ; 1 } ; state } ; madhya pradesh } = true | select the row whose seats ( acs ) record of all rows is 1st maximum . the state record of this row is madhya pradesh . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'seats (acs)_5': 5, '1_6': 6, 'state_7': 7, 'madhya pradesh_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', 'seats (acs)_5': 'seats ( acs )', '1_6': '1', 'state_7': 'state', 'madhya pradesh_8': 'madhya pradesh'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'seats (acs)_5': [0], '1_6': [0], 'state_7': [1], 'madhya pradesh_8': [2]} | ['state', 'date of polls', 'seats ( acs )', 'date of counting', 'incumbent', 'election winner'] | [['tripura', 'saturday , 23 february 2008', '60', 'friday , 7 mar 2008', 'cpi ( m )', 'cpi ( m )'], ['meghalaya', 'monday , 3 march 2008', '60', 'friday , 7 mar 2008', 'inc', 'mpa 1'], ['nagaland', 'wednesday , 5 march 2008', '60', 'saturday , 8 march 2008', 'dan', 'dan 2'], ['madhya pradesh', 'thursday , 27 november 2... |
kashmir | https://en.wikipedia.org/wiki/Kashmir | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17337-1.html.csv | comparative | azad kashmir area has only 1 % more residents that practice muslim than gilgit-baltistan . | {'row_1': '4', 'row_2': '5', 'col': '3', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1 %', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'area', 'azad kashmir'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose area record fuzzily matches to azad kashmir .', 'tostr': 'filter_eq { all_rows ; area ; azad kashmir }'}, '% ... | eq { diff { hop { filter_eq { all_rows ; area ; azad kashmir } ; % muslim } ; hop { filter_eq { all_rows ; area ; gilgit - baltistan } ; % muslim } } ; 1 % } = true | select the rows whose area record fuzzily matches to azad kashmir . take the % muslim record of this row . select the rows whose area record fuzzily matches to gilgit - baltistan . take the % muslim record of this row . the first record is 1 % larger than the second 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, 'area_8': 8, 'azad kashmir_9': 9, '% muslim_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'area_12': 12, 'gilgit - baltistan_13': 13, '% muslim_14': 14, '1%_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', 'area_8': 'area', 'azad kashmir_9': 'azad kashmir', '% muslim_10': '% muslim', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'area_1... | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'area_8': [0], 'azad kashmir_9': [0], '% muslim_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'area_12': [1], 'gilgit - baltistan_13': [1], '% muslim_14': [3], '1%_15': [5]} | ['area', 'population', '% muslim', '% hindu', '% buddhist', '% other'] | [['kashmir valley', '~ 4 million ( 4 million )', '95 %', '4 %', '-', '-'], ['jammu', '~ 3 million ( 3 million )', '30 %', '66 %', '-', '4 %'], ['ladakh', '~ 0.25 million ( 250000 )', '46 %', '-', '50 %', '3 %'], ['azad kashmir', '~ 2.6 million ( 2.6 million )', '100 %', '-', '-', '-'], ['gilgit - baltistan', '~ 1 milli... |
2010 - 11 new jersey nets season | https://en.wikipedia.org/wiki/2010%E2%80%9311_New_Jersey_Nets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27700375-8.html.csv | majority | kris humphries had the majority of the high rebounds performances for the new jersey nets . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'kris humphries', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high rebounds', 'kris humphries'], 'result': True, 'ind': 0, 'tointer': 'for the high rebounds records of all rows , most of them fuzzily match to kris humphries .', 'tostr': 'most_eq { all_rows ; high rebounds ; kris humphries } = true'} | most_eq { all_rows ; high rebounds ; kris humphries } = true | for the high rebounds records of all rows , most of them fuzzily match to kris humphries . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high rebounds_3': 3, 'kris humphries_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high rebounds_3': 'high rebounds', 'kris humphries_4': 'kris humphries'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high rebounds_3': [0], 'kris humphries_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['34', 'january 1', 'minnesota', 'l 88 - 103 ( ot )', 'sasha vujačić ( 22 )', 'kris humphries ( 14 )', 'devin harris ( 8 )', 'target center 12665', '9 - 25'], ['35', 'january 5', 'chicago', 'w 96 - 94 ( ot )', 'kris humphries ( 20 )', 'kris humphries ( 11 )', 'devin harris ( 11 )', 'prudential center 15025', '10 - 25'... |
thunder live | https://en.wikipedia.org/wiki/Thunder_Live | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12702752-1.html.csv | superlative | the april 21 , 1980 stereo lp release of thunder live was the largest size in centimeters . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,4', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'note'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; note }'}, 'date'], 'result': 'april 21 , 1980', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; note } ; date }'}, 'april 21 , 1980'], ... | and { eq { hop { argmax { all_rows ; note } ; date } ; april 21 , 1980 } ; eq { hop { argmax { all_rows ; note } ; format } ; stereo lp } } = true | select the row whose note record of all rows is maximum . the date record of this row is april 21 , 1980 . the format record of this row is stereo lp . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, 'note_8': 8, 'date_9': 9, 'april 21 , 1980_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'format_11': 11, 'stereo lp_12': 12} | {'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_7': 'all_rows', 'note_8': 'note', 'date_9': 'date', 'april 21 , 1980_10': 'april 21 , 1980', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'format_11': 'format', 'stereo lp_12': 'stereo lp'} | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], 'note_8': [0], 'date_9': [1], 'april 21 , 1980_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'format_11': [3], 'stereo lp_12': [4]} | ['region', 'date', 'label', 'format', 'catalog', 'note'] | [['japan', 'april 21 , 1980', 'alfa records', 'stereo lp', 'alr - 6037', '30 cm'], ['japan', 'december 21 , 1986', 'alfa records', 'cd', '32xa - 106', '12 cm'], ['japan', 'march 21 , 1992', 'alfa records', 'cd', 'alca - 273', '12 cm'], ['japan', 'june 29 , 1994', 'alfa records', 'cd', 'alca - 9003', '12 cm'], ['japan',... |
dancing on ice ( series 3 ) | https://en.wikipedia.org/wiki/Dancing_on_Ice_%28series_3%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21234111-6.html.csv | aggregation | for dancing on ice ( series 3 ) teams earning a total score of over 16.0 , their average public vote % was 10.75 % . | {'scope': 'subset', 'col': '11', 'type': 'average', 'result': '10.75 %', 'subset': {'col': '8', 'criterion': 'greater_than', 'value': '16.0'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'total', '16.0'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; total ; 16.0 }', 'tointer': 'select the rows whose total record is greater than 16.0 .'}, 'public vote %'], 'result': '10.75 %', 'ind':... | round_eq { avg { filter_greater { all_rows ; total ; 16.0 } ; public vote % } ; 10.75 % } = true | select the rows whose total record is greater than 16.0 . the average of the public vote % record of these rows is 10.75 % . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'total_5': 5, '16.0_6': 6, 'public vote %_7': 7, '10.75%_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'total_5': 'total', '16.0_6': '16.0', 'public vote %_7': 'public vote %', '10.75%_8': '10.75 %'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'total_5': [0], '16.0_6': [0], 'public vote %_7': [1], '10.75%_8': [2]} | ['order', 'couple', 'karen', 'nicky', 'jason', 'ruthie', 'robin', 'total', 'scoreboard', 'song', 'public vote %', 'result'] | [['1', 'gareth & maria', '4.5', '4.0', '3.5', '3.5', '4.0', '19 , 5', '3rd', 'wake me up when september ends - green day', '6.81 %', 'safe'], ['2', 'linda & daniel', '3.5', '3.0', '3.0', '4.0', '3.0', '16.5', '5th', 'candyman - christina aguilera', '9.09 %', 'safe'], ['3', 'samantha & pavel', '3.5', '3.0', '3.0', '3.5'... |
wichita state shockers men 's basketball | https://en.wikipedia.org/wiki/Wichita_State_Shockers_men%27s_basketball | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16619531-2.html.csv | unique | gene wiley was the only player who played for wsu in the 50 's to be drafted to the nba . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '1959 - 62', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'wsu year ( s )', '1959 - 62'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wsu year ( s ) record fuzzily matches to 1959 - 62 .', 'tostr': 'filter_eq { all_rows ; wsu year ( s ) ; 1959 - 62 }'}], 'result':... | and { only { filter_eq { all_rows ; wsu year ( s ) ; 1959 - 62 } } ; eq { hop { filter_eq { all_rows ; wsu year ( s ) ; 1959 - 62 } ; name } ; gene wiley } } = true | select the rows whose wsu year ( s ) record fuzzily matches to 1959 - 62 . there is only one such row in the table . the name record of this unqiue row is gene wiley . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'wsu year (s)_7': 7, '1959 - 62_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'gene wiley_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'wsu year (s)_7': 'wsu year ( s )', '1959 - 62_8': '1959 - 62', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'gene wiley_10': 'gene wiley'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'wsu year (s)_7': [0], '1959 - 62_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'gene wiley_10': [3]} | ['name', 'wsu year ( s )', 'position', 'team', 'pro year ( s )'] | [['gene wiley', '1959 - 62', 'c', 'los angeles lakers', '1962 - 67'], ['dave stallworth', '1962 - 65', 'pf - c', 'new york knicks', '1965 - 74'], ['nate bowman', '1962 - 65', 'c', 'cincinnati royals', '1966 - 71'], ['warren jabali', '1965 - 68', 'g - sf', 'new york knicks', '1968 - 1974'], ['bobby wilson', '1972 - 74',... |
1989 open championship | https://en.wikipedia.org/wiki/1989_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18135501-6.html.csv | unique | david feherty was the only competing player representing northern ireland . | {'scope': 'all', 'row': '7', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'northern ireland', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'northern ireland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to northern ireland .', 'tostr': 'filter_eq { all_rows ; country ; northern ireland }'}], 'result':... | and { only { filter_eq { all_rows ; country ; northern ireland } } ; eq { hop { filter_eq { all_rows ; country ; northern ireland } ; player } ; david feherty } } = true | select the rows whose country record fuzzily matches to northern ireland . there is only one such row in the table . the player record of this unqiue row is david feherty . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'northern ireland_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'david feherty_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'northern ireland_8': 'northern ireland', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'david feherty_10': 'david feherty'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'northern ireland_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'david feherty_10': [3]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'mark calcavecchia', 'united states', '71 + 68 + 68 + 68 = 275', '- 13', 'playoff'], ['t1', 'greg norman', 'australia', '69 + 70 + 72 + 64 = 275', '- 13', 'playoff'], ['t1', 'wayne grady', 'australia', '68 + 67 + 69 + 71 = 275', '- 13', 'playoff'], ['4', 'tom watson', 'united states', '69 + 68 + 68 + 72 = 277',... |
forbes global 2000 | https://en.wikipedia.org/wiki/Forbes_Global_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1682026-10.html.csv | count | 2 companies in the oil & gas industry are listed in the forbes global 2000 rankings . | {'scope': 'all', 'criterion': 'equal', 'value': 'oil & gas', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'industry', 'oil & gas'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose industry record fuzzily matches to oil & gas .', 'tostr': 'filter_eq { all_rows ; industry ; oil & gas }'}], 'result': '2', 'ind': 1, 't... | eq { count { filter_eq { all_rows ; industry ; oil & gas } } ; 2 } = true | select the rows whose industry record fuzzily matches to oil & gas . 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, 'industry_5': 5, 'oil & gas_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', 'industry_5': 'industry', 'oil & gas_6': 'oil & gas', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'industry_5': [0], 'oil & gas_6': [0], '2_7': [2]} | ['rank', 'company', 'headquarters', 'industry', 'sales ( billion )', 'profits ( billion )', 'assets ( billion )', 'market value ( billion )'] | [['1', 'citigroup', 'usa', 'banking', '94.71', '17.85', '1264.03', '255.30'], ['2', 'general electric', 'usa', 'conglomerates', '134.19', '15.59', '626.93', '328.54'], ['3', 'american international group', 'usa', 'insurance', '76.66', '6.46', '647.66', '194.87'], ['4', 'exxonmobil', 'usa', 'oil & gas', '222.88', '20.96... |
reykjavík international film festival | https://en.wikipedia.org/wiki/Reykjav%C3%ADk_International_Film_Festival | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11749830-1.html.csv | unique | 2006 was the only year that atom egoyan won the creative excellency award from reykjavík international film festival . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'atom egoyan', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'creative excellency', 'atom egoyan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose creative excellency record fuzzily matches to atom egoyan .', 'tostr': 'filter_eq { all_rows ; creative excellency ; atom e... | and { only { filter_eq { all_rows ; creative excellency ; atom egoyan } } ; eq { hop { filter_eq { all_rows ; creative excellency ; atom egoyan } ; year } ; 2006 } } = true | select the rows whose creative excellency record fuzzily matches to atom egoyan . there is only one such row in the table . the year record of this unqiue row is 2006 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'creative excellency_7': 7, 'atom egoyan_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2006_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'creative excellency_7': 'creative excellency', 'atom egoyan_8': 'atom egoyan', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2006_10': '2006'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'creative excellency_7': [0], 'atom egoyan_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2006_10': [3]} | ['year', 'dates', 'discovery of the year ( golden puffin )', 'lifetime achievement', 'creative excellency', 'audience award', 'fipresci award', 'church of iceland award'] | [['2004', 'nov 17 - nov 25', 'n / a', 'n / a', 'n / a', 'n / a', 'n / a', 'n / a'], ['2005', 'sept 29 - oct 9', 'the death of mr lazarescu , cristi puiu', 'abbas kiarostami', 'n / a', "howl 's moving castle hayao miyazaki", 'n / a', 'n / a'], ['2006', 'sept 28 - oct 8', 'grbavica , jasmila žbanić', 'alexander sokurov',... |
united states house of representatives elections , 1988 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1988 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341577-34.html.csv | count | two of the democratic party incumbents in the 1988 house of representative elections had been first elected in 1974 . | {'scope': 'subset', 'criterion': 'equal', 'value': '1974', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'democratic'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; party ; democratic }', 'tointer': 'select the rows whose party record fuzzily matches to democratic .'}, 'fi... | eq { count { filter_eq { filter_eq { all_rows ; party ; democratic } ; first elected ; 1974 } } ; 2 } = true | select the rows whose party record fuzzily matches to democratic . among these rows , select the rows whose first elected record is equal to 1974 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'party_6': 6, 'democratic_7': 7, 'first elected_8': 8, '1974_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'party_6': 'party', 'democratic_7': 'democratic', 'first elected_8': 'first elected', '1974_9': '1974', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'party_6': [0], 'democratic_7': [0], 'first elected_8': [1], '1974_9': [1], '2_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['north carolina 2', 'tim valentine', 'democratic', '1982', 're - elected', 'tim valentine ( d ) unopposed'], ['north carolina 3', 'martin lancaster', 'democratic', '1986', 're - elected', 'martin lancaster ( d ) unopposed'], ['north carolina 4', 'david e price', 'democratic', '1986', 're - elected', 'david e price ( ... |
rotores de portugal | https://en.wikipedia.org/wiki/Rotores_de_Portugal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16965464-1.html.csv | count | in rotores de portugal , one of the squadron 552 squadrons dates 2006-present . | {'scope': 'subset', 'criterion': 'equal', 'value': '2006-present', 'result': '1', 'col': '5', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'squadron 552'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'squadron', 'squadron 552'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; squadron ; squadron 552 }', 'tointer': 'select the rows whose squadron record fuzzily matches to sq... | eq { count { filter_eq { filter_eq { all_rows ; squadron ; squadron 552 } ; dates ; 2006-present } } ; 1 } = true | select the rows whose squadron record fuzzily matches to squadron 552 . among these rows , select the rows whose dates record fuzzily matches to 2006-present . the number of such rows is 1 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'squadron_6': 6, 'squadron 552_7': 7, 'dates_8': 8, '2006-present_9': 9, '1_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'squadron_6': 'squadron', 'squadron 552_7': 'squadron 552', 'dates_8': 'dates', '2006-present_9': '2006-present', '1_10': '1'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'squadron_6': [0], 'squadron 552_7': [0], 'dates_8': [1], '2006-present_9': [1], '1_10': [3]} | ['aircraft', 'origin', 'squadron', 'display aircraft', 'dates'] | [['sud aviation alouette iii', 'france', 'squadron 33', '4', '1976-1980'], ['sud aviation alouette iii', 'france', 'squadron 102', '2', '1982-1992'], ['sud aviation alouette iii', 'france', 'squadron 111', '4', '1993-1994'], ['sud aviation alouette iii', 'france', 'squadron 552', '2', '2004-2005'], ['sud aviation aloue... |
claire kuo | https://en.wikipedia.org/wiki/Claire_Kuo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18168296-1.html.csv | majority | all of claire kuo 's albums were released under the linfiar records label . | {'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'linfair records', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'label', 'linfair records'], 'result': True, 'ind': 0, 'tointer': 'for the label records of all rows , all of them fuzzily match to linfair records .', 'tostr': 'all_eq { all_rows ; label ; linfair records } = true'} | all_eq { all_rows ; label ; linfair records } = true | for the label records of all rows , all of them fuzzily match to linfair records . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'label_3': 3, 'linfair records_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'label_3': 'label', 'linfair records_4': 'linfair records'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'label_3': [0], 'linfair records_4': [0]} | ['album', 'english title', 'chinese ( traditional )', 'chinese ( simplified )', 'release date', 'label'] | [['1st', "i do n't want to forget you", '我不想忘記你', '我不想忘记你', 'june 29 , 2007', 'linfair records'], ['2nd', 'the next dawn', '下一個天亮', '下一个天亮', 'may 9 , 2008', 'linfair records'], ['3rd', 'singing in the tree', '在樹上唱歌', '在树上唱歌', 'may 22 , 2009', 'linfair records'], ['4th', 'your friend', '妳 朋友', '你 朋友', 'may 14 , 2010', '... |
premier league of bosnia and herzegovina | https://en.wikipedia.org/wiki/Premier_League_of_Bosnia_and_Herzegovina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1474099-1.html.csv | aggregation | premier league of bosnia and herzegovina clubs had an average of 16 seasons in the top division . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '16', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'number of seasons in top division'], 'result': '16', 'ind': 0, 'tostr': 'avg { all_rows ; number of seasons in top division }'}, '16'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; number of seasons in top division } ; 16 } = true', ... | round_eq { avg { all_rows ; number of seasons in top division } ; 16 } = true | the average of the number of seasons in top division record of all rows is 16 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'number of seasons in top division_4': 4, '16_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'number of seasons in top division_4': 'number of seasons in top division', '16_5': '16'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'number of seasons in top division_4': [0], '16_5': [1]} | ['club', 'position in 2012 - 13', 'first season in top division', 'number of seasons in top division', 'number of seasons in premier league a', 'first season of current spell in top division', 'top division titles', 'last top division title'] | [['borac b', '003 3rd', '1961 - 62', '23', '9', '2008 - 09', '1', '2010 - 11'], ['čelik b , c', '004 4th', '1966 - 67', '30', '13', '2000 - 01', '3 d', '1996 - 97'], ['gošk ( r )', '015 15th', '2011 - 12', '2', '2', '2011 - 12', '0', 'n / a'], ['gradina ( r )', '016 16th', '2012 - 13', '1', '1', '2012 - 13', '0', 'n / ... |
2008 afl season | https://en.wikipedia.org/wiki/2008_AFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14312471-3.html.csv | comparative | melbourne scored more points as the away team than richmond . | {'row_1': '2', 'row_2': '4', 'col': '4', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'away team', 'melbourne'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose away team record fuzzily matches to melbourne .', 'tostr': 'filter_eq { all_rows ; away team ; melbourne }'}, 'away team score']... | greater { hop { filter_eq { all_rows ; away team ; melbourne } ; away team score } ; hop { filter_eq { all_rows ; away team ; richmond } ; away team score } } = true | select the rows whose away team record fuzzily matches to melbourne . take the away team score record of this row . select the rows whose away team record fuzzily matches to richmond . take the away team score record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'away team_7': 7, 'melbourne_8': 8, 'away team score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'away team_11': 11, 'richmond_12': 12, 'away team score_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'away team_7': 'away team', 'melbourne_8': 'melbourne', 'away team score_9': 'away team score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'away ... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'away team_7': [0], 'melbourne_8': [0], 'away team score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'away team_11': [1], 'richmond_12': [1], 'away team score_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date', 'report'] | [['collingwood', '8.14 ( 62 )', 'hawthorn', '17.14 ( 116 )', 'mcg', '58307', 'friday , 1 august', 'aflcomau'], ['essendon', '19.10 ( 124 )', 'melbourne', '17.6 ( 108 )', 'mcg', '46334', 'saturday , 2 august', 'aflcomau'], ['adelaide', '13.16 ( 94 )', 'carlton', '12.14 ( 86 )', 'aami stadium', '40730', 'saturday , 2 aug... |
mutsuki - class destroyer | https://en.wikipedia.org/wiki/Mutsuki-class_destroyer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18756696-1.html.csv | count | 5 of the mutsuki - class destroyers had completion dates in the year 1927 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '1927', 'result': '5', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'completed', '1927'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose completed record fuzzily matches to 1927 .', 'tostr': 'filter_eq { all_rows ; completed ; 1927 }'}], 'result': '5', 'ind': 1, 'tostr': 'coun... | eq { count { filter_eq { all_rows ; completed ; 1927 } } ; 5 } = true | select the rows whose completed record fuzzily matches to 1927 . 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, 'completed_5': 5, '1927_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', 'completed_5': 'completed', '1927_6': '1927', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'completed_5': [0], '1927_6': [0], '5_7': [2]} | ['kanji', 'name', 'builder', 'laid down', 'launched', 'completed'] | [['睦月', 'mutsuki dd - 19', 'sasebo naval arsenal , japan', '21 may 1924', '23 july 1925', '25 march 1926'], ['如月', 'kisaragi dd - 21', 'maizuru naval arsenal , japan', '3 june 1924', '5 june 1925', '21 december 1925'], ['彌生', 'yayoi dd - 23', 'uraga dock company , japan', '11 january 1924', '11 july 1925', '28 august 1... |
fish leong | https://en.wikipedia.org/wiki/Fish_Leong | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1893815-1.html.csv | unique | the only fish leong album released by rock records in 2000 is courage . | {'scope': 'subset', 'row': '2', 'col': '5', 'col_other': '2,6', 'criterion': 'fuzzily_match', 'value': '2000', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'rock records'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'rock records'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; label ; rock records }', 'tointer': 'select the rows whose label record fuzzily matches to rock record... | and { only { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } } ; eq { hop { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } ; english title } ; courage } } = true | select the rows whose label record fuzzily matches to rock records . among these rows , select the rows whose release date record fuzzily matches to 2000 . there is only one such row in the table . the english title record of this unqiue row is courage . | 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, 'label_8': 8, 'rock records_9': 9, 'release date_10': 10, '2000_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'english title_12': 12, 'courage_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', 'label_8': 'label', 'rock records_9': 'rock records', 'release date_10': 'release date', '2000_11': '2000', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'english titl... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'label_8': [0], 'rock records_9': [0], 'release date_10': [1], '2000_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'english title_12': [3], 'courage_13': [4]} | ['album', 'english title', 'chinese ( traditional )', 'chinese ( simplified )', 'release date', 'label'] | [['1st', 'grown up overnight', '一夜長大', '一夜长大', 'september 17 , 1999', 'rock records'], ['2nd', 'courage', '勇氣', '勇气', 'august 2 , 2000', 'rock records'], ['3rd', 'shining star', '閃亮的星', '闪亮的星', 'june 27 , 2001', 'rock records'], ['4th', 'sunrise', '我喜歡', '我喜欢', 'february 7 , 2002', 'rock records'], ['5th', 'beautiful',... |
christian dailly | https://en.wikipedia.org/wiki/Christian_Dailly | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1317736-1.html.csv | unique | the only game that christian dailly scored more than one international goal took place in hong kong , china . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '3', 'criterion': 'greater_than', 'value': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'score', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record is greater than 1 .', 'tostr': 'filter_greater { all_rows ; score ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater... | and { only { filter_greater { all_rows ; score ; 1 } } ; eq { hop { filter_greater { all_rows ; score ; 1 } ; venue } ; hong kong , china } } = true | select the rows whose score record is greater than 1 . there is only one such row in the table . the venue record of this unqiue row is hong kong , china . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'score_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'venue_9': 9, 'hong kong , china_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'score_7': 'score', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'venue_9': 'venue', 'hong kong , china_10': 'hong kong , china'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'venue_9': [2], 'hong kong , china_10': [3]} | ['goal', 'date', 'venue', 'score', 'result', 'competition'] | [['1', '1 june 1997', "ta ' qali , malta", '1 - 0', '3 - 2', 'friendly'], ['2', '17 april 2002', 'aberdeen , scotland', '1 - 0', '1 - 2', 'friendly'], ['3', '23 may 2002', 'hong kong , china', '3 - 0', '4 - 0', 'friendly'], ['4', '12 october 2002', 'reykjavík , iceland', '1 - 0', '2 - 0', 'uefa euro 2004 qualifying'], ... |
united states house of representatives elections , 1998 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1998 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341453-7.html.csv | comparative | george miller was first elected earlier than cal dooley . | {'row_1': '1', 'row_2': '3', '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', 'george miller'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to george miller .', 'tostr': 'filter_eq { all_rows ; incumbent ; george miller }'}, 'first el... | less { hop { filter_eq { all_rows ; incumbent ; george miller } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; cal dooley } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to george miller . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to cal dooley . 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, 'george miller_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'cal dooley_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', 'george miller_8': 'george miller', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbe... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'george miller_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'cal dooley_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['california 7', 'george miller', 'democratic', '1974', 're - elected', 'george miller ( d ) 77 % norman reece ( r ) 23 %'], ['california 18', 'gary condit', 'democratic', '1989', 're - elected', 'gary condit ( d ) 86.7 % linda degroat ( l ) 13.2 %'], ['california 20', 'cal dooley', 'democratic', '1990', 're - elected... |
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/1-2668243-22.html.csv | majority | all of the incumbents were from the jacksonian party . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'jacksonian', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'party', 'jacksonian'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to jacksonian .', 'tostr': 'all_eq { all_rows ; party ; jacksonian } = true'} | all_eq { all_rows ; party ; jacksonian } = true | for the party records of all rows , all of them fuzzily match to jacksonian . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'jacksonian_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'jacksonian_4': 'jacksonian'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'jacksonian_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['south carolina 1', 'william drayton', 'jacksonian', '1825 ( special )', 're - elected', 'william drayton ( j )'], ['south carolina 2', 'james hamilton , jr', 'jacksonian', '1822 ( special )', 'retired jacksonian hold', 'robert w barnwell ( j )'], ['south carolina 3', 'thomas r mitchell', 'jacksonian', '1820 1824', '... |
2008 detroit lions season | https://en.wikipedia.org/wiki/2008_Detroit_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15347746-1.html.csv | comparative | there were more picks for the lions in round 3 than in round 1 . | {'row_1': '3', 'row_2': '2', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'round', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round record fuzzily matches to 3 .', 'tostr': 'filter_eq { all_rows ; round ; 3 }'}, 'pick'], 'result': None, 'ind': 2, 'tostr': 'hop { fil... | greater { hop { filter_eq { all_rows ; round ; 3 } ; pick } ; hop { filter_eq { all_rows ; round ; 2 } ; pick } } = true | select the rows whose round record fuzzily matches to 3 . take the pick record of this row . select the rows whose round record fuzzily matches to 2 . take the pick 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, 'round_7': 7, '3_8': 8, 'pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'round_11': 11, '2_12': 12, 'pick_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', 'round_7': 'round', '3_8': '3', 'pick_9': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'round_11': 'round', '2_12': '2', 'pick_13': 'pick'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'round_7': [0], '3_8': [0], 'pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'round_11': [1], '2_12': [1], 'pick_13': [3]} | ['round', 'pick', 'player', 'position', 'team'] | [['1', '17', 'gosder cherilus', 'offensive tackle', 'boston college'], ['2', '45', 'jordon dizon', 'linebacker', 'colorado'], ['3', '64', 'kevin smith', 'running back', 'central florida'], ['3', '87', 'andre fluellen', 'defensive tackle', 'florida state'], ['3', '92', 'cliff avril', 'linebacker', 'purdue'], ['5', '136'... |
list of protest clubs | https://en.wikipedia.org/wiki/List_of_protest_clubs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26218124-1.html.csv | count | for the protest clubs , when the sport is association football , 6 times , the country was england . | {'scope': 'subset', 'criterion': 'equal', 'value': 'england', 'result': '6', 'col': '5', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'association football'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sport', 'association football'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; sport ; association football }', 'tointer': 'select the rows whose sport record fuzzily matche... | eq { count { filter_eq { filter_eq { all_rows ; sport ; association football } ; country ; england } } ; 6 } = true | select the rows whose sport record fuzzily matches to association football . among these rows , select the rows whose country record fuzzily matches to england . the number of such rows is 6 . | 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, 'sport_6': 6, 'association football_7': 7, 'country_8': 8, 'england_9': 9, '6_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', 'sport_6': 'sport', 'association football_7': 'association football', 'country_8': 'country', 'england_9': 'england', '6_10': '6'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'sport_6': [0], 'association football_7': [0], 'country_8': [1], 'england_9': [1], '6_10': [3]} | ['name', 'original club', 'stadium', 'city', 'country', 'sport', 'founded', 'reason for foundation with source'] | [['afc liverpool', 'liverpool fc', 'valerie park', 'prescot', 'england', 'association football', '2008', 'protesting ticket prices at anfield'], ['bradford city afc', 'manningham fc', 'valley parade', 'bradford', 'england', 'association football', '1903', 'wanted to play another sport'], ['bray wanderers afc', "st kevi... |
list of step by step episodes | https://en.wikipedia.org/wiki/List_of_Step_by_Step_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2468961-8.html.csv | ordinal | of the step by step episodes , the one with the 2nd to last original air date was the one titled " the understudy . " . | {'row': '17', 'col': '6', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'original air date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; original air date ; 2 }'}, 'title'], 'result': 'the understudy', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; original air date... | eq { hop { nth_argmax { all_rows ; original air date ; 2 } ; title } ; the understudy } = true | select the row whose original air date record of all rows is 2nd maximum . the title record of this row is the understudy . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'original air date_5': 5, '2_6': 6, 'title_7': 7, 'the understudy_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', 'original air date_5': 'original air date', '2_6': '2', 'title_7': 'title', 'the understudy_8': 'the understudy'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'original air date_5': [0], '2_6': [0], 'title_7': [1], 'the understudy_8': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code'] | [['142', '1', 'making the grade', 'patrick duffy', 'adam markowitz', 'september 19 , 1997', '466501'], ['143', '2', 'a star is born', 'patrick duffy', 'mindy schneider', 'september 26 , 1997', '466502'], ['144', '3', "your cheatin ' heart", 'richard correll', 'howard adler & robert griffard', 'october 3 , 1997', '46650... |
oklahoma city hornets season | https://en.wikipedia.org/wiki/2005%E2%80%9306_New_Orleans/Oklahoma_City_Hornets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18289217-3.html.csv | superlative | in the 2005-06 oklahoma city hornets season , their first game at the ford center took place on nov 1 . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'ford center'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location / attendance', 'ford center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location / attendance ; ford center }', 'tointer': 'select the rows whose location / attendance record fuzzily matches to fo... | eq { min { filter_eq { all_rows ; location / attendance ; ford center } ; date } ; nov 1 } = true | select the rows whose location / attendance record fuzzily matches to ford center . the minimum date record of these rows is nov 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location / attendance_5': 5, 'ford center_6': 6, 'date_7': 7, 'nov 1_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location / attendance_5': 'location / attendance', 'ford center_6': 'ford center', 'date_7': 'date', 'nov 1_8': 'nov 1'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location / attendance_5': [0], 'ford center_6': [0], 'date_7': [1], 'nov 1_8': [2]} | ['game', 'date', 'opponent', 'score', 'location / attendance', 'record', 'streak'] | [['1', 'nov 1', 'sacramento kings', '93 - 67', 'ford center', '1 - 0', 'won 1'], ['2', 'nov 2', 'cleveland cavaliers', '87 - 109', 'quicken loans arena', '1 - 1', 'lost 1'], ['3', 'nov 5', 'houston rockets', '91 - 84', 'toyota center', '2 - 1', 'won 1'], ['4', 'nov 9', 'orlando magic', '83 - 88', 'ford center', '2 - 2'... |
rowing at the 2008 summer olympics - men 's coxless pair | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_coxless_pair | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662689-7.html.csv | comparative | in the 2008 summer olympic men 's coxless pairs , the australian team finished in front of the team from the united states . | {'row_1': '1', 'row_2': '2', 'col': '4', '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', 'country', 'australia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to australia .', 'tostr': 'filter_eq { all_rows ; country ; australia }'}, 'time'], 'result': None, 'i... | less { hop { filter_eq { all_rows ; country ; australia } ; time } ; hop { filter_eq { all_rows ; country ; united states } ; time } } = true | select the rows whose country record fuzzily matches to australia . take the time record of this row . select the rows whose country record fuzzily matches to united states . 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, 'country_7': 7, 'australia_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'country_11': 11, 'united states_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', 'country_7': 'country', 'australia_8': 'australia', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'country_11': 'country', 'united state... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'country_7': [0], 'australia_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'country_11': [1], 'united states_12': [1], 'time_13': [3]} | ['rank', 'athlete', 'country', 'time', 'notes'] | [['1', 'drew ginn , duncan free', 'australia', '6:34.29', 'fa'], ['2', 'tyler winklevoss , cameron winklevoss', 'united states', '6:36.65', 'fa'], ['3', 'tom lehmann , felix drahotta', 'germany', '6:37.26', 'fa'], ['4', 'goran jagar , nikola stojiä ‡', 'serbia', '6:38.96', 'fb'], ['5', 'giuseppe de vita , raffaello leo... |
2003 - 04 philadelphia flyers season | https://en.wikipedia.org/wiki/2003%E2%80%9304_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14347797-4.html.csv | aggregation | in the 2003 - 04 philadelphia flyers season , games against the carolina hurricanes had a total of 57 points . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '57', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'carolina hurricanes'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'carolina hurricanes'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; carolina hurricanes }', 'tointer': 'select the rows whose opponent record fuzzily matches to carolina hurricanes... | round_eq { sum { filter_eq { all_rows ; opponent ; carolina hurricanes } ; points } ; 57 } = true | select the rows whose opponent record fuzzily matches to carolina hurricanes . the sum of the points record of these rows is 57 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'carolina hurricanes_6': 6, 'points_7': 7, '57_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'carolina hurricanes_6': 'carolina hurricanes', 'points_7': 'points', '57_8': '57'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'carolina hurricanes_6': [0], 'points_7': [1], '57_8': [2]} | ['game', 'november', 'opponent', 'score', 'record', 'points'] | [['11', '1', 'toronto maple leafs', '7 - 1', '5 - 2 - 3 - 1', '14'], ['12', '6', 'washington capitals', '4 - 2', '6 - 2 - 3 - 1', '16'], ['13', '8', 'new york rangers', '2 - 1 ot', '7 - 2 - 3 - 1', '18'], ['14', '11', 'new york islanders', '2 - 1', '8 - 2 - 3 - 1', '20'], ['15', '13', 'vancouver canucks', '4 - 3 ot', '... |
edmonton radial railway society | https://en.wikipedia.org/wiki/Edmonton_Radial_Railway_Society | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22481967-1.html.csv | unique | the number 1 is the only model from the edmonton radial railway society that has a status of display only . | {'scope': 'all', 'row': '2', 'col': '7', 'col_other': '5', 'criterion': 'equal', 'value': 'display only', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'display only'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to display only .', 'tostr': 'filter_eq { all_rows ; status ; display only }'}], 'result': True, 'ind': 1... | and { only { filter_eq { all_rows ; status ; display only } } ; eq { hop { filter_eq { all_rows ; status ; display only } ; number } ; 1 } } = true | select the rows whose status record fuzzily matches to display only . there is only one such row in the table . the number record of this unqiue row is 1 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'status_7': 7, 'display only_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'number_9': 9, '1_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'status_7': 'status', 'display only_8': 'display only', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'number_9': 'number', '1_10': '1'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'status_7': [0], 'display only_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'number_9': [2], '1_10': [3]} | ['date', 'builder', 'type', 'operator', 'number', 'withdrawn', 'status'] | [['1907', 'occ', 'combination sweeper / overhead line car', 'saskatoon municipal railway', '200', '1951', 'stored'], ['1908', 'occ', 'streetcar', 'edmonton radial railway', '1', '1951', 'display only'], ['1912', 'stl', 'streetcar', 'edmonton radial railway', '33', '1951', 'stored'], ['1912', 'stl', 'streetcar', 'edmont... |
television in china | https://en.wikipedia.org/wiki/Television_in_China | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15147453-3.html.csv | majority | the minority of television channel in china were launched after the year 2000 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '2000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'launch', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the launch records of all rows , most of them are greater than 2000 .', 'tostr': 'most_greater { all_rows ; launch ; 2000 } = true'} | most_greater { all_rows ; launch ; 2000 } = true | for the launch records of all rows , most of them are greater than 2000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'launch_3': 3, '2000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'launch_3': 'launch', '2000_4': '2000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'launch_3': [0], '2000_4': [0]} | ['name', 'hanzi', 'language', 'launch', 'owner'] | [['kangba satellite television', '康巴卫视', 'tibetan', '2009', 'sichuan radio and television'], ['nmtv mongolian satellite television', '内蒙古蒙语卫视', 'mongolian', '1997', 'nei mongol television ( nmtv )'], ['television southern', '南方卫视', 'cantonese', '2000', 'southern media corporation ( smc )'], ['xjtv uyghur satellite tele... |
derek warwick | https://en.wikipedia.org/wiki/Derek_Warwick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1158017-1.html.csv | count | there were four years in which derek warwick did n't score any points at all . | {'scope': 'all', 'criterion': 'equal', 'value': '0', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; points ; 0 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; po... | eq { count { filter_eq { all_rows ; points ; 0 } } ; 4 } = true | select the rows whose points record is equal to 0 . 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, 'points_5': 5, '0_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'points_5': 'points', '0_6': '0', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'points_5': [0], '0_6': [0], '4_7': [2]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1981', 'candy toleman motorsport', 'toleman tg181', 'hart 415t 1.5 l4 t', '0'], ['1982', 'candy toleman motorsport', 'toleman tg181c', 'hart 415t 1.5 l4 t', '0'], ['1982', 'candy toleman motorsport', 'toleman tg183', 'hart 415t 1.5 l4 t', '0'], ['1983', 'candy toleman motorsport', 'toleman tg183b', 'hart 415t 1.5 l4... |
list of macintosh models grouped by cpu type | https://en.wikipedia.org/wiki/List_of_Macintosh_models_grouped_by_CPU_type | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18640-1.html.csv | majority | the majority of macintosh models have a processor with a clock speed of 8 mhz . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '8', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'clock speed ( mhz )', '8'], 'result': True, 'ind': 0, 'tointer': 'for the clock speed ( mhz ) records of all rows , most of them are equal to 8 .', 'tostr': 'most_eq { all_rows ; clock speed ( mhz ) ; 8 } = true'} | most_eq { all_rows ; clock speed ( mhz ) ; 8 } = true | for the clock speed ( mhz ) records of all rows , most of them are equal to 8 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'clock speed (mhz)_3': 3, '8_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'clock speed (mhz)_3': 'clock speed ( mhz )', '8_4': '8'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'clock speed (mhz)_3': [0], '8_4': [0]} | ['processor', 'model', 'clock speed ( mhz )', 'l1 cache ( bytes )', 'introduced', 'discontinued'] | [['mc68000', 'lisa', '5', '-', 'january 1983', 'january 1984'], ['mc68000', 'lisa 2', '5', '-', 'january 1984', 'january 1985'], ['mc68000', 'macintosh', '8', '-', 'january 1984', 'october 1985'], ['mc68000', 'macintosh 512k', '8', '-', 'september 1984', 'april 1986'], ['mc68000', 'macintosh xl', '5', '-', 'january 198... |
1998 australian super touring championship | https://en.wikipedia.org/wiki/1998_Australian_Super_Touring_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15394512-2.html.csv | unique | in the 1998 australian super touring championship , only one race in phillip island , victoria was won by volvo racing team . | {'scope': 'subset', 'row': '6', 'col': '7', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'volvo racing', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'phillip island , victoria'}} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city / state', 'phillip island , victoria'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; city / state ; phillip island , victoria }', 'tointer': 'select the rows whose city / state record fuzzily ... | only { filter_eq { filter_eq { all_rows ; city / state ; phillip island , victoria } ; team ; volvo racing } } = true | select the rows whose city / state record fuzzily matches to phillip island , victoria . among these rows , select the rows whose team record fuzzily matches to volvo racing . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'city / state_5': 5, 'phillip island , victoria_6': 6, 'team_7': 7, 'volvo racing_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'city / state_5': 'city / state', 'phillip island , victoria_6': 'phillip island , victoria', 'team_7': 'team', 'volvo racing_8': 'volvo racing'} | {'only_2': [3], 'result_3': [], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'city / state_5': [0], 'phillip island , victoria_6': [0], 'team_7': [1], 'volvo racing_8': [1]} | ['rd / race', 'race title', 'circuit', 'city / state', 'date', 'winner', 'team'] | [['1 / 1', 'calder', 'calder park raceway', 'melbourne , victoria', '4 - 5 apr', 'cameron mcconville', 'brad jones racing'], ['1 / 2', 'calder', 'calder park raceway', 'melbourne , victoria', '4 - 5 apr', 'cameron mcconville', 'brad jones racing'], ['2 / 1', 'oran park', 'oran park raceway', 'sydney , new south wales',... |
british records in athletics | https://en.wikipedia.org/wiki/British_records_in_athletics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11070660-5.html.csv | unique | tony geal set only one british athletic record . | {'scope': 'all', 'row': '13', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'tony geal', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'athlete', 'tony geal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose athlete record fuzzily matches to tony geal .', 'tostr': 'filter_eq { all_rows ; athlete ; tony geal }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { ... | only { filter_eq { all_rows ; athlete ; tony geal } } = true | select the rows whose athlete record fuzzily matches to tony geal . 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, 'athlete_4': 4, 'tony geal_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'athlete_4': 'athlete', 'tony geal_5': 'tony geal'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'athlete_4': [0], 'tony geal_5': [0]} | ['event', 'data', 'athlete', 'date', 'place'] | [['5 km', '19:29', 'andi drake', '27 may 1990', 'søfteland , norway'], ['5 miles', '32:38 +', 'ian mccombie', '23 march 1985', 'york , united kingdom'], ['10 km', '40:17', 'chris maddocks', '30 april 1989', 'burrator , united kingdom'], ['15 km', '1:01:11', 'steve barry', '24 june 1984', 'mézidon - canon , france'], ['... |
mickey wright | https://en.wikipedia.org/wiki/Mickey_Wright | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1635463-1.html.csv | count | three of the championships took place in 1961 . | {'scope': 'all', 'criterion': 'equal', 'value': '1961', 'result': '3', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '1961'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 1961 .', 'tostr': 'filter_eq { all_rows ; year ; 1961 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ;... | eq { count { filter_eq { all_rows ; year ; 1961 } } ; 3 } = true | select the rows whose year record is equal to 1961 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, '1961_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '1961_6': '1961', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '1961_6': [0], '3_7': [2]} | ['year', 'championship', 'winning score', 'margin', 'runner ( s ) - up'] | [['1958', 'lpga championship', '+ 8 ( 69 + 69 + 76 + 74 = 288 )', '6 strokes', 'fay crocker'], ['1958', "us women 's open", '- 2 ( 74 + 72 + 70 + 74 = 290 )', '5 strokes', 'louise suggs'], ['1959', "us women 's open", '+ 7 ( 72 + 75 + 69 + 71 = 287 )', '2 strokes', 'louise suggs'], ['1960', 'lpga championship', '- 4 ( ... |
2008 - 09 scottish first division | https://en.wikipedia.org/wiki/2008%E2%80%9309_Scottish_First_Division | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14003085-5.html.csv | aggregation | the average attendance for all venues during the 2008-09 season was just over 2,500 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '2530.6', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'average'], 'result': '2530.6', 'ind': 0, 'tostr': 'avg { all_rows ; average }'}, '2530.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; average } ; 2530.6 } = true', 'tointer': 'the average of the average record of all rows is 2530.... | round_eq { avg { all_rows ; average } ; 2530.6 } = true | the average of the average record of all rows is 2530.6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'average_4': 4, '2530.6_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'average_4': 'average', '2530.6_5': '2530.6'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'average_4': [0], '2530.6_5': [1]} | ['team', 'stadium', 'capacity', 'highest', 'lowest', 'average'] | [['dundee', 'dens park', '11856', '6537', '2831', '3995'], ['st johnstone', 'mcdiarmid park', '10673', '7238', '2259', '3502'], ['dunfermline athletic', 'east end park', '11998', '4998', '1371', '3255'], ['partick thistle', 'firhill stadium', '10887', '3378', '2296', '2956'], ['queen of the south', 'palmerston park', '... |
fencing at the 2010 summer youth olympics - mixed team | https://en.wikipedia.org/wiki/Fencing_at_the_2010_Summer_Youth_Olympics_%E2%80%93_Mixed_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28372291-1.html.csv | aggregation | in the 2010 season the american fencer 's average rank is 6.58 . | {'scope': 'subset', 'col': '8', 'type': 'average', 'result': '6.58', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': 'america'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'america'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; team ; america }', 'tointer': 'select the rows whose team record fuzzily matches to america .'}, 'average fencers rank'], 'result': '6.58',... | round_eq { avg { filter_eq { all_rows ; team ; america } ; average fencers rank } ; 6.58 } = true | select the rows whose team record fuzzily matches to america . the average of the average fencers rank record of these rows is 6.58 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'america_6': 6, 'average fencers rank_7': 7, '6.58_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'america_6': 'america', 'average fencers rank_7': 'average fencers rank', '6.58_8': '6.58'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'america_6': [0], 'average fencers rank_7': [1], '6.58_8': [2]} | ['team', 'female épée', 'male épée', 'female foil', 'male foil', 'female saber', 'male saber', 'average fencers rank', 'initial team rank'] | [['europe 1', 'santuccio alberta ( 2 ) ( ita )', 'fichera marco ( 1 ) ( ita )', 'mancini camilla ( 1 ) ( ita )', 'luperi edoardo ( 1 ) ( ita )', 'egoryan yana ( 1 ) ( rus )', 'affede leonardo ( 2 ) ( ita )', '1.33', '1'], ['europe 2', 'swatowska martyna ( 3 ) ( pol )', 'bodoczi nikolaus ( 2 ) ( ger )', 'alekseeva victo... |
list of tvb series ( 2009 ) | https://en.wikipedia.org/wiki/List_of_TVB_series_%282009%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19210674-1.html.csv | unique | for the tvb series in 2009 , the only episode with over 2.2 million viewers was the one titled beyond the realm of conscience . | {'scope': 'all', 'row': '1', 'col': '8', 'col_other': '2', 'criterion': 'greater_than', 'value': '2.20 million', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'hk viewers', '2.20 million'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose hk viewers record is greater than 2.20 million .', 'tostr': 'filter_greater { all_rows ; hk viewers ; 2.20 million }'}], 'result':... | and { only { filter_greater { all_rows ; hk viewers ; 2.20 million } } ; eq { hop { filter_greater { all_rows ; hk viewers ; 2.20 million } ; english title } ; beyond the realm of conscience } } = true | select the rows whose hk viewers record is greater than 2.20 million . there is only one such row in the table . the english title record of this unqiue row is beyond the realm of conscience . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'hk viewers_7': 7, '2.20 million_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'english title_9': 9, 'beyond the realm of conscience_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'hk viewers_7': 'hk viewers', '2.20 million_8': '2.20 million', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'english title_9': 'english title', 'beyond the realm of conscience_10': 'beyond the realm ... | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'hk viewers_7': [0], '2.20 million_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'english title_9': [2], 'beyond the realm of conscience_10': [3]} | ['rank', 'english title', 'chinese title', 'average', 'peak', 'premiere', 'finale', 'hk viewers'] | [['1', 'beyond the realm of conscience', '宮心計', '35', '50', '33', '35', '2.26 million'], ['2', 'rosy business', '巾幗梟雄', '33', '47', '28', '39', '2.11 million'], ['3', 'burning flame iii', '烈火雄心3', '33', '38', '33', '34', '2.10 million'], ['4', "you 're hired", '絕代商驕', '32', '40', '31', '36', '2.05 million'], ['5', 'die... |
1989 san francisco 49ers season | https://en.wikipedia.org/wiki/1989_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15521693-2.html.csv | majority | the 49ers won most of their games in the 1989 football 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', 'tv time', 'attendance'] | [['1', 'september 10 , 1989', 'indianapolis colts', 'w 30 - 24', 'cbs 10:00 am', '60111'], ['2', 'september 17 , 1989', 'tampa bay buccaneers', 'w 20 - 16', 'cbs 1:00 pm', '64087'], ['3', 'september 24 , 1989', 'philadelphia eagles', 'w 38 - 28', 'cbs 10:00 am', '66042'], ['4', 'october 1 , 1989', 'los angeles rams', '... |
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 | count | in the 1999 indianapolis colts season , for games in december , there were two games at the rca dome . | {'scope': 'subset', 'criterion': 'equal', 'value': 'rca dome', 'result': '2', 'col': '6', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'december'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; december }', 'tointer': 'select the rows whose date record fuzzily matches to december .'}, 'game si... | eq { count { filter_eq { filter_eq { all_rows ; date ; december } ; game site ; rca dome } } ; 2 } = true | select the rows whose date record fuzzily matches to december . among these rows , select the rows whose game site record fuzzily matches to rca dome . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, 'december_7': 7, 'game site_8': 8, 'rca dome_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', 'december_7': 'december', 'game site_8': 'game site', 'rca dome_9': 'rca dome', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], 'december_7': [0], 'game site_8': [1], 'rca dome_9': [1], '2_10': [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', 'c... |
2007 - 08 chicago bulls season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Chicago_Bulls_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11960610-10.html.csv | aggregation | during march of 2008 , hinrich averaged 7.8 assists in games in which he lead the bulls in the category . | {'scope': 'subset', 'col': '7', 'type': 'average', 'result': '7.8', 'subset': {'col': '7', 'criterion': 'fuzzily_match', 'value': 'hinrich'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'hinrich'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high assists ; hinrich }', 'tointer': 'select the rows whose high assists record fuzzily matches to hinrich .'}, 'high assists'], '... | round_eq { avg { filter_eq { all_rows ; high assists ; hinrich } ; high assists } ; 7.8 } = true | select the rows whose high assists record fuzzily matches to hinrich . the average of the high assists record of these rows is 7.8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high assists_5': 5, 'hinrich_6': 6, 'high assists_7': 7, '7.8_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high assists_5': 'high assists', 'hinrich_6': 'hinrich', 'high assists_7': 'high assists', '7.8_8': '7.8'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high assists_5': [0], 'hinrich_6': [0], 'high assists_7': [1], '7.8_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['59', 'march 2', 'cleveland', '86 - 95', 'hughes ( 23 )', 'gooden ( 10 )', 'hughes ( 4 )', 'quicken loans arena 20562', '23 - 36'], ['60', 'march 4', 'memphis', '112 - 97', 'deng , gooden ( 21 )', 'gooden ( 14 )', 'hinrich ( 12 )', 'united center 21725', '24 - 36'], ['61', 'march 6', 'cleveland', '107 - 96', 'deng , ... |
athletics at the 2008 summer olympics - men 's 400 metres | https://en.wikipedia.org/wiki/Athletics_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_400_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18569105-7.html.csv | aggregation | the average reaction time for all athletes in the men 's 400 metres is 0.236 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '0.236', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'react'], 'result': '0.236', 'ind': 0, 'tostr': 'avg { all_rows ; react }'}, '0.236'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; react } ; 0.236 } = true', 'tointer': 'the average of the react record of all rows is 0.236 .'} | round_eq { avg { all_rows ; react } ; 0.236 } = true | the average of the react record of all rows is 0.236 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'react_4': 4, '0.236_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'react_4': 'react', '0.236_5': '0.236'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'react_4': [0], '0.236_5': [1]} | ['rank', 'lane', 'athlete', 'nationality', 'time', 'react'] | [['1', '7', 'andrew steele', 'great britain', '44.94', '0.248'], ['2', '5', 'renny quow', 'trinidad and tobago', '45.13', '0.266'], ['3', '6', 'michael mathieu', 'bahamas', '45.17', '0.193'], ['4', '8', 'michael blackwood', 'jamaica', '45.56', '0.204'], ['5', '2', 'tyler christopher', 'canada', '45.67', '0.172'], ['6',... |
campbeltown and machrihanish light railway | https://en.wikipedia.org/wiki/Campbeltown_and_Machrihanish_Light_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1820430-1.html.csv | majority | the majority of the railways were built by andrew barclay & co . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'andrew barclay & co', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'builder', 'andrew barclay & co'], 'result': True, 'ind': 0, 'tointer': 'for the builder records of all rows , most of them fuzzily match to andrew barclay & co .', 'tostr': 'most_eq { all_rows ; builder ; andrew barclay & co } = true'} | most_eq { all_rows ; builder ; andrew barclay & co } = true | for the builder records of all rows , most of them fuzzily match to andrew barclay & co . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'builder_3': 3, 'andrew barclay & co_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'builder_3': 'builder', 'andrew barclay & co_4': 'andrew barclay & co'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'builder_3': [0], 'andrew barclay & co_4': [0]} | ['name', 'builder', 'type', 'works number', 'built'] | [['pioneer', 'andrew barclay & co', '0 - 4 - 0 wt ( converted to 0 - 4 - 2 wt )', 'unknown', '1876'], ['chevalier', 'andrew barclay & co', '0 - 4 - 0 st ( converted to 0 - 4 - 2 st )', '269', '1885'], ['princess', 'kerr stuart', '0 - 4 - 2 t', '717', '1900'], ['argyll', 'andrew barclay & co', '0 - 6 - 2 t', '1049', '19... |
united states house of representatives elections , 1824 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1824 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668264-8.html.csv | comparative | david trimble has a first elected year which is earlier than that of thomas p moore . | {'row_1': '1', 'row_2': '5', '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', 'david trimble'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to david trimble .', 'tostr': 'filter_eq { all_rows ; incumbent ; david trimble }'}, 'first el... | less { hop { filter_eq { all_rows ; incumbent ; david trimble } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; thomas p moore } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to david trimble . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to thomas p moore . 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, 'david trimble_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'thomas p moore_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', 'david trimble_8': 'david trimble', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbe... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'david trimble_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'thomas p moore_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['kentucky 1', 'david trimble', 'adams - clay republican', '1816', 're - elected', 'david trimble ( a )'], ['kentucky 3', 'henry clay', 'adams - clay republican', '1810 1822', 're - elected', 'henry clay ( a ) 100 %'], ['kentucky 4', 'robert p letcher', 'adams - clay republican', '1822', 're - elected', 'robert p letc... |
list of town tramway systems in the netherlands | https://en.wikipedia.org/wiki/List_of_town_tramway_systems_in_the_Netherlands | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12562214-1.html.csv | majority | the majority of town tramway systems in the netherlands had initially horse drawn systems . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'horse', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'traction type', 'horse'], 'result': True, 'ind': 0, 'tointer': 'for the traction type records of all rows , most of them fuzzily match to horse .', 'tostr': 'most_eq { all_rows ; traction type ; horse } = true'} | most_eq { all_rows ; traction type ; horse } = true | for the traction type records of all rows , most of them fuzzily match to horse . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'traction type_3': 3, 'horse_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'traction type_3': 'traction type', 'horse_4': 'horse'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'traction type_3': [0], 'horse_4': [0]} | ['name of system', 'location', 'traction type', 'date ( from )', 'date ( to )'] | [['atm ( 1897 - 1917 ) gta ( 1919 - 1922 )', 'apeldoorn', 'horse', '12 august 1897', '11 november 1917'], ['atm ( 1897 - 1917 ) gta ( 1919 - 1922 )', 'apeldoorn', 'petrol ( gasoline )', '5 june 1919', '8 october 1922'], ['atm ( 1880 - 1911 ) geta ( 1911 - 1944 )', 'arnhem', 'horse', '3 may 1880', '12 june 1912'], ['atm... |
double trap | https://en.wikipedia.org/wiki/Double_trap | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1354148-3.html.csv | count | satu pusila won a total of three gold medals in the double trap events . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'satu pusila', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'gold', 'satu pusila'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record fuzzily matches to satu pusila .', 'tostr': 'filter_eq { all_rows ; gold ; satu pusila }'}], 'result': '3', 'ind': 1, 'tostr':... | eq { count { filter_eq { all_rows ; gold ; satu pusila } } ; 3 } = true | select the rows whose gold record fuzzily matches to satu pusila . 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, 'gold_5': 5, 'satu pusila_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', 'gold_5': 'gold', 'satu pusila_6': 'satu pusila', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'gold_5': [0], 'satu pusila_6': [0], '3_7': [2]} | ['year', 'place', 'gold', 'silver', 'bronze'] | [['1989', 'montecatini terme', 'roberta morara ( ita )', 'roberta pelosi ( ita )', 'anna maria bianchi ( ita )'], ['1990', 'moscow', 'satu pusila ( fin )', 'elena shishirina ( urs )', 'audrey grosch ( usa )'], ['1991', 'perth', 'satu pusila ( fin )', 'elena tkach ( urs )', 'deena julin ( usa )'], ['1993', 'barcelona', ... |
1965 american football league draft | https://en.wikipedia.org/wiki/1965_American_Football_League_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18652198-4.html.csv | count | between the 25th and 32nd picks of the 1965 afl draft , two quarterbacks were picked . | {'scope': 'all', 'criterion': 'equal', 'value': 'quarterback', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'quarterback'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to quarterback .', 'tostr': 'filter_eq { all_rows ; position ; quarterback }'}], 'result': '2', 'ind':... | eq { count { filter_eq { all_rows ; position ; quarterback } } ; 2 } = true | select the rows whose position record fuzzily matches to quarterback . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, 'quarterback_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', 'quarterback_6': 'quarterback', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'quarterback_6': [0], '2_7': [2]} | ['pick', 'team', 'player', 'position', 'college'] | [['25', 'denver broncos', 'george donnelly', 'defensive back', 'illinois'], ['26', 'houston oilers', 'bobby maples', 'center', 'baylor'], ['27', 'oakland raiders', 'gus otto', 'linebacker', 'missouri'], ['28', 'new york jets', 'bob schweickert', 'quarterback', 'virginia tech'], ['29', 'kansas city chiefs', 'otis taylor... |
list of longest suspension bridge spans | https://en.wikipedia.org/wiki/List_of_longest_suspension_bridge_spans | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1604842-2.html.csv | ordinal | izmit bay bridge was the last bridge to open on the list of longest suspension bridge spans . | {'row': '1', 'col': '4', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'year to open', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; year to open ; 1 }'}, 'name'], 'result': 'izmit bay bridge', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; year to open ; 1 } ; name ... | eq { hop { nth_argmax { all_rows ; year to open ; 1 } ; name } ; izmit bay bridge } = true | select the row whose year to open record of all rows is 1st maximum . the name record of this row is izmit bay bridge . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'year to open_5': 5, '1_6': 6, 'name_7': 7, 'izmit bay bridge_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'year to open_5': 'year to open', '1_6': '1', 'name_7': 'name', 'izmit bay bridge_8': 'izmit bay bridge'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'year to open_5': [0], '1_6': [0], 'name_7': [1], 'izmit bay bridge_8': [2]} | ['name', 'main span metres', 'main span feet', 'year to open', 'country'] | [['izmit bay bridge', '1550', '5085', '2017', 'turkey'], ['yavuz sultan selim bridge', '1408', '4619', '2015', 'turkey'], ['longjiang river bridge', '1196', '3924', '2015', 'china'], ['longmen bridge ( guangxi )', '1160', '3806', '2016', 'china'], ['ulsan bridge', '1150', '3773', '2014', 'south korea'], ['hålogaland br... |
list of big brother ( uk ) shows | https://en.wikipedia.org/wiki/List_of_Big_Brother_%28UK%29_shows | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11748792-2.html.csv | count | there are 7 series of the big brother ( uk ) shows . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '7', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose series record is arbitrary .', 'tostr': 'filter_all { all_rows ; series }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; series } ... | eq { count { filter_all { all_rows ; series } } ; 7 } = true | select the rows whose series record is arbitrary . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'series_5': 5, '7_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'series_5': 'series', '7_6': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'series_5': [0], '7_6': [2]} | ['series', 'monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday'] | [['celebrity big brother 8', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['big brother 12', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie eas... |
list of reality television show franchises | https://en.wikipedia.org/wiki/List_of_reality_television_show_franchises | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24224647-2.html.csv | count | three clash of the choirs franchisees premiered in 2010 . | {'scope': 'all', 'criterion': 'equal', 'value': '2010', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year premiered', '2010'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year premiered record is equal to 2010 .', 'tostr': 'filter_eq { all_rows ; year premiered ; 2010 }'}], 'result': '3', 'ind': 1, 'tostr': '... | eq { count { filter_eq { all_rows ; year premiered ; 2010 } } ; 3 } = true | select the rows whose year premiered record is equal to 2010 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year premiered_5': 5, '2010_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year premiered_5': 'year premiered', '2010_6': '2010', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year premiered_5': [0], '2010_6': [0], '3_7': [2]} | ['region / country', 'local name', 'main presenter', 'network', 'year premiered'] | [['china', '夢想合唱團 mengxiang hechang tuan', 'sa beining', 'cctv - 1', '2011'], ['denmark', 'allstars', 'lisbeth østergaard', 'tv2', '2008'], ['estonia', 'laululahing', 'tarmo leinatamm', 'etv', '2008'], ['finland', 'kuorosota', 'kristiina komulainen', 'nelonen', '2009'], ['france', 'la bataille des chorales', 'benjamin ... |
ministry of housing and construction | https://en.wikipedia.org/wiki/Ministry_of_Housing_and_Construction | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18921615-2.html.csv | superlative | eli ben - menachem is the newest member of the ministry of housing and consutrction , with his term starting in 2005 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '9', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'term start'], 'result': '11 january 2005', 'ind': 0, 'tostr': 'max { all_rows ; term start }', 'tointer': 'the maximum term start record of all rows is 11 january 2005 .'}, '11 january 2005'], 'result': True, 'ind': 1, 'tostr': 'eq {... | and { eq { max { all_rows ; term start } ; 11 january 2005 } ; eq { hop { argmax { all_rows ; term start } ; minister } ; eli ben - menachem } } = true | the maximum term start record of all rows is 11 january 2005 . the minister record of the row with superlative term start record is eli ben - menachem . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'term start_8': 8, '11 january 2005_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'term start_11': 11, 'minister_12': 12, 'eli ben - menachem_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'term start_8': 'term start', '11 january 2005_9': '11 january 2005', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'term start_11': 'term start', 'minister_12': 'minister', 'eli... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'term start_8': [0], '11 january 2005_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'term start_11': [2], 'minister_12': [3], 'eli ben - menachem_13': [4]} | ['minister', 'party', 'governments', 'term start', 'term end'] | [['moshe katsav', 'likud', '20', '10 october 1983', '13 september 1984'], ['avraham ravitz', 'degel hatorah', '24', '25 june 1990', '13 july 1992'], ['aryeh gamliel', 'shas', '25', '29 july 1992', '9 september 1993'], ['ran cohen', 'meretz', '25', '4 august 1992', '31 december 1992'], ['eli ben - menachem', 'labor part... |
1944 in brazilian football | https://en.wikipedia.org/wiki/1944_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15331540-1.html.csv | comparative | juventus had a higher goals against than corinthains in the 1944 brazilian football season . | {'row_1': '7', 'row_2': '3', 'col': '7', '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', 'team', 'juventus'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to juventus .', 'tostr': 'filter_eq { all_rows ; team ; juventus }'}, 'against'], 'result': None, 'ind': 2... | greater { hop { filter_eq { all_rows ; team ; juventus } ; against } ; hop { filter_eq { all_rows ; team ; corinthians } ; against } } = true | select the rows whose team record fuzzily matches to juventus . take the against record of this row . select the rows whose team record fuzzily matches to corinthians . take the against 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, 'team_7': 7, 'juventus_8': 8, 'against_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'corinthians_12': 12, 'against_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', 'team_7': 'team', 'juventus_8': 'juventus', 'against_9': 'against', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'corinthians_12... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'juventus_8': [0], 'against_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'corinthians_12': [1], 'against_13': [3]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'palmeiras', '32', '20', '2', '3', '19', '31'], ['2', 'são paulo', '29', '20', '3', '4', '32', '37'], ['3', 'corinthians', '28', '20', '4', '4', '35', '20'], ['4', 'ypiranga - sp', '23', '20', '3', '7', '29', '8'], ['5', 'são paulo railway', '21', '20', '3', '8', '48', '- 7'], ['6', 'santos', '20', '20', '4', '8... |
2008 - 09 detroit red wings season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Red_Wings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17371135-5.html.csv | ordinal | the game on november 13 ranked first for the highest number in attendance for the 08-09 red wings season . | {'row': '4', 'col': '6', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'date'], 'result': 'november 13', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; date }'}, 'novem... | eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; date } ; november 13 } = true | select the row whose attendance record of all rows is 1st maximum . the date record of this row is november 13 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'date_7': 7, 'november 13_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'date_7': 'date', 'november 13_8': 'november 13'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'date_7': [1], 'november 13_8': [2]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['november 2', 'detroit', '3 - 2', 'vancouver', 'osgood', '18630', '8 - 2 - 2'], ['november 8', 'new jersey', '1 - 3', 'detroit', 'osgood', '20066', '9 - 2 - 2'], ['november 11', 'pittsburgh', '7 - 6', 'detroit', 'osgood', '20066', '9 - 2 - 3'], ['november 13', 'detroit', '4 - 3', 'tampa bay', 'osgood', '20544', '10 -... |
puerto rico soccer league | https://en.wikipedia.org/wiki/Puerto_Rico_Soccer_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17430068-2.html.csv | count | among the clubs of puerto rico soccer league that were founded after 2000 , 3 of them played 2009 season in prsl . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': '2009', 'result': '3', 'col': '5', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '2000'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'founded', '2000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; founded ; 2000 }', 'tointer': 'select the rows whose founded record is greater than 2000 .'}, 'seasons... | eq { count { filter_eq { filter_greater { all_rows ; founded ; 2000 } ; seasons in prsl ; 2009 } } ; 3 } = true | select the rows whose founded record is greater than 2000 . among these rows , select the rows whose seasons in prsl record fuzzily matches to 2009 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'founded_6': 6, '2000_7': 7, 'seasons in prsl_8': 8, '2009_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'founded_6': 'founded', '2000_7': '2000', 'seasons in prsl_8': 'seasons in prsl', '2009_9': '2009', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'founded_6': [0], '2000_7': [0], 'seasons in prsl_8': [1], '2009_9': [1], '3_10': [3]} | ['club', 'home city', 'stadium', 'founded', 'seasons in prsl'] | [['academia quintana fc', 'san juan', 'hiram bithorn stadium', '1969', '2008 , 2009'], ['atlético de san juan fc', 'san juan', 'hiram bithorn stadium', '2008', '2008 , 2009'], ['bayamón fc', 'bayamón', 'estadio juan ramón loubriel', '2009', '2009'], ['fajardo fc', 'fajardo', 'fajardo stadium', '2010', '2010'], ['guayna... |
2002 - 03 toronto raptors season | https://en.wikipedia.org/wiki/2002%E2%80%9303_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15780718-8.html.csv | majority | all games of the 2002 - 03 toronto raptors ' season were scheduled for the month of march . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'march', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'march'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to march .', 'tostr': 'all_eq { all_rows ; date ; march } = true'} | all_eq { all_rows ; date ; march } = true | for the date records of all rows , all of them fuzzily match to march . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'march_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'march_4': 'march'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'march_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['56', 'march 2', 'boston', 'w 104 - 92 ( ot )', 'antonio davis ( 19 )', 'michael bradley ( 13 )', 'alvin williams ( 6 )', 'air canada centre 19800', '18 - 38'], ['57', 'march 4', 'washington', 'w 89 - 86 ( ot )', 'vince carter ( 24 )', 'michael bradley , jerome williams ( 7 )', 'antonio davis ( 5 )', 'mci center 2017... |
1994 cincinnati bengals season | https://en.wikipedia.org/wiki/1994_Cincinnati_Bengals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16779943-2.html.csv | aggregation | in the 1994 season of cincinnati bengals , games in october had a total of 245,093 people attend . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '245,093', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'october'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'attendance'], 'result': '245,093', 'ind':... | round_eq { sum { filter_eq { all_rows ; date ; october } ; attendance } ; 245,093 } = true | select the rows whose date record fuzzily matches to october . the sum of the attendance record of these rows is 245,093 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'october_6': 6, 'attendance_7': 7, '245,093_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'october_6': 'october', 'attendance_7': 'attendance', '245,093_8': '245,093'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'october_6': [0], 'attendance_7': [1], '245,093_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 4 , 1994', 'cleveland browns', 'l 20 - 28', '52778'], ['2', 'september 11 , 1994', 'san diego chargers', 'l 10 - 27', '53217'], ['3', 'september 18 , 1994', 'new england patriots', 'l 28 - 31', '46640'], ['4', 'september 25 , 1994', 'houston oilers', 'l 13 - 20', '44253'], ['5', 'october 2 , 1994', 'm... |
westmorland county , new brunswick | https://en.wikipedia.org/wiki/Westmorland_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-176529-2.html.csv | superlative | salisbury is the parish in westmorland county , new brunswick that has the highest area . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'area km 2'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; area km 2 }'}, 'official name'], 'result': 'salisbury', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; area km 2 } ; official name }'}, 'salisbury'], 'res... | eq { hop { argmax { all_rows ; area km 2 } ; official name } ; salisbury } = true | select the row whose area km 2 record of all rows is maximum . the official name record of this row is salisbury . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'area km 2_5': 5, 'official name_6': 6, 'salisbury_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'area km 2_5': 'area km 2', 'official name_6': 'official name', 'salisbury_7': 'salisbury'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'area km 2_5': [0], 'official name_6': [1], 'salisbury_7': [2]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['moncton', 'parish', '582.20', '8861', '427 of 5008'], ['shediac', 'parish', '238.47', '4801', '709 of 5008'], ['salisbury', 'parish', '873.55', '3425', '909 of 5008'], ['botsford', 'parish', '303.75', '1203', '1827 of 5008'], ['sackville', 'parish', '578.28', '1174', '1857 of 5008'], ['westmorland', 'parish', '173.4... |
united states house of representatives elections , 1880 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1880 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1431558-4.html.csv | majority | all of the incumbents from south carolina in the united states house of representatives 1880 elections were with the democratic party . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'democratic', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to democratic .', 'tostr': 'all_eq { all_rows ; party ; democratic } = true'} | all_eq { all_rows ; party ; democratic } = true | for the party records of all rows , all of them fuzzily match to democratic . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result'] | [['south carolina 1', 'john s richardson', 'democratic', '1878', 're - elected'], ['south carolina 2', "michael p o'connor", 'democratic', '1878', 're - elected'], ['south carolina 3', 'd wyatt aiken', 'democratic', '1876', 're - elected'], ['south carolina 4', 'john h evins', 'democratic', '1876', 're - elected'], ['s... |
2005 pga championship | https://en.wikipedia.org/wiki/2005_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12512153-2.html.csv | comparative | john daly had won a pga championship earlier than david toms . | {'row_1': '6', 'row_2': '5', 'col': '3', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'john daly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to john daly .', 'tostr': 'filter_eq { all_rows ; player ; john daly }'}, 'year ( s ) won'], 'result': N... | less { hop { filter_eq { all_rows ; player ; john daly } ; year ( s ) won } ; hop { filter_eq { all_rows ; player ; david toms } ; year ( s ) won } } = true | select the rows whose player record fuzzily matches to john daly . take the year ( s ) won record of this row . select the rows whose player record fuzzily matches to david toms . take the year ( s ) won record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'john daly_8': 8, 'year (s) won_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'david toms_12': 12, 'year (s) won_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'john daly_8': 'john daly', 'year (s) won_9': 'year ( s ) won', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player',... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'john daly_8': [0], 'year (s) won_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'david toms_12': [1], 'year (s) won_13': [3]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['steve elkington', 'australia', '1995', '277', '- 3', 't2'], ['davis love iii', 'united states', '1997', '278', '- 2', 't4'], ['tiger woods', 'united states', '1999 , 2000', '278', '- 2', 't4'], ['vijay singh', 'fiji', '1998 , 2004', '280', 'e', 't10'], ['david toms', 'united states', '2001', '280', 'e', 't10'], ['jo... |
1972 baltimore colts season | https://en.wikipedia.org/wiki/1972_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14959246-2.html.csv | comparative | the game against the san diego chargers was seven days before the game against the dallas cowboys . | {'row_1': '4', 'row_2': '5', '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', 'opponent', 'san diego chargers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to san diego chargers .', 'tostr': 'filter_eq { all_rows ; opponent ; san diego chargers }'... | less { hop { filter_eq { all_rows ; opponent ; san diego chargers } ; date } ; hop { filter_eq { all_rows ; opponent ; dallas cowboys } ; date } } = true | select the rows whose opponent record fuzzily matches to san diego chargers . take the date record of this row . select the rows whose opponent record fuzzily matches to dallas cowboys . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'san diego chargers_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'dallas cowboys_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'san diego chargers_8': 'san diego chargers', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'op... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'san diego chargers_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'dallas cowboys_12': [1], 'date_13': [3]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 17 , 1972', 'st louis cardinals', 'l 3 - 10', '0 - 1', 'memorial stadium', '53562'], ['2', 'september 24 , 1972', 'new york jets', 'l 34 - 44', '0 - 2', 'memorial stadium', '56626'], ['3', 'october 1 , 1972', 'buffalo bills', 'w 17 - 0', '1 - 2', 'war memorial stadium', '46206'], ['4', 'october 8 , 19... |
swimming at the 2000 summer olympics - men 's 100 metre butterfly | https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Men%27s_100_metre_butterfly | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12446342-5.html.csv | ordinal | anatoly polyakov had the 3rd longest time in the men 's 100 metre butterfly during the 2000 summer olympics . | {'row': '6', 'col': '5', 'order': '3', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'time', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; time ; 3 }'}, 'name'], 'result': 'anatoly polyakov', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; time ; 3 } ; name }'}, 'anatoly polyakov']... | eq { hop { nth_argmax { all_rows ; time ; 3 } ; name } ; anatoly polyakov } = true | select the row whose time record of all rows is 3rd maximum . the name record of this row is anatoly polyakov . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'time_5': 5, '3_6': 6, 'name_7': 7, 'anatoly polyakov_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', 'time_5': 'time', '3_6': '3', 'name_7': 'name', 'anatoly polyakov_8': 'anatoly polyakov'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'time_5': [0], '3_6': [0], 'name_7': [1], 'anatoly polyakov_8': [2]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '4', 'michael klim', 'australia', '52.63'], ['2', '2', 'ian crocker', 'united states', '52.82'], ['3', '3', 'lars frölander', 'sweden', '52.84'], ['4', '5', 'mike mintenko', 'canada', '53.00'], ['5', '1', 'thomas rupprath', 'germany', '53.18'], ['6', '6', 'anatoly polyakov', 'russia', '53.32'], ['7', '7', 'franc... |
usa today all - usa high school basketball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11677760-10.html.csv | majority | the majority of players on the usa today all - usa high school basketball team were taken in the 1st round of the nba draft . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1st round', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nba draft', '1st round'], 'result': True, 'ind': 0, 'tointer': 'for the nba draft records of all rows , most of them fuzzily match to 1st round .', 'tostr': 'most_eq { all_rows ; nba draft ; 1st round } = true'} | most_eq { all_rows ; nba draft ; 1st round } = true | for the nba draft records of all rows , most of them fuzzily match to 1st round . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nba draft_3': 3, '1st round_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nba draft_3': 'nba draft', '1st round_4': '1st round'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nba draft_3': [0], '1st round_4': [0]} | ['player', 'height', 'school', 'hometown', 'college', 'nba draft'] | [['alonzo mourning', '6 - 10', 'indian river high school', 'chesapeake , va', 'georgetown', '1st round - 2nd pick of 1992 draft ( hornets )'], ['chris jackson', '6 - 0', 'gulfport high school', 'gulfport , ms', 'lsu', '1st round - 3rd pick of 1990 draft ( nuggets )'], ['chris mills', '6 - 7', 'fairfax high school', 'lo... |
adriano buzaid | https://en.wikipedia.org/wiki/Adriano_Buzaid | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23128286-1.html.csv | superlative | adriano buzaid scored the highest amount of points in his career in the 2008 formula renault uk . | {'scope': 'all', 'col_superlative': '9', 'row_superlative': '5', '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', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'series'], 'result': 'formula renault uk', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; series }'}, 'formula renault uk'], 'result':... | eq { hop { argmax { all_rows ; points } ; series } ; formula renault uk } = true | select the row whose points record of all rows is maximum . the series record of this row is formula renault uk . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'series_6': 6, 'formula renault uk_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'series_6': 'series', 'formula renault uk_7': 'formula renault uk'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'series_6': [1], 'formula renault uk_7': [2]} | ['season', 'series', 'team name', 'races', 'wins', 'poles', 'flaps', 'podiums', 'points', 'final placing'] | [['2006', 'formula ford uk', 'eau rouge motorsport', '17', '1', '0', '1', '1', '186', '13th'], ['2006', 'formula renault uk winter series', 'aka lemac', '4', '0', '0', '0', '1', '58', '7th'], ['2007', 'formula renault uk', 'eucatex', '20', '0', '0', '0', '2', '166', '13th'], ['2007', 'formula renault uk winter series',... |
2001 belarusian premier league | https://en.wikipedia.org/wiki/2001_Belarusian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14747610-1.html.csv | count | in the 2001 belarusian premier league , among the venues named central , 2 of them have capacity over 5,000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '5000', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'fuzzily_match', 'value': 'central'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'central'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; central }', 'tointer': 'select the rows whose venue record fuzzily matches to central .'}, 'capaci... | eq { count { filter_greater { filter_eq { all_rows ; venue ; central } ; capacity ; 5000 } } ; 2 } = true | select the rows whose venue record fuzzily matches to central . among these rows , select the rows whose capacity record is greater than 5000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'venue_6': 6, 'central_7': 7, 'capacity_8': 8, '5000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'venue_6': 'venue', 'central_7': 'central', 'capacity_8': 'capacity', '5000_9': '5000', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'venue_6': [0], 'central_7': [0], 'capacity_8': [1], '5000_9': [1], '2_10': [3]} | ['team', 'location', 'venue', 'capacity', 'position in 2000'] | [['slavia', 'mozyr', 'yunost', '5500', '1'], ['bate', 'borisov', 'city stadium , borisov', '5500', '2'], ['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '3'], ['neman - belcard', 'grodno', 'neman', '6300', '4'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '5'], ['gomel', 'gomel', 'central , gomel', '11800', '6'... |
2008 italian motorcycle grand prix | https://en.wikipedia.org/wiki/2008_Italian_motorcycle_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16212245-1.html.csv | count | four competitors in the 2008 italian motorcycle grand prix did not complete the race due to accidents . | {'scope': 'all', 'criterion': 'equal', 'value': 'accident', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', 'accident'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to accident .', 'tostr': 'filter_eq { all_rows ; time ; accident }'}], 'result': '4', 'ind': 1, 'tostr': 'count {... | eq { count { filter_eq { all_rows ; time ; accident } } ; 4 } = true | select the rows whose time record fuzzily matches to accident . 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, 'time_5': 5, 'accident_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', 'time_5': 'time', 'accident_6': 'accident', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'time_5': [0], 'accident_6': [0], '4_7': [2]} | ['rider', 'manufacturer', 'laps', 'time', 'grid'] | [['valentino rossi', 'yamaha', '23', '42:31.153', '1'], ['casey stoner', 'ducati', '23', '+ 2.201', '4'], ['dani pedrosa', 'honda', '23', '+ 4.867', '2'], ['alex de angelis', 'honda', '23', '+ 6.313', '10'], ['colin edwards', 'yamaha', '23', '+ 12.530', '5'], ['james toseland', 'yamaha', '23', '+ 13.806', '8'], ['loris... |
nishi - ōhira domain | https://en.wikipedia.org/wiki/Nishi-%C5%8Chira_Domain | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12803263-1.html.csv | unique | ōoka tadatomo was the only daimyōs with revenues above 10000 koku . | {'scope': 'all', 'row': '4', 'col': '6', 'col_other': '2', 'criterion': 'greater_than', 'value': '10000 koku', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'revenues', '10000 koku'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose revenues record is greater than 10000 koku .', 'tostr': 'filter_greater { all_rows ; revenues ; 10000 koku }'}], 'result': True, 'ind'... | and { only { filter_greater { all_rows ; revenues ; 10000 koku } } ; eq { hop { filter_greater { all_rows ; revenues ; 10000 koku } ; name } ; ōoka tadatomo ( 大岡忠與 ) } } = true | select the rows whose revenues record is greater than 10000 koku . there is only one such row in the table . the name record of this unqiue row is ōoka tadatomo ( 大岡忠與 ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'revenues_7': 7, '10000 koku_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'ōoka tadatomo (大岡忠與)_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'revenues_7': 'revenues', '10000 koku_8': '10000 koku', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'ōoka tadatomo (大岡忠與)_10': 'ōoka tadatomo ( 大岡忠與 )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'revenues_7': [0], '10000 koku_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'ōoka tadatomo (大岡忠與)_10': [3]} | ['', 'name', 'tenure', 'courtesy title', 'court rank', 'revenues', 'lineage'] | [['1', 'ōoka tadasuke ( 大岡忠相 )', '1748 - 1751', 'echizen - no - kami ( 越前守 )', 'lower 5th ( 従五位下 )', '10000 koku', '4th son of hatamoto ōoka tadataka'], ['2', 'ōoka tadayoshi ( 大岡忠宜 )', '1755 - 1766', 'echizen - no - kami ( 越前守 )', 'lower 5th ( 従五位下 )', '10000 koku', '2nd son of tadasuke'], ['3', 'ōoka tadatsune ( 大岡忠恒... |
skins ( north american tv series ) | https://en.wikipedia.org/wiki/Skins_%28North_American_TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29545336-2.html.csv | aggregation | skins had a total of 2.20 million viewers in the us in the last two episodes . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '2.20', 'subset': {'col': '1', 'criterion': 'greater_than_eq', 'value': '8'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'no', '8'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; no ; 8 }', 'tointer': 'select the rows whose no record is greater than or equal to 8 .'}, 'us viewers ( millions )'], 'result': '2.20',... | round_eq { sum { filter_greater_eq { all_rows ; no ; 8 } ; us viewers ( millions ) } ; 2.20 } = true | select the rows whose no record is greater than or equal to 8 . the sum of the us viewers ( millions ) record of these rows is 2.20 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'no_5': 5, '8_6': 6, 'us viewers (millions)_7': 7, '2.20_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'no_5': 'no', '8_6': '8', 'us viewers (millions)_7': 'us viewers ( millions )', '2.20_8': '2.20'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'no_5': [0], '8_6': [0], 'us viewers (millions)_7': [1], '2.20_8': [2]} | ['no', 'title', 'directed by', 'written by', 'featured character ( s )', 'us viewers ( millions )', 'original air date'] | [['1', 'tony', 'scott smith', 'bryan elsley', 'tony snyder', '3.26', 'january 17 , 2011'], ['2', 'tea', 'scott smith', 'bryan elsley', 'tea marvelli', '1.58', 'january 24 , 2011'], ['3', 'chris', 'scott smith', "jack thorne and ryan o'nan", 'chris collins', '1.45', 'january 31 , 2011'], ['4', 'cadie', 'samir rehem', 'm... |
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