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2007 - 08 minnesota wild season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Minnesota_Wild_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11739153-10.html.csv | count | in the 2007 - 08 minnesota wild season , when the home team was minnesota , there were 2 games where the attendance was at least 19360 . | {'scope': 'subset', 'criterion': 'greater_than_eq', 'value': '19360', 'result': '2', 'col': '6', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'minnesota'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home', 'minnesota'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; home ; minnesota }', 'tointer': 'select the rows whose home record fuzzily matches to minnesota .'}, 'attendance', '19360'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home record fuzzily matches to minnesota . among these rows , select the rows whose attendance record is greater than or equal to 19360 .', 'tostr': 'filter_greater_eq { filter_eq { all_rows ; home ; minnesota } ; attendance ; 19360 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater_eq { filter_eq { all_rows ; home ; minnesota } ; attendance ; 19360 } }', 'tointer': 'select the rows whose home record fuzzily matches to minnesota . among these rows , select the rows whose attendance record is greater than or equal to 19360 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater_eq { filter_eq { all_rows ; home ; minnesota } ; attendance ; 19360 } } ; 2 } = true', 'tointer': 'select the rows whose home record fuzzily matches to minnesota . among these rows , select the rows whose attendance record is greater than or equal to 19360 . the number of such rows is 2 .'} | eq { count { filter_greater_eq { filter_eq { all_rows ; home ; minnesota } ; attendance ; 19360 } } ; 2 } = true | select the rows whose home record fuzzily matches to minnesota . among these rows , select the rows whose attendance record is greater than or equal to 19360 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'home_6': 6, 'minnesota_7': 7, 'attendance_8': 8, '19360_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_eq_1': 'filter_greater_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'home_6': 'home', 'minnesota_7': 'minnesota', 'attendance_8': 'attendance', '19360_9': '19360', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'home_6': [0], 'minnesota_7': [0], 'attendance_8': [1], '19360_9': [1], '2_10': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'series'] | [['april 9', 'colorado', '3 - 2', 'minnesota', 'backstrom', '19352', '0 - 1'], ['april 11', 'colorado', '2 - 3', 'minnesota', 'backstrom', '19360', '1 - 1'], ['april 14', 'minnesota', '3 - 2', 'colorado', 'backstrom', '18007', '2 - 1'], ['april 15', 'minnesota', '1 - 5', 'colorado', 'backstrom', '18007', '2 - 2'], ['april 17', 'colorado', '3 - 2', 'minnesota', 'backstrom', '19364', '2 - 3'], ['april 19', 'minnesota', '1 - 2', 'colorado', 'backstrom', '18007', '2 - 4']] |
saltwood miniature railway | https://en.wikipedia.org/wiki/Saltwood_Miniature_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11658983-1.html.csv | count | among steam locomotives of saltwood miniature railway , two of them were withdrawn after 1969 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '1969', 'result': '2', 'col': '6', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'steam'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'locomotive type', 'steam'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; locomotive type ; steam }', 'tointer': 'select the rows whose locomotive type record fuzzily matches to steam .'}, 'withdrawn', '1969'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose locomotive type record fuzzily matches to steam . among these rows , select the rows whose withdrawn record is greater than 1969 .', 'tostr': 'filter_greater { filter_eq { all_rows ; locomotive type ; steam } ; withdrawn ; 1969 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; locomotive type ; steam } ; withdrawn ; 1969 } }', 'tointer': 'select the rows whose locomotive type record fuzzily matches to steam . among these rows , select the rows whose withdrawn record is greater than 1969 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; locomotive type ; steam } ; withdrawn ; 1969 } } ; 2 } = true', 'tointer': 'select the rows whose locomotive type record fuzzily matches to steam . among these rows , select the rows whose withdrawn record is greater than 1969 . the number of such rows is 2 .'} | eq { count { filter_greater { filter_eq { all_rows ; locomotive type ; steam } ; withdrawn ; 1969 } } ; 2 } = true | select the rows whose locomotive type record fuzzily matches to steam . among these rows , select the rows whose withdrawn record is greater than 1969 . 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, 'locomotive type_6': 6, 'steam_7': 7, 'withdrawn_8': 8, '1969_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', 'locomotive type_6': 'locomotive type', 'steam_7': 'steam', 'withdrawn_8': 'withdrawn', '1969_9': '1969', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'locomotive type_6': [0], 'steam_7': [0], 'withdrawn_8': [1], '1969_9': [1], '2_10': [3]} | ['number', 'locomotive type', 'wheel arrangement', 'builder', 'entered service', 'withdrawn'] | [['1', 'steam', '0 - 4 - 2 tank', 'jubb engineering', '1922', '1928'], ['471', 'steam', '4 - 4 - 2 atlantic', 'f & a schwab', '1928', '1970'], ['260', 'steam', '2 - 6 - 0 mogul', 'f & a schwab & henry greenly', '1939', '1975'], ['5060', 'battery electric', "bo ' 2 '", 'tom smith', '1974', '1987'], ['7007', 'battery electric', "bo ' 2 '", 'tom smith', '1976', '1987']] |
orlando magic all - time roster | https://en.wikipedia.org/wiki/Orlando_Magic_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15621965-10.html.csv | comparative | on the roster jon koncak played in years earlier than tim kempton . | {'row_1': '7', 'row_2': '3', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'jon koncak'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to jon koncak .', 'tostr': 'filter_eq { all_rows ; player ; jon koncak }'}, 'years in orlando'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; jon koncak } ; years in orlando }', 'tointer': 'select the rows whose player record fuzzily matches to jon koncak . take the years in orlando record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'tim kempton'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to tim kempton .', 'tostr': 'filter_eq { all_rows ; player ; tim kempton }'}, 'years in orlando'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; tim kempton } ; years in orlando }', 'tointer': 'select the rows whose player record fuzzily matches to tim kempton . take the years in orlando record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; jon koncak } ; years in orlando } ; hop { filter_eq { all_rows ; player ; tim kempton } ; years in orlando } } = true', 'tointer': 'select the rows whose player record fuzzily matches to jon koncak . take the years in orlando record of this row . select the rows whose player record fuzzily matches to tim kempton . take the years in orlando record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; jon koncak } ; years in orlando } ; hop { filter_eq { all_rows ; player ; tim kempton } ; years in orlando } } = true | select the rows whose player record fuzzily matches to jon koncak . take the years in orlando record of this row . select the rows whose player record fuzzily matches to tim kempton . take the years in orlando 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, 'player_7': 7, 'jon koncak_8': 8, 'years in orlando_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'tim kempton_12': 12, 'years in orlando_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', 'player_7': 'player', 'jon koncak_8': 'jon koncak', 'years in orlando_9': 'years in orlando', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'tim kempton_12': 'tim kempton', 'years in orlando_13': 'years in orlando'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'jon koncak_8': [0], 'years in orlando_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'tim kempton_12': [1], 'years in orlando_13': [3]} | ['player', 'no', 'nationality', 'position', 'years in orlando', 'school / club team'] | [['mario kasun', '41', 'croatia', 'center', '2004 - 2006', 'gonzaga'], ['shawn kemp', '40', 'united states', 'forward', '2002 - 2003', 'concord hs'], ['tim kempton', '9', 'united states', 'forward - center', '2002 - 2004', 'notre dame'], ['jonathan kerner', '52', 'united states', 'center', '1998 - 1999', 'east carolina'], ['steve kerr', '2', 'united states', 'guard', '1992 - 1993', 'arizona'], ['greg kite', '34', 'united states', 'center', '1990 - 1994', 'byu'], ['jon koncak', '45', 'united states', 'center', '1995 - 1996', 'southern methodist']] |
bring ya to the brink | https://en.wikipedia.org/wiki/Bring_Ya_to_the_Brink | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16953587-4.html.csv | ordinal | the first release of " bring ya to the brink " was in japan on may 14 , 2008 . | {'row': '1', 'col': '2', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 1 }'}, 'date'], 'result': 'may 14 , 2008', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 1 } ; date }'}, 'may 14 , 2008'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 1 } ; date } ; may 14 , 2008 } = true', 'tointer': 'select the row whose date record of all rows is 1st minimum . the date record of this row is may 14 , 2008 .'} | eq { hop { nth_argmin { all_rows ; date ; 1 } ; date } ; may 14 , 2008 } = true | select the row whose date record of all rows is 1st minimum . the date record of this row is may 14 , 2008 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '1_6': 6, 'date_7': 7, 'may 14 , 2008_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '1_6': '1', 'date_7': 'date', 'may 14 , 2008_8': 'may 14 , 2008'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '1_6': [0], 'date_7': [1], 'may 14 , 2008_8': [2]} | ['region', 'date', 'label', 'format', 'catalog'] | [['japan', 'may 14 , 2008', 'sony music japan', 'cd with bonus tracks', 'eicp 968'], ['united states uk', 'may 27 , 2008', 'epic records', 'cd', '706592'], ['united states uk', 'may 27 , 2008', 'epic records', 'paid download', '706592'], ['argentina', 'may 27 , 2008', 'sony bmg', 'cd', '706592'], ['finland', 'may 28 , 2008', '-', '-', '-'], ['australia', 'june 7 , 2008', 'epic', 'cd', '88697065922'], ['australia', 'june 7 , 2008', 'epic', 'paid download', '88697065922'], ['indonesia', 'august 15 , 2008', 'sony bmg', 'cd', '-'], ['indonesia', 'august 15 , 2008', 'sony bmg', 'cassette', '-']] |
chiefs - raiders rivalry | https://en.wikipedia.org/wiki/Chiefs%E2%80%93Raiders_rivalry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11840325-7.html.csv | aggregation | during the 2000-2009 decade , when the raiders won against the chiefs they scored an average of 25.5 points . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '25.5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'kansas city chiefs'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'loser', 'kansas city chiefs'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; loser ; kansas city chiefs }', 'tointer': 'select the rows whose loser record fuzzily matches to kansas city chiefs .'}, 'result'], 'result': '25.5', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; loser ; kansas city chiefs } ; result }'}, '25.5'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; loser ; kansas city chiefs } ; result } ; 25.5 } = true', 'tointer': 'select the rows whose loser record fuzzily matches to kansas city chiefs . the average of the result record of these rows is 25.5 .'} | round_eq { avg { filter_eq { all_rows ; loser ; kansas city chiefs } ; result } ; 25.5 } = true | select the rows whose loser record fuzzily matches to kansas city chiefs . the average of the result record of these rows is 25.5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'loser_5': 5, 'kansas city chiefs_6': 6, 'result_7': 7, '25.5_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'loser_5': 'loser', 'kansas city chiefs_6': 'kansas city chiefs', 'result_7': 'result', '25.5_8': '25.5'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'loser_5': [0], 'kansas city chiefs_6': [0], 'result_7': [1], '25.5_8': [2]} | ['year', 'date', 'winner', 'result', 'loser', 'location'] | [['2000', 'october 15', 'oakland raiders', '20 - 17', 'kansas city chiefs', 'arrowhead stadium'], ['2000', 'november 5', 'oakland raiders', '49 - 31', 'kansas city chiefs', 'network associates coliseum'], ['2001', 'september 9', 'oakland raiders', '27 - 24', 'kansas city chiefs', 'arrowhead stadium'], ['2001', 'december 9', 'oakland raiders', '28 - 26', 'kansas city chiefs', 'network associates coliseum'], ['2002', 'october 27', 'kansas city chiefs', '20 - 10', 'oakland raiders', 'arrowhead stadium'], ['2002', 'december 28', 'oakland raiders', '24 - 0', 'kansas city chiefs', 'network associates coliseum'], ['2003', 'october 20', 'kansas city chiefs', '17 - 10', 'oakland raiders', 'network associates coliseum'], ['2003', 'november 23', 'kansas city chiefs', '27 - 24', 'oakland raiders', 'arrowhead stadium'], ['2004', 'december 5', 'kansas city chiefs', '34 - 27', 'oakland raiders', 'network associates coliseum'], ['2004', 'december 25', 'kansas city chiefs', '31 - 30', 'oakland raiders', 'arrowhead stadium'], ['2005', 'september 18', 'kansas city chiefs', '23 - 17', 'oakland raiders', 'mcafee coliseum'], ['2005', 'november 6', 'kansas city chiefs', '27 - 23', 'oakland raiders', 'arrowhead stadium'], ['2006', 'november 19', 'kansas city chiefs', '17 - 13', 'oakland raiders', 'arrowhead stadium'], ['2006', 'december 23', 'kansas city chiefs', '20 - 9', 'oakland raiders', 'mcafee coliseum'], ['2007', 'october 21', 'kansas city chiefs', '12 - 10', 'oakland raiders', 'mcafee coliseum'], ['2007', 'november 25', 'oakland raiders', '20 - 17', 'kansas city chiefs', 'arrowhead stadium'], ['2008', 'september 14', 'oakland raiders', '23 - 8', 'kansas city chiefs', 'arrowhead stadium'], ['2008', 'november 30', 'kansas city chiefs', '20 - 13', 'oakland raiders', 'oakland - alameda county coliseum'], ['2009', 'september 20', 'oakland raiders', '13 - 10', 'kansas city chiefs', 'arrowhead stadium'], ['2009', 'november 15', 'kansas city chiefs', '16 - 10', 'oakland raiders', 'oakland - alameda county coliseum']] |
list of soccer clubs in australia | https://en.wikipedia.org/wiki/List_of_soccer_clubs_in_Australia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1742186-16.html.csv | comparative | salisbury united was founded before south adelaide was founded . | {'row_1': '5', 'row_2': '7', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'salisbury united'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to salisbury united .', 'tostr': 'filter_eq { all_rows ; team ; salisbury united }'}, 'founded'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; salisbury united } ; founded }', 'tointer': 'select the rows whose team record fuzzily matches to salisbury united . take the founded record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'south adelaide'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to south adelaide .', 'tostr': 'filter_eq { all_rows ; team ; south adelaide }'}, 'founded'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; south adelaide } ; founded }', 'tointer': 'select the rows whose team record fuzzily matches to south adelaide . take the founded record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; team ; salisbury united } ; founded } ; hop { filter_eq { all_rows ; team ; south adelaide } ; founded } } = true', 'tointer': 'select the rows whose team record fuzzily matches to salisbury united . take the founded record of this row . select the rows whose team record fuzzily matches to south adelaide . take the founded record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; team ; salisbury united } ; founded } ; hop { filter_eq { all_rows ; team ; south adelaide } ; founded } } = true | select the rows whose team record fuzzily matches to salisbury united . take the founded record of this row . select the rows whose team record fuzzily matches to south adelaide . take the founded 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, 'team_7': 7, 'salisbury united_8': 8, 'founded_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'south adelaide_12': 12, 'founded_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', 'team_7': 'team', 'salisbury united_8': 'salisbury united', 'founded_9': 'founded', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'south adelaide_12': 'south adelaide', 'founded_13': 'founded'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'salisbury united_8': [0], 'founded_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'south adelaide_12': [1], 'founded_13': [3]} | ['team', 'coach', 'home ground', 'location', 'founded'] | [['the cove sc', 'danny graystone', 'club cove', 'hallett cove', '1983'], ['gawler', 'john duthie', 'karbeethan reserve', 'evanston', '1978'], ['nab', 'unknown', 'athelstone recreation reserve', 'athelstone', '1989'], ['northern demons', 'anthony brevi', 'byrne park', 'port pirie', '1951'], ['salisbury united', 'unknown', 'steve jarvis park', 'salisbury', '1954'], ['seaford', 'ben dale', 'karingal reserve', 'seaford', '1970'], ['south adelaide', 'aldo maricic', "o ' sullivan beach sports complex", "o ' sullivan beach", '1997'], ['sturt lions fc', 'alan paice', 'a a bailey recreation ground', 'clarence gardens', '2011'], ['western toros', 'leigh mathews', 'pennington oval', 'pennington', 'unknown'], ['west adelaide', 'ross aloisi', 'kingston gardens', 'adelaide', '1962']] |
1956 vfl season | https://en.wikipedia.org/wiki/1956_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10640687-7.html.csv | count | there were 6 game venues used during the 1956 vfl season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; venue } } ; 6 } = true', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'} | eq { count { filter_all { all_rows ; venue } } ; 6 } = true | select the rows whose venue record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '15.7 ( 97 )', 'south melbourne', '7.16 ( 58 )', 'arden street oval', '13000', '26 may 1956'], ['st kilda', '9.10 ( 64 )', 'richmond', '6.8 ( 44 )', 'junction oval', '15800', '26 may 1956'], ['hawthorn', '8.10 ( 58 )', 'fitzroy', '9.13 ( 67 )', 'glenferrie oval', '18000', '26 may 1956'], ['geelong', '15.17 ( 107 )', 'essendon', '8.9 ( 57 )', 'kardinia park', '21758', '26 may 1956'], ['melbourne', '11.13 ( 79 )', 'collingwood', '9.7 ( 61 )', 'mcg', '46868', '26 may 1956'], ['footscray', '7.13 ( 55 )', 'carlton', '8.8 ( 56 )', 'western oval', '33089', '26 may 1956']] |
b " swimming at the 2007 world aquatics championships - men 's 200 metre freestyle " | https://en.wikipedia.org/wiki/Swimming_at_the_2007_World_Aquatics_Championships_%E2%80%93_Men%27s_200_metre_freestyle | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10563642-4.html.csv | count | 8 athletes participated in the men 's 200 metre freestyle at the 2007 world aquatics championships . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '8', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'name'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record is arbitrary .', 'tostr': 'filter_all { all_rows ; name }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; name } }', 'tointer': 'select the rows whose name record is arbitrary . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; name } } ; 8 } = true', 'tointer': 'select the rows whose name record is arbitrary . the number of such rows is 8 .'} | eq { count { filter_all { all_rows ; name } } ; 8 } = true | select the rows whose name record is arbitrary . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'name_5': 5, '8_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'name_5': 'name', '8_6': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'name_5': [0], '8_6': [2]} | ['lane', 'name', 'nationality', '100 m', '150 m', 'time'] | [['5', 'michael phelps', 'united states', '51.00', '1:17.73', '1:43.86 wr'], ['4', 'pieter van den hoogenband', 'netherlands', '51.17', '1:18.16', '1:46.28'], ['2', 'park tae - hwan', 'south korea', '52.74', '1:19.51', '1:46.73'], ['6', 'kenrick monk', 'australia', '52.52', '1:19.88', '1:47.12'], ['3', 'massimiliano rosolino', 'italy', '52.02', '1:19.15', '1:47.18'], ['7', 'zhang lin', 'china', '53.22', '1:20.89', '1:47.53'], ['1', 'paul biedermann', 'germany', '53.17', '1:20.60', '1:48.09'], ['8', 'nicola cassio', 'italy', '53.37', '1:21.00', '1:49.13']] |
dwsn | https://en.wikipedia.org/wiki/DWSN | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17487395-1.html.csv | aggregation | the average frequencies of the mom 's radio branding are about 95.9 mega hertz . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '95.9 mega hertz', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'frequency'], 'result': '95.9 mega hertz', 'ind': 0, 'tostr': 'avg { all_rows ; frequency }'}, '95.9 mega hertz'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; frequency } ; 95.9 mega hertz } = true', 'tointer': 'the average of the frequency record of all rows is 95.9 mega hertz .'} | round_eq { avg { all_rows ; frequency } ; 95.9 mega hertz } = true | the average of the frequency record of all rows is 95.9 mega hertz . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'frequency_4': 4, '95.9 mega hertz_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'frequency_4': 'frequency', '95.9 mega hertz_5': '95.9 mega hertz'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'frequency_4': [0], '95.9 mega hertz_5': [1]} | ['branding', 'callsign', 'frequency', 'power ( kw )', 'location'] | [["mom 's radio 97.9 laoag", 'dwsn - fm', '97.9 mhz', '5 kw', 'laoag'], ["mom 's radio 95.9 naga", 'dzrb - fm', '95.9 mhz', '10 kw', 'naga'], ["mom 's radio 90.3 bacolod", 'dycp - fm', '90.3 mhz', '5 kw', 'bacolod'], ["mom 's radio 88.3 cebu", 'dyap - fm', '88.3 mhz', '5 kw', 'cebu'], ["mom 's radio 101.5 tacloban", 'dyjp - fm', '101.5 mhz', '2.5 kw', 'tacloban'], ["mom 's radio 101.9 zamboanga", 'dxjp - fm', '101.9 mhz', '5 kw', 'zamboanga'], ["mom 's radio 97.9 davao", 'dxss', '97.9 mhz', '10 kw', 'davao']] |
piia pantsu | https://en.wikipedia.org/wiki/Piia_Pantsu | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16178073-1.html.csv | count | two of the competitions took place in the year 2005 . | {'scope': 'all', 'criterion': 'equal', 'value': '2005', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2005'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 2005 .', 'tostr': 'filter_eq { all_rows ; year ; 2005 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; year ; 2005 } }', 'tointer': 'select the rows whose year record is equal to 2005 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; year ; 2005 } } ; 2 } = true', 'tointer': 'select the rows whose year record is equal to 2005 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; year ; 2005 } } ; 2 } = true | select the rows whose year record is equal to 2005 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, '2005_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '2005_6': '2005', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '2005_6': [0], '2_7': [2]} | ['competition', 'place', 'year', 'horse', 'rank'] | [['world championship', 'haag', '1994', 'cyna', '5'], ['european championship', 'rome', '1995', 'cyna', '4'], ['european championship', 'burghley', '1997', 'cyna', 'stopped in second event'], ['world championship', 'rooma', '1998', 'uppercut', '9'], ['european championship', 'luhmühlen', '1999', 'uppercut', '4'], ['olympics', 'sydney', '2000', 'uppercut', 'disqualification in second event'], ['european championship', 'pau', '2001', 'ypäjä karuso', '17'], ['world championship', 'jerez', '2002', 'ypäjä karuso', '3'], ['badminton horse trials', 'gloucestershire , england', '2003', 'ypäjä karuso', '2'], ['european championship', 'blenheim', '2005', 'ypäjä karuso', '6'], ['world cup final', 'malmö', '2005', 'ypäjä karuso', '3'], ['world championship', 'aachen', '2006', 'ypäjä karuso', 'stopped in second event'], ['finland championship', 'kerava , finland', '2007', 'ypäjä karuso', '1']] |
turkmenistan fed cup team | https://en.wikipedia.org/wiki/Turkmenistan_Fed_Cup_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11311764-4.html.csv | count | two of the players on the turkmenistan fed cup team recorded 18 ties . | {'scope': 'all', 'criterion': 'equal', 'value': '18', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'ties', '18'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ties record is equal to 18 .', 'tostr': 'filter_eq { all_rows ; ties ; 18 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; ties ; 18 } }', 'tointer': 'select the rows whose ties record is equal to 18 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; ties ; 18 } } ; 2 } = true', 'tointer': 'select the rows whose ties record is equal to 18 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; ties ; 18 } } ; 2 } = true | select the rows whose ties record is equal to 18 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'ties_5': 5, '18_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'ties_5': 'ties', '18_6': '18', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'ties_5': [0], '18_6': [0], '2_7': [2]} | ['name', 'tkm career', 'ties', 'dou w / l', 'sin w / l'] | [['anastasiya prenko', '2008 -', '18', '9 - 6', '10 - 7'], ['jenneta halliyeva', '2004 - 2013', '18', '5 - 6', '4 - 5'], ['ummarahmat hummetova', '2004 - 2012', '13', '3 - 8', '1 - 7'], ['ayna ereshova', '2011', '1', '1 - 0', '0 - 0'], ['guljahan kadryova', '2013', '2', '1 - 0', '0 - 1'], ['amangul mollayeva', '2011', '4', '1 - 0', '0 - 3'], ['jahana bayramova', '2013 -', '5', '1 - 1', '1 - 4'], ['veronika babayan', '2004', '3', '1 - 2', '0 - 1']] |
sun sun | https://en.wikipedia.org/wiki/Sun_Sun | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15624634-2.html.csv | ordinal | the album sun sun by the japanese fusion group casiopea was first released as a cd by alfa records on september 10 , 1986 . | {'scope': 'subset', 'row': '2', 'col': '2', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'cd'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'format', 'cd'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; format ; cd }', 'tointer': 'select the rows whose format record fuzzily matches to cd .'}, 'date', '1'], 'result': 'september 10 , 1986', 'ind': 1, 'tostr': 'nth_min { filter_eq { all_rows ; format ; cd } ; date ; 1 }', 'tointer': 'select the rows whose format record fuzzily matches to cd . the 1st minimum date record of these rows is september 10 , 1986 .'}, 'september 10 , 1986'], 'result': True, 'ind': 2, 'tostr': 'eq { nth_min { filter_eq { all_rows ; format ; cd } ; date ; 1 } ; september 10 , 1986 }', 'tointer': 'select the rows whose format record fuzzily matches to cd . the 1st minimum date record of these rows is september 10 , 1986 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'format', 'cd'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; format ; cd }', 'tointer': 'select the rows whose format record fuzzily matches to cd .'}, 'date', '1'], 'result': None, 'ind': 3, 'tostr': 'nth_argmin { filter_eq { all_rows ; format ; cd } ; date ; 1 }'}, 'label'], 'result': 'alfa records', 'ind': 4, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; format ; cd } ; date ; 1 } ; label }'}, 'alfa records'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; format ; cd } ; date ; 1 } ; label } ; alfa records }', 'tointer': 'the label record of the row with 1st minimum date record is alfa records .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { nth_min { filter_eq { all_rows ; format ; cd } ; date ; 1 } ; september 10 , 1986 } ; eq { hop { nth_argmin { filter_eq { all_rows ; format ; cd } ; date ; 1 } ; label } ; alfa records } } = true', 'tointer': 'select the rows whose format record fuzzily matches to cd . the 1st minimum date record of these rows is september 10 , 1986 . the label record of the row with 1st minimum date record is alfa records .'} | and { eq { nth_min { filter_eq { all_rows ; format ; cd } ; date ; 1 } ; september 10 , 1986 } ; eq { hop { nth_argmin { filter_eq { all_rows ; format ; cd } ; date ; 1 } ; label } ; alfa records } } = true | select the rows whose format record fuzzily matches to cd . the 1st minimum date record of these rows is september 10 , 1986 . the label record of the row with 1st minimum date record is alfa records . | 8 | 7 | {'and_6': 6, 'result_7': 7, 'eq_2': 2, 'nth_min_1': 1, 'filter_str_eq_0': 0, 'all_rows_8': 8, 'format_9': 9, 'cd_10': 10, 'date_11': 11, '1_12': 12, 'september 10 , 1986_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'nth_argmin_3': 3, 'date_14': 14, '1_15': 15, 'label_16': 16, 'alfa records_17': 17} | {'and_6': 'and', 'result_7': 'true', 'eq_2': 'eq', 'nth_min_1': 'nth_min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_8': 'all_rows', 'format_9': 'format', 'cd_10': 'cd', 'date_11': 'date', '1_12': '1', 'september 10 , 1986_13': 'september 10 , 1986', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'nth_argmin_3': 'nth_argmin', 'date_14': 'date', '1_15': '1', 'label_16': 'label', 'alfa records_17': 'alfa records'} | {'and_6': [7], 'result_7': [], 'eq_2': [6], 'nth_min_1': [2], 'filter_str_eq_0': [1, 3], 'all_rows_8': [0], 'format_9': [0], 'cd_10': [0], 'date_11': [1], '1_12': [1], 'september 10 , 1986_13': [2], 'str_eq_5': [6], 'str_hop_4': [5], 'nth_argmin_3': [4], 'date_14': [3], '1_15': [3], 'label_16': [4], 'alfa records_17': [5]} | ['region', 'date', 'label', 'format', 'catalog'] | [['japan', 'september 10 , 1986', 'alfa records', 'stereo lp', 'alr - 28085'], ['japan', 'september 10 , 1986', 'alfa records', 'cd', '32xa - 90'], ['japan', 'march 21 , 1992', 'alfa records', 'cd', 'alca - 285'], ['japan', 'august 31 , 1994', 'alfa records', 'cd', 'alca - 9015'], ['japan', 'august 29 , 1998', 'alfa records', 'cd', 'alca - 9210'], ['japan', 'february 20 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2215'], ['japan', 'march 13 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2235'], ['japan', 'may 27 , 2009', 'sony music direct', 'ed remaster cd', 'mhcl - 20017']] |
dalriada ( band ) | https://en.wikipedia.org/wiki/Dalriada_%28band%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17303372-1.html.csv | superlative | the band dalriada had their highest hungarian top 40 album chart appearance at number 2 , with their album szelek in 2008 . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'min', 'args': ['all_rows', 'hungarian top 40 album charts'], 'result': '2', 'ind': 0, 'tostr': 'min { all_rows ; hungarian top 40 album charts }', 'tointer': 'the minimum hungarian top 40 album charts record of all rows is 2 .'}, '2'], 'result': True, 'ind': 1, 'tostr': 'eq { min { all_rows ; hungarian top 40 album charts } ; 2 }', 'tointer': 'the minimum hungarian top 40 album charts record of all rows is 2 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'hungarian top 40 album charts'], 'result': None, 'ind': 2, 'tostr': 'argmin { all_rows ; hungarian top 40 album charts }'}, 'album'], 'result': 'szelek', 'ind': 3, 'tostr': 'hop { argmin { all_rows ; hungarian top 40 album charts } ; album }'}, 'szelek'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmin { all_rows ; hungarian top 40 album charts } ; album } ; szelek }', 'tointer': 'the album record of the row with superlative hungarian top 40 album charts record is szelek .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { min { all_rows ; hungarian top 40 album charts } ; 2 } ; eq { hop { argmin { all_rows ; hungarian top 40 album charts } ; album } ; szelek } } = true', 'tointer': 'the minimum hungarian top 40 album charts record of all rows is 2 . the album record of the row with superlative hungarian top 40 album charts record is szelek .'} | and { eq { min { all_rows ; hungarian top 40 album charts } ; 2 } ; eq { hop { argmin { all_rows ; hungarian top 40 album charts } ; album } ; szelek } } = true | the minimum hungarian top 40 album charts record of all rows is 2 . the album record of the row with superlative hungarian top 40 album charts record is szelek . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'min_0': 0, 'all_rows_7': 7, 'hungarian top 40 album charts_8': 8, '2_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmin_2': 2, 'all_rows_10': 10, 'hungarian top 40 album charts_11': 11, 'album_12': 12, 'szelek_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'min_0': 'min', 'all_rows_7': 'all_rows', 'hungarian top 40 album charts_8': 'hungarian top 40 album charts', '2_9': '2', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmin_2': 'argmin', 'all_rows_10': 'all_rows', 'hungarian top 40 album charts_11': 'hungarian top 40 album charts', 'album_12': 'album', 'szelek_13': 'szelek'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'min_0': [1], 'all_rows_7': [0], 'hungarian top 40 album charts_8': [0], '2_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmin_2': [3], 'all_rows_10': [2], 'hungarian top 40 album charts_11': [2], 'album_12': [3], 'szelek_13': [4]} | ['year', 'album', 'release type', 'label', 'hungarian top 40 album charts'] | [['2003', 'a walesi bárdok', 'demo', 'self - released', '-'], ['2004', 'fergeteg', 'studio album', 'hammer music / nail records', '-'], ['2006', 'jégbontó', 'studio album', 'hammer music / nail records', '-'], ['2007', 'kikelet', 'studio album', 'hammer music / nail records', '4'], ['2008', 'szelek', 'studio album', 'hammer music / nail records', '2'], ['2009', 'arany - album', 'studio album', 'hammer music / nail records', '4'], ['2011', 'ígéret', 'studio album', 'afm records', '6'], ['2012', 'napisten hava', 'studio album', 'hammer music / nail records', '3']] |
2001 st. louis rams season | https://en.wikipedia.org/wiki/2001_St._Louis_Rams_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10659538-3.html.csv | unique | the game on september 9th , 2001 was the only game where the opponent was the philadelphia eagles . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'philadelphia eagles', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'philadelphia eagles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to philadelphia eagles .', 'tostr': 'filter_eq { all_rows ; opponent ; philadelphia eagles }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; opponent ; philadelphia eagles } }', 'tointer': 'select the rows whose opponent record fuzzily matches to philadelphia eagles . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'philadelphia eagles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to philadelphia eagles .', 'tostr': 'filter_eq { all_rows ; opponent ; philadelphia eagles }'}, 'week'], 'result': '1', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; philadelphia eagles } ; week }'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent ; philadelphia eagles } ; week } ; 1 }', 'tointer': 'the week record of this unqiue row is 1 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; opponent ; philadelphia eagles } } ; eq { hop { filter_eq { all_rows ; opponent ; philadelphia eagles } ; week } ; 1 } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to philadelphia eagles . there is only one such row in the table . the week record of this unqiue row is 1 .'} | and { only { filter_eq { all_rows ; opponent ; philadelphia eagles } } ; eq { hop { filter_eq { all_rows ; opponent ; philadelphia eagles } ; week } ; 1 } } = true | select the rows whose opponent record fuzzily matches to philadelphia eagles . there is only one such row in the table . the week 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, 'opponent_7': 7, 'philadelphia eagles_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'week_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', 'opponent_7': 'opponent', 'philadelphia eagles_8': 'philadelphia eagles', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'week_9': 'week', '1_10': '1'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'opponent_7': [0], 'philadelphia eagles_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'week_9': [2], '1_10': [3]} | ['week', 'date', 'opponent', 'result', 'record', 'tv time', 'attendance'] | [['1', 'september 9 , 2001', 'philadelphia eagles', 'w 20 - 17 ( ot )', '1 - 0', 'fox 3:15 pm', '66243'], ['2', 'september 23 , 2001', 'san francisco 49ers', 'w 30 - 26', '2 - 0', 'fox 3:15 pm', '67536'], ['3', 'september 30 , 2001', 'miami dolphins', 'w 42 - 10', '3 - 0', 'cbs 12:00 pm', '66046'], ['4', 'october 8 , 2001', 'detroit lions', 'w 35 - 0', '4 - 0', 'abc 8:00 pm', '77765'], ['5', 'october 14 , 2001', 'new york giants', 'w 15 - 14', '5 - 0', 'fox 12:00 pm', '65992'], ['6', 'october 21 , 2001', 'new york jets', 'w 34 - 14', '6 - 0', 'fox 12:00 pm', '78766'], ['7', 'october 28 , 2001', 'new orleans saints', 'l 34 - 31', '6 - 1', 'fox 12:00 pm', '66189'], ['8', '-', '-', '-', '-', '-', ''], ['9', 'november 11 , 2001', 'carolina panthers', 'w 48 - 14', '7 - 1', 'fox 12:00 pm', '66069'], ['10', 'november 18 , 2001', 'new england patriots', 'w 24 - 17', '8 - 1', 'espn 7:30 pm', '60292'], ['11', 'november 26 , 2001', 'tampa bay buccaneers', 'l 24 - 17', '8 - 2', 'abc 8:00 pm', '66198'], ['12', 'december 2 , 2001', 'atlanta falcons', 'w 35 - 6', '9 - 2', 'fox 3:15 pm', '60787'], ['13', 'december 9 , 2001', 'san francisco 49ers', 'w 27 - 14', '10 - 2', 'fox 12:00 pm', '66218'], ['14', 'december 17 , 2001', 'new orleans saints', 'w 34 - 21', '11 - 2', 'abc 8:00 pm', '70332'], ['15', 'december 23 , 2001', 'carolina panthers', 'w 38 - 32', '12 - 2', 'fox 12:00 pm', '72438'], ['16', 'december 30 , 2001', 'indianapolis colts', 'w 42 - 17', '13 - 2', 'cbs 12:00 pm', '66084'], ['17', 'january 6 , 2002', 'atlanta falcons', 'w 31 - 13', '14 - 2', 'fox 3:15 pm', '66033']] |
mauro baldi | https://en.wikipedia.org/wiki/Mauro_Baldi | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226503-1.html.csv | comparative | mauro baldi earned more points in his 1983 formula one race as opposed to his 1984 race . | {'row_1': '3', 'row_2': '4', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1983'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1983 .', 'tostr': 'filter_eq { all_rows ; year ; 1983 }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1983 } ; points }', 'tointer': 'select the rows whose year record fuzzily matches to 1983 . take the points record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1984'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1984 .', 'tostr': 'filter_eq { all_rows ; year ; 1984 }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1984 } ; points }', 'tointer': 'select the rows whose year record fuzzily matches to 1984 . take the points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 1983 } ; points } ; hop { filter_eq { all_rows ; year ; 1984 } ; points } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 1983 . take the points record of this row . select the rows whose year record fuzzily matches to 1984 . take the points record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; year ; 1983 } ; points } ; hop { filter_eq { all_rows ; year ; 1984 } ; points } } = true | select the rows whose year record fuzzily matches to 1983 . take the points record of this row . select the rows whose year record fuzzily matches to 1984 . take the points record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '1983_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '1984_12': 12, 'points_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '1983_8': '1983', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '1984_12': '1984', 'points_13': 'points'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '1983_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '1984_12': [1], 'points_13': [3]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1982', 'arrows racing team', 'arrows a4', 'cosworth v8', '2'], ['1982', 'arrows racing team', 'arrows a5', 'cosworth v8', '2'], ['1983', 'marlboro team alfa romeo', 'alfa romeo 183t', 'alfa romeo v8', '3'], ['1984', 'spirit racing', 'spirit 101', 'hart straight - 4', '0'], ['1985', 'spirit enterprises ltd', 'spirit 101d', 'hart straight - 4', '0']] |
1976 - 77 philadelphia flyers season | https://en.wikipedia.org/wiki/1976%E2%80%9377_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14303579-16.html.csv | count | in the 1976-77 philadelphia flyers season , when the nationality is united states , there were two players whose position was wing . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'wing', 'result': '2', 'col': '3', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; nationality ; united states }', 'tointer': 'select the rows whose nationality record fuzzily matches to united states .'}, 'position', 'wing'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nationality record fuzzily matches to united states . among these rows , select the rows whose position record fuzzily matches to wing .', 'tostr': 'filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; wing }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; wing } }', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . among these rows , select the rows whose position record fuzzily matches to wing . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; wing } } ; 2 } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . among these rows , select the rows whose position record fuzzily matches to wing . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; wing } } ; 2 } = true | select the rows whose nationality record fuzzily matches to united states . among these rows , select the rows whose position record fuzzily matches to wing . 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, 'nationality_6': 6, 'united states_7': 7, 'position_8': 8, 'wing_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', 'nationality_6': 'nationality', 'united states_7': 'united states', 'position_8': 'position', 'wing_9': 'wing', '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], 'nationality_6': [0], 'united states_7': [0], 'position_8': [1], 'wing_9': [1], '2_10': [3]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'mark suzor', 'defense', 'canada', 'kingston canadians ( oha )'], ['2', 'drew callander', 'defense', 'canada', 'regina pats ( wchl )'], ['3', 'craig hanmer', 'defense', 'united states', 'mohawk valley comets ( nahl )'], ['4', 'dave hynek', 'defense', 'canada', 'kingston canadians ( oha )'], ['5', 'robin lang', 'defense', 'canada', 'cornell big red ( ecac )'], ['6', 'paul klasinski', 'left wing', 'united states', 'st paul vulcans ( mjhl )'], ['7', 'ray kurpis', 'right wing', 'united states', 'austin mavericks ( mjhl )']] |
2008 indiana fever season | https://en.wikipedia.org/wiki/2008_Indiana_Fever_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17104539-9.html.csv | ordinal | the indiana fever 's game against los angeles recorded their highest attendance of the 2008 season . | {'row': '7', 'col': '8', 'order': '1', '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', 'location / attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location / attendance ; 1 }'}, 'opponent'], 'result': 'los angeles', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location / attendance ; 1 } ; opponent }'}, 'los angeles'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; location / attendance ; 1 } ; opponent } ; los angeles } = true', 'tointer': 'select the row whose location / attendance record of all rows is 1st maximum . the opponent record of this row is los angeles .'} | eq { hop { nth_argmax { all_rows ; location / attendance ; 1 } ; opponent } ; los angeles } = true | select the row whose location / attendance record of all rows is 1st maximum . the opponent record of this row is los angeles . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location / attendance_5': 5, '1_6': 6, 'opponent_7': 7, 'los angeles_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', 'location / attendance_5': 'location / attendance', '1_6': '1', 'opponent_7': 'opponent', 'los angeles_8': 'los angeles'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location / attendance_5': [0], '1_6': [0], 'opponent_7': [1], 'los angeles_8': [2]} | ['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record'] | [['6', 'june 7', 'houston', 'w 84 - 75', 'douglas ( 20 )', 'hoffman ( 10 )', 'douglas , hoffman ( 4 )', 'conseco fieldhouse 8214', '4 - 2'], ['7', 'june 11', 'san antonio', 'l 64 - 53', 'douglas , white ( 13 )', 'hoffman ( 9 )', 'douglas ( 4 )', 'at & t center 6262', '4 - 3'], ['8', 'june 13', 'atlanta', 'w 76 - 67', 'white ( 21 )', 'sutton - brown ( 12 )', 'douglas ( 7 )', 'philips arena 8167', '5 - 3'], ['9', 'june 15', 'san antonio', 'l 70 - 60', 'douglas ( 17 )', 'hoffman ( 10 )', 'hoffman ( 4 )', 'conseco fieldhouse 7412', '5 - 4'], ['10', 'june 18', 'new york', 'w 83 - 69', 'douglas ( 16 )', 'douglas ( 8 )', 'douglas ( 5 )', 'conseco fieldhouse 6333', '6 - 4'], ['11', 'june 20', 'seattle', 'l 78 - 70', 'sutton - brown ( 14 )', 'hoffman ( 10 )', 'catchings , white ( 4 )', 'keyarena 7393', '6 - 5'], ['12', 'june 22', 'los angeles', 'l 77 - 63', 'catchings ( 17 )', 'hoffman ( 10 )', 'catchings ( 3 )', 'staples center 9463', '6 - 6'], ['13', 'june 24', 'sacramento', 'w 78 - 73', 'hoffman ( 23 )', 'hoffman ( 13 )', 'bevilaqua , feaster , ebony hoffman ( 3 )', 'conseco fieldhouse 6020', '7 - 6'], ['14', 'june 26', 'new york', 'l 102 - 96 ( 3ot )', 'hoffman ( 26 )', 'sutton - brown ( 15 )', 'bevilaqua ( 5 )', 'madison square garden 7899', '7 - 7']] |
washington redskins draft history | https://en.wikipedia.org/wiki/Washington_Redskins_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17100961-8.html.csv | comparative | dick farman was drafted higher overall by the washington redskins than paul coop . | {'row_1': '14', 'row_2': '18', 'col': '3', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'dick farman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to dick farman .', 'tostr': 'filter_eq { all_rows ; name ; dick farman }'}, 'overall'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; dick farman } ; overall }', 'tointer': 'select the rows whose name record fuzzily matches to dick farman . take the overall record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'paul coop'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to paul coop .', 'tostr': 'filter_eq { all_rows ; name ; paul coop }'}, 'overall'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; paul coop } ; overall }', 'tointer': 'select the rows whose name record fuzzily matches to paul coop . take the overall record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; dick farman } ; overall } ; hop { filter_eq { all_rows ; name ; paul coop } ; overall } } = true', 'tointer': 'select the rows whose name record fuzzily matches to dick farman . take the overall record of this row . select the rows whose name record fuzzily matches to paul coop . take the overall record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; name ; dick farman } ; overall } ; hop { filter_eq { all_rows ; name ; paul coop } ; overall } } = true | select the rows whose name record fuzzily matches to dick farman . take the overall record of this row . select the rows whose name record fuzzily matches to paul coop . take the overall record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'dick farman_8': 8, 'overall_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'paul coop_12': 12, 'overall_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'dick farman_8': 'dick farman', 'overall_9': 'overall', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'paul coop_12': 'paul coop', 'overall_13': 'overall'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'dick farman_8': [0], 'overall_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'paul coop_12': [1], 'overall_13': [3]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '8', '8', 'i b hale', 'ot', 'texas christian'], ['3', '8', '23', 'charley holm', 'rb', 'alabama'], ['5', '8', '38', 'dick todd', 'rb', 'texas a & m'], ['6', '8', '48', 'dave anderson', 'rb', 'california'], ['7', '8', '58', 'quinton lumpkin', 'c', 'georgia'], ['8', '8', '68', 'bo russell', 'ot', 'auburn'], ['9', '8', '78', 'wilbur moore', 'hb', 'minnesota'], ['10', '8', '88', 'jim johnston', 'rb', 'washington'], ['11', '8', '98', 'jim german', 'rb', 'centre'], ['12', '8', '108', "bob o'mara", 'rb', 'duke'], ['13', '8', '118', 'steve slivinski', 'g', 'washington'], ['14', '8', '128', 'bob hoffman', 'rb', 'southern california'], ['15', '8', '138', 'eric tipton', 'rb', 'duke'], ['16', '8', '148', 'dick farman', 'ot', 'washington state'], ['17', '8', '158', 'clyde shugart', 'ot', 'iowa state'], ['18', '8', '168', 'boyd morgan', 'rb', 'southern california'], ['19', '8', '178', 'phil smith', 'ot', "st benedict 's"], ['20', '8', '188', 'paul coop', 'ot', 'centre'], ['21', '3', '193', 'matt kuber', 'g', 'villanova'], ['22', '3', '198', 'al cruver', 'rb', 'washington state']] |
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/2-18569105-10.html.csv | aggregation | 2008 summer olympics - men 's 400 metres contestants ran an average time of 45.16 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '45.16', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'time'], 'result': '45.16', 'ind': 0, 'tostr': 'avg { all_rows ; time }'}, '45.16'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; time } ; 45.16 } = true', 'tointer': 'the average of the time record of all rows is 45.16 .'} | round_eq { avg { all_rows ; time } ; 45.16 } = true | the average of the time record of all rows is 45.16 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'time_4': 4, '45.16_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'time_4': 'time', '45.16_5': '45.16'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'time_4': [0], '45.16_5': [1]} | ['rank', 'lane', 'athlete', 'nationality', 'time', 'react'] | [['1', '6', 'leslie djhone', 'france', '44.79', '0.159'], ['2', '4', 'david neville', 'united states', '44.91', '0.190'], ['3', '5', 'joel milburn', 'australia', '45.06', '0.187'], ['4', '9', 'ricardo chambers', 'jamaica', '45.09', '0.220'], ['5', '3', 'jonathan borlãe', 'belgium', '45.11', '0.191'], ['6', '8', 'james godday', 'nigeria', '45.24', '0.185'], ['7', '2', 'andretti bain', 'bahamas', '45.52', '0.196'], ['8', '7', 'andrew steele', 'great britain', '45.59', '0.216']] |
mll expansion draft | https://en.wikipedia.org/wiki/MLL_Expansion_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12173193-1.html.csv | unique | the only player from the united states to be picked in the mll expansion draft to play as goalie is sal locascio . | {'scope': 'subset', 'row': '1', 'col': '4', 'col_other': '3,5', 'criterion': 'equal', 'value': 'goalie', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; nationality ; united states }', 'tointer': 'select the rows whose nationality record fuzzily matches to united states .'}, 'position', 'goalie'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nationality record fuzzily matches to united states . among these rows , select the rows whose position record fuzzily matches to goalie .', 'tostr': 'filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; goalie }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; goalie } }', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . among these rows , select the rows whose position record fuzzily matches to goalie . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; nationality ; united states }', 'tointer': 'select the rows whose nationality record fuzzily matches to united states .'}, 'position', 'goalie'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nationality record fuzzily matches to united states . among these rows , select the rows whose position record fuzzily matches to goalie .', 'tostr': 'filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; goalie }'}, 'player'], 'result': 'sal locascio', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; goalie } ; player }'}, 'sal locascio'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; goalie } ; player } ; sal locascio }', 'tointer': 'the player record of this unqiue row is sal locascio .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; goalie } } ; eq { hop { filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; goalie } ; player } ; sal locascio } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . among these rows , select the rows whose position record fuzzily matches to goalie . there is only one such row in the table . the player record of this unqiue row is sal locascio .'} | and { only { filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; goalie } } ; eq { hop { filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; goalie } ; player } ; sal locascio } } = true | select the rows whose nationality record fuzzily matches to united states . among these rows , select the rows whose position record fuzzily matches to goalie . there is only one such row in the table . the player record of this unqiue row is sal locascio . | 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, 'nationality_8': 8, 'united states_9': 9, 'position_10': 10, 'goalie_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'player_12': 12, 'sal locascio_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', 'nationality_8': 'nationality', 'united states_9': 'united states', 'position_10': 'position', 'goalie_11': 'goalie', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'player_12': 'player', 'sal locascio_13': 'sal locascio'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'nationality_8': [0], 'united states_9': [0], 'position_10': [1], 'goalie_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'player_12': [3], 'sal locascio_13': [4]} | ['round', 'pick', 'player', 'position', 'nationality', 'team'] | [['1', '1', 'sal locascio', 'goalie', 'united states', 'bridgeport barrage'], ['1', '2', 'tucker radebaugh', 'attack / midfield', 'united states', 'boston cannons'], ['1', '3', 'gary gait', 'attack / midfield', 'canada', 'long island lizards'], ['1', '4', 'tom marechek', 'forward', 'canada', 'baltimore bayhawks'], ['1', '5', 'dave curry', 'midfield', 'united states', 'new jersey pride'], ['1', '6', 'jake bergey', 'forward', 'united states', 'rochester rattlers']] |
2003 - 04 fa cup | https://en.wikipedia.org/wiki/2003%E2%80%9304_FA_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15828727-6.html.csv | aggregation | the games in the 2003 - 04 fa cup drew an average crowd attendance of 26593 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '26593', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '26593', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '26593'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 26593 } = true', 'tointer': 'the average of the attendance record of all rows is 26593 .'} | round_eq { avg { all_rows ; attendance } ; 26593 } = true | the average of the attendance record of all rows is 26593 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '26593_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '26593_5': '26593'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '26593_5': [1]} | ['tie no', 'home team', 'score', 'away team', 'attendance'] | [['1', 'liverpool', '1 - 1', 'portsmouth', '34669'], ['replay', 'portsmouth', '1 - 0', 'liverpool', '19529'], ['2', 'sunderland', '1 - 1', 'birmingham city', '24966'], ['replay', 'birmingham city', '0 - 2', 'sunderland', '25645'], ['3', 'sheffield united', '1 - 0', 'colchester united', '17074'], ['4', 'tranmere rovers', '2 - 1', 'swansea city', '12215'], ['5', 'fulham', '0 - 0', 'west ham united', '14705'], ['replay', 'west ham united', '0 - 3', 'fulham', '27934'], ['6', 'manchester united', '4 - 2', 'manchester city', '67228'], ['7', 'millwall', '1 - 0', 'burnley', '10420'], ['8', 'arsenal', '2 - 1', 'chelsea', '38136']] |
united states house of representatives elections , 1816 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1816 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668347-14.html.csv | comparative | john w taylor has a first elected year which is earlier than that of john b yates . | {'row_1': '5', 'row_2': '6', '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', 'john w taylor'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to john w taylor .', 'tostr': 'filter_eq { all_rows ; incumbent ; john w taylor }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; john w taylor } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to john w taylor . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'john b yates'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to john b yates .', 'tostr': 'filter_eq { all_rows ; incumbent ; john b yates }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; john b yates } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to john b yates . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; john w taylor } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; john b yates } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to john w taylor . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to john b yates . take the first elected record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; incumbent ; john w taylor } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; john b yates } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to john w taylor . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to john b yates . 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, 'john w taylor_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'john b yates_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', 'john w taylor_8': 'john w taylor', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'john b yates_12': 'john b yates', 'first elected_13': 'first elected'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'john w taylor_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'john b yates_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['new york 3', 'jonathan ward', 'democratic - republican', '1814', 'retired democratic - republican hold', 'caleb tompkins ( dr ) 56.8 % abraham odell ( f ) 42.8 %'], ['new york 6', 'james w wilkin', 'democratic - republican', '1815 ( special )', 're - elected', 'james w wilkin ( dr ) 55.4 % james burt ( f ) 44.6 %'], ['new york 7', 'samuel r betts', 'democratic - republican', '1814', 'retired democratic - republican hold', 'josiah hasbrouck ( dr ) 51.7 % john sudam ( f ) 48.2 %'], ['new york 10', 'hosea moffitt', 'federalist', '1812', 'retired federalist hold', 'john p cushman ( f ) 54.9 % thomas turner ( dr ) 44.9 %'], ['new york 11', 'john w taylor', 'democratic - republican', '1812', 're - elected', 'john w taylor ( dr ) 53.4 % elisha powell ( f ) 46.6 %'], ['new york 13', 'john b yates', 'democratic - republican', '1814', 'retired democratic - republican hold', 'thomas lawyer ( dr ) 54.9 % william beekman ( f ) 45.1 %'], ['new york 17', 'westel willoughby , jr', 'federalist', '1814', 'retired democratic - republican gain', 'thomas h hubbard ( dr ) 51.5 % simeon ford ( f ) 48.4 %'], ['new york 18', 'moss kent', 'federalist', '1812', 'retired federalist hold', 'david a ogden ( f ) 50.4 % ela collins ( dr ) 49.5 %']] |
list of tvb series ( 1998 ) | https://en.wikipedia.org/wiki/List_of_TVB_series_%281998%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18493407-1.html.csv | unique | the 1998 tvb series " old time buddy - to catch a thief " was the only series in the period drama genre . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'period drama', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'genre', 'period drama'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose genre record fuzzily matches to period drama .', 'tostr': 'filter_eq { all_rows ; genre ; period drama }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; genre ; period drama } }', 'tointer': 'select the rows whose genre record fuzzily matches to period drama . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'genre', 'period drama'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose genre record fuzzily matches to period drama .', 'tostr': 'filter_eq { all_rows ; genre ; period drama }'}, 'english title ( chinese title )'], 'result': 'old time buddy - to catch a thief 難兄難弟之神探李奇', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; genre ; period drama } ; english title ( chinese title ) }'}, 'old time buddy - to catch a thief 難兄難弟之神探李奇'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; genre ; period drama } ; english title ( chinese title ) } ; old time buddy - to catch a thief 難兄難弟之神探李奇 }', 'tointer': 'the english title ( chinese title ) record of this unqiue row is old time buddy - to catch a thief 難兄難弟之神探李奇 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; genre ; period drama } } ; eq { hop { filter_eq { all_rows ; genre ; period drama } ; english title ( chinese title ) } ; old time buddy - to catch a thief 難兄難弟之神探李奇 } } = true', 'tointer': 'select the rows whose genre record fuzzily matches to period drama . there is only one such row in the table . the english title ( chinese title ) record of this unqiue row is old time buddy - to catch a thief 難兄難弟之神探李奇 .'} | and { only { filter_eq { all_rows ; genre ; period drama } } ; eq { hop { filter_eq { all_rows ; genre ; period drama } ; english title ( chinese title ) } ; old time buddy - to catch a thief 難兄難弟之神探李奇 } } = true | select the rows whose genre record fuzzily matches to period drama . there is only one such row in the table . the english title ( chinese title ) record of this unqiue row is old time buddy - to catch a thief 難兄難弟之神探李奇 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'genre_7': 7, 'period drama_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'english title (chinese title)_9': 9, 'old time buddy - to catch a thief 難兄難弟之神探李奇_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'genre_7': 'genre', 'period drama_8': 'period drama', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'english title (chinese title)_9': 'english title ( chinese title )', 'old time buddy - to catch a thief 難兄難弟之神探李奇_10': 'old time buddy - to catch a thief 難兄難弟之神探李奇'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'genre_7': [0], 'period drama_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'english title (chinese title)_9': [2], 'old time buddy - to catch a thief 難兄難弟之神探李奇_10': [3]} | ['airing date', 'english title ( chinese title )', 'number of episodes', 'genre', 'official website'] | [['12 jan - 6 feb', 'a tough side of a lady 花木蘭', '20', 'costume action', 'official website'], ['9 feb - 6 mar', "a place of one 's own 大澳的天空", '20', 'modern drama', 'official website'], ['9 mar - 1 may', 'dark tales ii 聊齋 ( 貳 )', '50', 'costume drama', 'official website'], ['4 may - 29 may', 'as sure as fate 師奶強人', '20', 'modern drama', 'official website'], ['1 jun - 31 jul', 'the duke of mount deer 鹿鼎記', '45', 'costume drama', 'official website'], ['3 aug - 4 sep', 'old time buddy - to catch a thief 難兄難弟之神探李奇', '25', 'period drama', 'official website'], ['7 sep - 25 sep', 'simply ordinary 林世榮', '15', 'costume drama', 'official website'], ['28 sep - 23 oct', 'web of love 網上有情人', '20', 'modern drama', 'official website'], ['26 oct - 18 dec', 'journey to the west ii 西遊記 ( 貳 )', '42', 'costume drama', 'official website'], ['21 dec 1998 - 15 jan 1999', 'moments of endearment 外父唔怕做', '20', 'modern drama', 'official website']] |
fiat albea | https://en.wikipedia.org/wiki/Fiat_Albea | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1415652-1.html.csv | superlative | of the 16 valve engines , the 1.6 16v dohc has the largest displacement , 1596cc . | {'scope': 'subset', 'col_superlative': '3', 'row_superlative': '4', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': {'col': '1', 'criterion': 'equal', 'value': '16v'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', '16v'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; engine ; 16v }', 'tointer': 'select the rows whose engine record fuzzily matches to 16v .'}, 'displacement'], 'result': '1596 cc', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; engine ; 16v } ; displacement }', 'tointer': 'select the rows whose engine record fuzzily matches to 16v . the maximum displacement record of these rows is 1596 cc .'}, '1596 cc'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; engine ; 16v } ; displacement } ; 1596 cc } = true', 'tointer': 'select the rows whose engine record fuzzily matches to 16v . the maximum displacement record of these rows is 1596 cc .'} | eq { max { filter_eq { all_rows ; engine ; 16v } ; displacement } ; 1596 cc } = true | select the rows whose engine record fuzzily matches to 16v . the maximum displacement record of these rows is 1596 cc . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'engine_5': 5, '16v_6': 6, 'displacement_7': 7, '1596 cc_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'engine_5': 'engine', '16v_6': '16v', 'displacement_7': 'displacement', '1596 cc_8': '1596 cc'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'engine_5': [0], '16v_6': [0], 'displacement_7': [1], '1596 cc_8': [2]} | ['engine', 'type', 'displacement', 'power', 'torque'] | [['1.2 8v sohc', 'i4', '1242 cc', 'at5000 rpm', 'at2500 rpm'], ['1.2 16v dohc', 'i4', '1242 cc', 'at5000 rpm', 'at4000 rpm'], ['1.4 8v sohc', 'i4', '1368 cc', 'at6000 rpm', 'at3000 rpm'], ['1.6 16v dohc', 'i4', '1596 cc', 'at5750 rpm', 'at4000 rpm'], ['1.3 16v multijet', 'i4', '1248 cc', 'at4000 rpm', 'at1500 rpm']] |
list of boston celtics broadcasters | https://en.wikipedia.org/wiki/List_of_Boston_Celtics_broadcasters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14902507-9.html.csv | majority | the flagship station listed for most of the broadcasters of boston celtics is weei . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'weei', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'flagship station', 'weei'], 'result': True, 'ind': 0, 'tointer': 'for the flagship station records of all rows , most of them fuzzily match to weei .', 'tostr': 'most_eq { all_rows ; flagship station ; weei } = true'} | most_eq { all_rows ; flagship station ; weei } = true | for the flagship station records of all rows , most of them fuzzily match to weei . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'flagship station_3': 3, 'weei_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'flagship station_3': 'flagship station', 'weei_4': 'weei'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'flagship station_3': [0], 'weei_4': [0]} | ['year', 'flagship station', 'play - by - play', 'color commentator ( s )', 'studio host'] | [['1999 - 2000', 'weei', 'howard david', 'cedric maxwell', 'ted sarandis'], ['1998 - 99', 'weei', 'howard david', 'cedric maxwell', 'ted sarandis'], ['1997 - 98', 'weei', 'howard david', 'cedric maxwell', 'ted sarandis'], ['1996 - 97', 'weei', 'spencer ross', 'cedric maxwell', 'ted sarandis'], ['1995 - 96', 'wrko', 'spencer ross', 'cedric maxwell', 'ted sarandis'], ['1994 - 95', 'weei', 'glenn ordway', 'jerry sichting', 'craig mustard'], ['1993 - 94', 'weei', 'glenn ordway', 'jerry sichting', 'craig mustard'], ['1992 - 93', 'weei', 'glenn ordway', 'jerry sichting', 'craig mustard'], ['1991 - 92', 'weei', 'glenn ordway', 'jerry sichting', 'craig mustard'], ['1990 - 91', 'weei', 'glenn ordway', 'doug brown', 'craig mustard']] |
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 | majority | all of the football clubs in the 1955 - 56 segunda división played a total of 30 matches . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '30', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '30'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 30 .', 'tostr': 'all_eq { all_rows ; played ; 30 } = true'} | all_eq { all_rows ; played ; 30 } = true | for the played records of all rows , all of them are equal to 30 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '30_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '30_4': '30'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '30_4': [0]} | ['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', '13', '7', '10', '50', '44', '+ 6'], ['6', 'club ferrol', '30', '32', '11', '10', '9', '44', '47', '- 3'], ['7', 'real gijón cf', '30', '32', '14', '4', '12', '51', '46', '+ 5'], ['8', 'sd indauchu', '30', '30', '12', '6', '12', '53', '50', '+ 3'], ['9', 'cd tarrasa', '30', '28', '10', '8', '12', '46', '59', '- 13'], ['10', 'baracaldo ah', '30', '28', '10', '8', '12', '45', '54', '- 9'], ['11', 'real santander', '30', '28', '12', '4', '14', '47', '47', '0'], ['12', 'ud lérida', '30', '26', '11', '4', '15', '53', '63', '- 10'], ['13', 'cp la felguera', '30', '26', '10', '6', '14', '35', '57', '- 22'], ['14', 'sd eibar', '30', '25', '9', '7', '14', '40', '55', '- 15'], ['15', 'club sestao', '30', '19', '6', '7', '17', '24', '58', '- 34'], ['16', 'cd logroñés', '30', '16', '4', '8', '18', '38', '76', '- 38']] |
1991 buffalo bills season | https://en.wikipedia.org/wiki/1991_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15353123-1.html.csv | comparative | for the 1991 buffalo bills season , brad lamb was picked one round before mark maddox . | {'row_1': '7', 'row_2': '8', 'col': '1', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'brad lamb'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to brad lamb .', 'tostr': 'filter_eq { all_rows ; player ; brad lamb }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; brad lamb } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to brad lamb . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'mark maddox'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to mark maddox .', 'tostr': 'filter_eq { all_rows ; player ; mark maddox }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; mark maddox } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to mark maddox . take the round record of this row .'}], 'result': '-1', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; player ; brad lamb } ; round } ; hop { filter_eq { all_rows ; player ; mark maddox } ; round } }'}, '-1'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; player ; brad lamb } ; round } ; hop { filter_eq { all_rows ; player ; mark maddox } ; round } } ; -1 } = true', 'tointer': 'select the rows whose player record fuzzily matches to brad lamb . take the round record of this row . select the rows whose player record fuzzily matches to mark maddox . take the round record of this row . the second record is 1 larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; player ; brad lamb } ; round } ; hop { filter_eq { all_rows ; player ; mark maddox } ; round } } ; -1 } = true | select the rows whose player record fuzzily matches to brad lamb . take the round record of this row . select the rows whose player record fuzzily matches to mark maddox . take the round record of this row . the second record is 1 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'player_8': 8, 'brad lamb_9': 9, 'round_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'mark maddox_13': 13, 'round_14': 14, '-1_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'player_8': 'player', 'brad lamb_9': 'brad lamb', 'round_10': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player', 'mark maddox_13': 'mark maddox', 'round_14': 'round', '-1_15': '-1'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'brad lamb_9': [0], 'round_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'mark maddox_13': [1], 'round_14': [3], '-1_15': [5]} | ['round', 'pick', 'player', 'position', 'college'] | [['1', '26', 'henry jones', 'defensive back', 'illinois'], ['2', '54', 'phil hansen', 'defensive end', 'north dakota state'], ['3', '82', 'darryl wren', 'defensive back', 'pittsburg state'], ['4', '138', 'shawn wilbourn', 'defensive back', 'long beach state'], ['5', '166', 'millard hamilton', 'wide receiver', 'clark university'], ['6', '194', 'amir rasul', 'running back', 'florida a & m'], ['8', '222', 'brad lamb', 'wide receiver', 'anderson'], ['9', '249', 'mark maddox', 'linebacker', 'northern michigan'], ['10', '277', 'tony delorenzo', 'guard', 'new mexico state'], ['11', '305', 'dean kirkland', 'guard', 'washington'], ['12', '333', 'stephen clark', 'tight end', 'texas']] |
pilibhit ( lok sabha constituency ) | https://en.wikipedia.org/wiki/Pilibhit_%28Lok_Sabha_constituency%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18106841-1.html.csv | count | for pilibhit , when the trailing party is indian national congress , there were 3 times that the party that won was praja socialist party . | {'scope': 'subset', 'criterion': 'equal', 'value': 'praja socialist party', 'result': '3', 'col': '4', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'indian national congress'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'trailing party', 'indian national congress'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; trailing party ; indian national congress }', 'tointer': 'select the rows whose trailing party record fuzzily matches to indian national congress .'}, 'party won', 'praja socialist party'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose trailing party record fuzzily matches to indian national congress . among these rows , select the rows whose party won record fuzzily matches to praja socialist party .', 'tostr': 'filter_eq { filter_eq { all_rows ; trailing party ; indian national congress } ; party won ; praja socialist party }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; trailing party ; indian national congress } ; party won ; praja socialist party } }', 'tointer': 'select the rows whose trailing party record fuzzily matches to indian national congress . among these rows , select the rows whose party won record fuzzily matches to praja socialist party . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; trailing party ; indian national congress } ; party won ; praja socialist party } } ; 3 } = true', 'tointer': 'select the rows whose trailing party record fuzzily matches to indian national congress . among these rows , select the rows whose party won record fuzzily matches to praja socialist party . the number of such rows is 3 .'} | eq { count { filter_eq { filter_eq { all_rows ; trailing party ; indian national congress } ; party won ; praja socialist party } } ; 3 } = true | select the rows whose trailing party record fuzzily matches to indian national congress . among these rows , select the rows whose party won record fuzzily matches to praja socialist party . 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, 'trailing party_6': 6, 'indian national congress_7': 7, 'party won_8': 8, 'praja socialist party_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', 'trailing party_6': 'trailing party', 'indian national congress_7': 'indian national congress', 'party won_8': 'party won', 'praja socialist party_9': 'praja socialist party', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'trailing party_6': [0], 'indian national congress_7': [0], 'party won_8': [1], 'praja socialist party_9': [1], '3_10': [3]} | ['year', 'lok sabha', 'members of parliament', 'party won', "winner 's % votes", 'trailing party', 'trailing party % votes'] | [['1951', '1st lok sabha', 'mukund lal agrawal', 'indian national congress', '43.11 %', 'socialist party', '22.58 %'], ['1957', '2nd lok sabha', 'mohan swarup', 'praja socialist party', '50.54 %', 'indian national congress', '34.86 %'], ['1962', '3rd lok sabha', 'mohan swarup', 'praja socialist party', '29.62 %', 'indian national congress', '27.42 %'], ['1967', '4th lok sabha', 'mohan swarup', 'praja socialist party', '28.24 %', 'indian national congress', '24.26 %'], ['1971', '5th lok sabha', 'mohan swarup', 'indian national congress', '38.96 %', 'indian national organization', '24.74 %'], ['1977', '6th lok sabha', 'md shamsul hasan khan', 'bharatiya lok dal', '71.32 %', 'indian national congress', '19.73 %'], ['1980', '7th lok sabha', 'harish kumar gangawar', 'indian national congress', '40.42 %', 'janata party', '25.34 %'], ['1984', '8th lok sabha', 'bhanu pratap singh', 'indian national congress', '63.84 %', 'bharatiya lok dal', '23.39 %'], ['1989', '9th lok sabha', 'maneka gandhi', 'janata dal', '57.34 %', 'indian national congress', '29.37 %'], ['1991', '10th lok sabha', 'parshuram gangwar', 'bharatiya janta party', '30.86 %', 'janata dal', '29.40 %'], ['1996', '11th lok sabha', 'maneka gandhi', 'janata dal', '59.83 %', 'bharatiya janta party', '17.01 %'], ['1998', '12th lok sabha', 'maneka gandhi', 'independent', '55.99 %', 'bahujan samaj party', '22.60 %'], ['1999', '13th lok sabha', 'maneka gandhi', 'independent', '57.94 %', 'bahujan samaj party', '25.88 %'], ['2004', '14th lok sabha', 'maneka gandhi', 'bharatiya janta party', '37.75 %', 'samajwadi party', '22.58 %'], ['2009', '15th lok sabha', 'feroze varun gandhi', 'bharatiya janta party', '49.79 %', 'indian national congress', '16.38 %']] |
2008 - 09 lega pro prima divisione | https://en.wikipedia.org/wiki/2008%E2%80%9309_Lega_Pro_Prima_Divisione | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17605092-1.html.csv | superlative | the highest stadium capacity in the lega pro prima divisione in the season 2008-09 was in the stadio marcantonio bentegodi . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '18', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'capacity'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; capacity }'}, 'stadium'], 'result': 'stadio marcantonio bentegodi', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; capacity } ; stadium }'}, 'stadio marcantonio bentegodi'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; capacity } ; stadium } ; stadio marcantonio bentegodi } = true', 'tointer': 'select the row whose capacity record of all rows is maximum . the stadium record of this row is stadio marcantonio bentegodi .'} | eq { hop { argmax { all_rows ; capacity } ; stadium } ; stadio marcantonio bentegodi } = true | select the row whose capacity record of all rows is maximum . the stadium record of this row is stadio marcantonio bentegodi . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'capacity_5': 5, 'stadium_6': 6, 'stadio marcantonio bentegodi_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', 'stadium_6': 'stadium', 'stadio marcantonio bentegodi_7': 'stadio marcantonio bentegodi'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'capacity_5': [0], 'stadium_6': [1], 'stadio marcantonio bentegodi_7': [2]} | ['club', 'city', 'stadium', 'capacity', '200708 season'] | [['ac cesena', 'cesena', 'stadio dino manuzzi', '23860', '22nd in serie b'], ['us cremonese', 'cremona', 'stadio giovanni zini', '22000', '2nd in serie c1 / a'], ['calcio lecco 1912', 'lecco', 'stadio rigamonti - ceppi', '4977', '16th in serie c1 / a'], ['ac legnano', 'legnano', 'stadio giovanni mari', '6600', '7th in serie c1 / a'], ['ac lumezzane', 'lumezzane', 'nuovo stadio comunale', '4150', 'serie c2 / a play - off winners'], ['ac monza brianza 1912', 'monza', 'stadio brianteo', '18568', '8th in serie c1 / a'], ['novara calcio', 'novara', 'stadio silvio piola', '8810', '9th in serie c1 / a'], ['calcio padova', 'padua', 'stadio euganeo', '32336', '6th in serie c1 / a'], ['us pergocrema 1932', 'crema', 'stadio giuseppe voltini', '3490', 'serie c2 / a champions'], ['calcio portogruaro summaga', 'portogruaro', 'stadio pier giovanni mecchia', '3335', 'serie c2 / b play - off winners'], ['pro patria', 'busto arsizio', 'stadio carlo speroni', '3990', '14th in serie c1 / a'], ['ac pro sesto', 'sesto san giovanni', 'stadio breda', '4500', '11th in serie c1 / a'], ['ravenna calcio', 'ravenna', 'stadio bruno benelli', '12020', '20th in serie b'], ['ac reggiana 1919', 'reggio emilia', 'stadio giglio', '29546', 'serie c2 / b champions'], ['ss sambenedettese calcio', 'san benedetto del tronto', 'stadio riviera delle palme', '22000', '12th in serie c1 / b'], ['spal 1907', 'ferrara', 'stadio paolo mazza', '19000', '4th in serie c2 / b'], ['ssc venezia', 'venice', 'stadio pierluigi penzo', '10500', '12th in serie c1 / a'], ['hellas verona fc', 'verona', 'stadio marcantonio bentegodi', '39211', '17th in serie c1 / a']] |
soccer - specific stadium | https://en.wikipedia.org/wiki/Soccer-specific_stadium | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1034291-6.html.csv | unique | the indiana invaders soccer complex is the only stadium that was opened in 2004 . | {'scope': 'all', 'row': '6', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': '2004', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'opened', '2004'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opened record is equal to 2004 .', 'tostr': 'filter_eq { all_rows ; opened ; 2004 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; opened ; 2004 } }', 'tointer': 'select the rows whose opened record is equal to 2004 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'opened', '2004'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opened record is equal to 2004 .', 'tostr': 'filter_eq { all_rows ; opened ; 2004 }'}, 'stadium'], 'result': 'indiana invaders soccer complex', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opened ; 2004 } ; stadium }'}, 'indiana invaders soccer complex'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; opened ; 2004 } ; stadium } ; indiana invaders soccer complex }', 'tointer': 'the stadium record of this unqiue row is indiana invaders soccer complex .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; opened ; 2004 } } ; eq { hop { filter_eq { all_rows ; opened ; 2004 } ; stadium } ; indiana invaders soccer complex } } = true', 'tointer': 'select the rows whose opened record is equal to 2004 . there is only one such row in the table . the stadium record of this unqiue row is indiana invaders soccer complex .'} | and { only { filter_eq { all_rows ; opened ; 2004 } } ; eq { hop { filter_eq { all_rows ; opened ; 2004 } ; stadium } ; indiana invaders soccer complex } } = true | select the rows whose opened record is equal to 2004 . there is only one such row in the table . the stadium record of this unqiue row is indiana invaders soccer complex . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'opened_7': 7, '2004_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'stadium_9': 9, 'indiana invaders soccer complex_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'opened_7': 'opened', '2004_8': '2004', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'stadium_9': 'stadium', 'indiana invaders soccer complex_10': 'indiana invaders soccer complex'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'opened_7': [0], '2004_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'stadium_9': [2], 'indiana invaders soccer complex_10': [3]} | ['stadium', 'club ( s )', 'division', 'city', 'capacity', 'opened'] | [['blackbaud stadium', 'charleston battery', 'usl pro', 'charleston , sc', '5113', '1999'], ['city park stadium', 'westchester flames', 'pdl', 'new rochelle , ny', '1845', '1970s'], ['seminole soccer complex ( sanford )', 'central florida kraze', 'pdl', 'lake mary , fl', '3666', '1995'], ['ezell park', 'nashville metros', 'pdl', 'nashville , tn', '1317', '1950s'], ['highmark stadium', 'pittsburgh riverhounds', 'usl pro', 'pittsburgh , pa', '3500', '2013'], ['indiana invaders soccer complex', 'indiana invaders', 'pdl', 'south bend , in', '4985', '2004'], ['legion stadium', 'wilmington hammerheads', 'usl pro', 'wilmington , nc', '5300', '1930s'], ['lusitano stadium', 'western mass pioneers', 'pdl', 'ludlow , ma', '3000', '1918'], ['macpherson stadium', 'carolina dynamo', 'pdl', 'browns summit , nc', '1600', '2002'], ['patriot stadium', 'chivas el paso patriots', 'pdl', 'el paso , tx', '3000', '2005'], ["sahlen 's stadium", 'rochester rhinos western new york flash', 'usl pro nwsl', 'rochester , ny', '13500', '2006'], ['virginia beach sportsplex', 'hampton roads piranhas', 'pdl', 'virginia beach , va', '10000', '1999']] |
black swan - class sloop | https://en.wikipedia.org/wiki/Black_Swan-class_sloop | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1220125-3.html.csv | ordinal | cygnet was the earliest commissioned sloop in the black swan - class sloop . | {'row': '3', 'col': '6', 'order': '1', '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', 'commissioned', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; commissioned ; 1 }'}, 'name'], 'result': 'cygnet', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; commissioned ; 1 } ; name }'}, 'cygnet'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; commissioned ; 1 } ; name } ; cygnet } = true', 'tointer': 'select the row whose commissioned record of all rows is 1st minimum . the name record of this row is cygnet .'} | eq { hop { nth_argmin { all_rows ; commissioned ; 1 } ; name } ; cygnet } = true | select the row whose commissioned record of all rows is 1st minimum . the name record of this row is cygnet . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'commissioned_5': 5, '1_6': 6, 'name_7': 7, 'cygnet_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', 'commissioned_5': 'commissioned', '1_6': '1', 'name_7': 'name', 'cygnet_8': 'cygnet'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'commissioned_5': [0], '1_6': [0], 'name_7': [1], 'cygnet_8': [2]} | ['name', 'pennant', 'builder', 'laid down', 'launched', 'commissioned'] | [['chanticleer', 'u05', 'denny , dunbarton', '6 june 1941', '24 september 1942', '29 march 1943'], ['crane', 'u23', 'denny , dunbarton', '13 june 1941', '9 november 1942', '10 may 1943'], ['cygnet', 'u38', 'cammell laird , birkenhead', '30 august 1941', '28 july 1942', '1 december 1942'], ['kite', 'u87', 'cammell laird , birkenhead', '25 september 1941', '13 october 1942', '1 march 1943'], ['lapwing', 'u62', 'scotts , greenock', '17 december 1941', '16 july 1943', '21 march 1944'], ['lark', 'u11', 'scotts , greenock', '5 may 1942', '28 august 1943', '10 april 1944'], ['magpie', 'u82', 'thornycroft , woolston', '30 december 1941', '24 march 1943', '30 august 1943'], ['peacock', 'u96', 'thornycroft , woolston', '29 november 1942', '11 december 1943', '10 may 1944'], ['pheasant', 'u49', 'yarrow , scotstoun', '17 march 1942', '21 december 1942', '12 may 1943'], ['redpole', 'u69', 'yarrow , scotstoun', '18 may 1942', '25 february 1943', '24 june 1943'], ['snipe', 'u20', 'denny , dunbarton', '21 september 1944', '20 december 1945', '9 september 1946'], ['sparrow', 'u71', 'denny , dunbarton', '30 october 1944', '18 february 1946', '16 december 1946'], ['starling', 'u66', 'fairfield , govan', '21 october 1941', '14 october 1942', '1 april 1943'], ['woodcock', 'u90', 'fairfield , govan', '21 october 1941', '26 november 1942', '29 may 1943']] |
list of little house on the prairie episodes | https://en.wikipedia.org/wiki/List_of_Little_House_on_the_Prairie_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1854728-2.html.csv | comparative | the episode entitled family quarrel originally aired after the episode entitled the award . | {'row_1': '15', 'row_2': '12', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'family quarrel'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to family quarrel .', 'tostr': 'filter_eq { all_rows ; title ; family quarrel }'}, 'air date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title ; family quarrel } ; air date }', 'tointer': 'select the rows whose title record fuzzily matches to family quarrel . take the air date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'the award'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title record fuzzily matches to the award .', 'tostr': 'filter_eq { all_rows ; title ; the award }'}, 'air date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title ; the award } ; air date }', 'tointer': 'select the rows whose title record fuzzily matches to the award . take the air date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; title ; family quarrel } ; air date } ; hop { filter_eq { all_rows ; title ; the award } ; air date } } = true', 'tointer': 'select the rows whose title record fuzzily matches to family quarrel . take the air date record of this row . select the rows whose title record fuzzily matches to the award . take the air date record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; title ; family quarrel } ; air date } ; hop { filter_eq { all_rows ; title ; the award } ; air date } } = true | select the rows whose title record fuzzily matches to family quarrel . take the air date record of this row . select the rows whose title record fuzzily matches to the award . take the air date record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'title_7': 7, 'family quarrel_8': 8, 'air date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'the award_12': 12, 'air date_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'title_7': 'title', 'family quarrel_8': 'family quarrel', 'air date_9': 'air date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': 'title', 'the award_12': 'the award', 'air date_13': 'air date'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'family quarrel_8': [0], 'air date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'the award_12': [1], 'air date_13': [3]} | ['no in series', 'title', 'directed by', 'written by', 'air date', 'production code'] | [['1', 'a harvest of friends', 'michael landon', 'blanche hanalis , john hawkins & william putman', 'september 11 , 1974', '1002'], ['2', 'country girls', 'william f claxton', 'blanche hanalis & juanita bartlett', 'september 18 , 1974', '1001'], ['3', '100 mile walk', 'william f claxton', 'blanche hanalis & ward hawkins', 'september 25 , 1974', '1003'], ['4', "mr edwards ' homecoming", 'michael landon', 'blanche hanalis & joel murcott', 'october 2 , 1974', '1004'], ['5', 'the love of johnny johnson', 'william f claxton', 'blanche hanalis & gerry day', 'october 9 , 1974', '1005'], ['6', 'if i should wake before i die', 'victor french', 'blanche hanalis & harold swanton', 'october 23 , 1974', '1006'], ['7', 'town party , country party', 'alf kjellin', 'blanche hanalis & juanita bartlett', 'october 30 , 1974', '1007'], ['8', "ma 's holiday", 'leo penn', 'blanche hanalis & dale eunson', 'november 6 , 1974', '1010'], ['9', 'school mom', 'william f claxton', 'blanche hanalis , ward hawkins & jean rouverol', 'november 13 , 1974', '1011'], ['10', 'the raccoon', 'william f claxton', 'blanche hanalis & joseph bonaduce', 'november 20 , 1974', '1013'], ['11', 'the voice of tinker jones', 'leo penn', 'tony kayden & michael russnow', 'december 4 , 1974', '1012'], ['12', 'the award', 'william f claxton', 'michael landon', 'december 11 , 1974', '1014'], ['13 / 14', 'the lord is my shepherd', 'michael landon', 'michael landon', 'december 18 , 1974', '1008 / 1009'], ['15', 'christmas at plum creek', 'william f claxton', 'arthur heinemann', 'december 25 , 1974', '1015'], ['16', 'family quarrel', 'william f claxton', 'ward hawkins', 'january 8 , 1975', '1016'], ['20', 'child of pain', 'victor french', 'john meston', 'february 12 , 1975', '1020'], ['21', 'money crop', 'leo penn', 'teleplay by : ward hawkins story by : john meston', 'february 19 , 1975', '1021']] |
greg norman | https://en.wikipedia.org/wiki/Greg_Norman | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-157447-7.html.csv | unique | the open championship is the only tournament where greg norman had any wins . | {'scope': 'all', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'greater_than', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'wins', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is greater than 0 .', 'tostr': 'filter_greater { all_rows ; wins ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; wins ; 0 } }', 'tointer': 'select the rows whose wins record is greater than 0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'wins', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is greater than 0 .', 'tostr': 'filter_greater { all_rows ; wins ; 0 }'}, 'tournament'], 'result': 'the open championship', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; wins ; 0 } ; tournament }'}, 'the open championship'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; wins ; 0 } ; tournament } ; the open championship }', 'tointer': 'the tournament record of this unqiue row is the open championship .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; wins ; 0 } } ; eq { hop { filter_greater { all_rows ; wins ; 0 } ; tournament } ; the open championship } } = true', 'tointer': 'select the rows whose wins record is greater than 0 . there is only one such row in the table . the tournament record of this unqiue row is the open championship .'} | and { only { filter_greater { all_rows ; wins ; 0 } } ; eq { hop { filter_greater { all_rows ; wins ; 0 } ; tournament } ; the open championship } } = true | select the rows whose wins record is greater than 0 . there is only one such row in the table . the tournament record of this unqiue row is the open championship . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'wins_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'the open championship_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'wins_7': 'wins', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'the open championship_10': 'the open championship'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'wins_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'the open championship_10': [3]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '8', '9', '12', '23', '17'], ['us open', '0', '3', '5', '7', '19', '13'], ['the open championship', '2', '4', '10', '17', '27', '23'], ['pga championship', '0', '5', '6', '12', '22', '18'], ['totals', '2', '20', '30', '48', '91', '71']] |
richard attwood | https://en.wikipedia.org/wiki/Richard_Attwood | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235873-1.html.csv | count | there were only two years in which richard attwood did n't win any points at all . | {'scope': 'all', 'criterion': 'equal', 'value': '0', 'result': '2', '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': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; points ; 0 } }', 'tointer': 'select the rows whose points record is equal to 0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; points ; 0 } } ; 2 } = true', 'tointer': 'select the rows whose points record is equal to 0 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; points ; 0 } } ; 2 } = true | select the rows whose points record is equal to 0 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'points_5': 5, '0_6': 6, '2_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', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'points_5': [0], '0_6': [0], '2_7': [2]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1964', 'owen racing organisation', 'brm p67', 'brm v8', '0'], ['1965', 'reg parnell racing', 'lotus 25', 'brm v8', '2'], ['1967', 'cooper car company', 'cooper t81b', 'maserati v12', '0'], ['1968', 'owen racing organisation', 'brm p126', 'brm v12', '6'], ['1969', 'gold leaf team lotus', 'lotus 49b', 'cosworth v8', '3'], ['1969', 'frank williams racing cars', 'brabham bt30 ( f2 )', 'cosworth straight - 4', '3']] |
list of schools in the otago region | https://en.wikipedia.org/wiki/List_of_schools_in_the_Otago_Region | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12303251-3.html.csv | comparative | the arrowtown school has a higher decile value than the glenorchy school . | {'row_1': '1', 'row_2': '2', 'col': '6', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'arrowtown school'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to arrowtown school .', 'tostr': 'filter_eq { all_rows ; name ; arrowtown school }'}, 'decile'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; arrowtown school } ; decile }', 'tointer': 'select the rows whose name record fuzzily matches to arrowtown school . take the decile record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'glenorchy school'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to glenorchy school .', 'tostr': 'filter_eq { all_rows ; name ; glenorchy school }'}, 'decile'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; glenorchy school } ; decile }', 'tointer': 'select the rows whose name record fuzzily matches to glenorchy school . take the decile record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; arrowtown school } ; decile } ; hop { filter_eq { all_rows ; name ; glenorchy school } ; decile } } = true', 'tointer': 'select the rows whose name record fuzzily matches to arrowtown school . take the decile record of this row . select the rows whose name record fuzzily matches to glenorchy school . take the decile record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; name ; arrowtown school } ; decile } ; hop { filter_eq { all_rows ; name ; glenorchy school } ; decile } } = true | select the rows whose name record fuzzily matches to arrowtown school . take the decile record of this row . select the rows whose name record fuzzily matches to glenorchy school . take the decile record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'arrowtown school_8': 8, 'decile_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'glenorchy school_12': 12, 'decile_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'arrowtown school_8': 'arrowtown school', 'decile_9': 'decile', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'glenorchy school_12': 'glenorchy school', 'decile_13': 'decile'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'arrowtown school_8': [0], 'decile_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'glenorchy school_12': [1], 'decile_13': [3]} | ['name', 'years', 'gender', 'area', 'authority', 'decile', 'roll'] | [['arrowtown school', '1 - 8', 'coed', 'arrowtown', 'state', '10', '498'], ['glenorchy school', '1 - 8', 'coed', 'glenorchy', 'state', '9', '28'], ['hawea flat school', '1 - 6', 'coed', 'hawea flat', 'state', '10', '160'], ['holy family school', '1 - 8', 'coed', 'wanaka', 'state integrated', '10', '122'], ['kingsview school', '1 - 8', 'coed', 'frankton', 'state integrated', '10', '20'], ['makarora primary school', '1 - 8', 'coed', 'makarora', 'state', '7', '15'], ['mount aspiring college', '7 - 13', 'coed', 'wanaka', 'state', '10', '711'], ['queenstown school', '1 - 6', 'coed', 'queenstown', 'state', '10', '627'], ['remarkables primary school', '1 - 8', 'coed', 'frankton', 'state', '10', '495'], ["st joseph 's school", '1 - 8', 'coed', 'queenstown', 'state integrated', '10', '141'], ['wakatipu high school', '9 - 13', 'coed', 'queenstown', 'state', '10', '720'], ['wanaka primary school', '1 - 6', 'coed', 'wanaka', 'state', '10', '527']] |
b " 2005 - 06 north carolina tar heels men 's basketball team " | https://en.wikipedia.org/wiki/2005%E2%80%9306_North_Carolina_Tar_Heels_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20785990-2.html.csv | count | 3 players on the 2005 - 06 north carolina tar heels men 's basketball team are juniors . | {'scope': 'all', 'criterion': 'equal', 'value': 'junior', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', 'junior'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to junior .', 'tostr': 'filter_eq { all_rows ; year ; junior }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; year ; junior } }', 'tointer': 'select the rows whose year record fuzzily matches to junior . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; year ; junior } } ; 3 } = true', 'tointer': 'select the rows whose year record fuzzily matches to junior . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; year ; junior } } ; 3 } = true | select the rows whose year record fuzzily matches to junior . 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, 'year_5': 5, 'junior_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', 'year_5': 'year', 'junior_6': 'junior', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], 'junior_6': [0], '3_7': [2]} | ['name', '-', 'height', 'weight', 'position', 'year', 'home town', 'high school'] | [['dewey burke', '15', '6 - 0', '185', 'guard', 'junior', 'philadelphia , pa', 'conestoga'], ['mike copeland', '40', '6 - 7', '225', 'forward', 'freshman', 'winston - salem , nc', 'r j reynolds'], ['bobby frasor', '4', '6 - 3', '208', 'guard', 'freshman', 'blue island , il', 'brother rice'], ['marcus ginyard', '1', '6 - 5', '218', 'guard - forward', 'freshman', 'alexandria , va', "bishop o'connell"], ['danny green', '14', '6 - 5', '210', 'guard', 'freshman', 'north babylon , ny', "st mary 's"], ['tyler hansbrough', '50', '6 - 9', '245', 'center', 'freshman', 'poplar bluff , mo', 'poplar bluff'], ['wes miller', '22', '5 - 11', '190', 'guard', 'junior', 'charlotte , nc', 'new hampton prep ( n h )'], ['david noel', '34', '6 - 6', '232', 'forward', 'senior', 'durham , nc', 'southern durham'], ['will robinson', '30', '6 - 6', '220', 'forward', 'senior', 'chapel hill , nc', 'chapel hill'], ['byron sanders', '41', '6 - 9', '238', 'forward', 'senior', 'gulfport , ms', 'harrison central'], ['reyshawn terry', '3', '6 - 8', '232', 'forward', 'junior', 'winston - salem , nc', 'r j reynolds'], ['quentin thomas', '11', '6 - 3', '185', 'guard', 'sophomore', 'oakland , ca', 'oakland technical senior'], ['thomas wilkins', '31', '5 - 8', '175', 'guard', 'senior', 'cary , nc', 'glen hope']] |
ktlf | https://en.wikipedia.org/wiki/KTLF | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13831309-1.html.csv | majority | most of the stations are based in the state of colorado . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'colorado', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'city of license', 'colorado'], 'result': True, 'ind': 0, 'tointer': 'for the city of license records of all rows , most of them fuzzily match to colorado .', 'tostr': 'most_eq { all_rows ; city of license ; colorado } = true'} | most_eq { all_rows ; city of license ; colorado } = true | for the city of license records of all rows , most of them fuzzily match to colorado . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'city of license_3': 3, 'colorado_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'city of license_3': 'city of license', 'colorado_4': 'colorado'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'city of license_3': [0], 'colorado_4': [0]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'height m ( ft )', 'class', 'fcc info'] | [['ktlc', '89.1', 'canon city , colorado', '1150', '-', 'c3', 'fcc'], ['ktcf', '89.5', 'dolores , colorado', '500', '-', 'a', 'fcc'], ['ktdu', '88.5', 'durango , colorado', '4000', '-', 'a', 'fcc'], ['ktmh', '89.9', 'montrose , colorado', '4000', '-', 'c1', 'fcc'], ['ktps', '89.7', 'pagosa springs , colorado', '200', '-', 'a', 'fcc'], ['ktsg', '91.7', 'steamboat springs , colorado', '2500', '-', 'c3', 'fcc'], ['ktol', '90.9', 'leadville , colorado', '450', '-', 'a', 'fcc'], ['ktpf', '91.3', 'salida , colorado', '390', '-', 'c2', 'fcc'], ['ktei', '90.7', 'placerville , colorado', '250', '-', 'a', 'fcc'], ['ktdl', '90.7', 'trinidad , colorado', '450', '-', 'a', 'fcc'], ['ktad', '89.9', 'sterling , colorado', '5000', '-', 'c3', 'fcc'], ['ktml', '91.5', 'south fork , colorado', '280', '-', 'c3', 'fcc'], ['ktaw', '89.3', 'walsenburg , colorado', '500', '-', 'a', 'fcc'], ['ktdx', '89.3', 'laramie , wyoming', '450', '-', 'a', 'fcc']] |
united states house of representatives elections , 2006 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1805191-15.html.csv | count | two of the incumbents from the us house of representatives were with the democratic party . | {'scope': 'all', 'criterion': 'equal', 'value': 'democratic', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to democratic .', 'tostr': 'filter_eq { all_rows ; party ; democratic }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; party ; democratic } }', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; party ; democratic } } ; 2 } = true', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; party ; democratic } } ; 2 } = true | select the rows whose party record fuzzily matches to democratic . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'party_5': 5, 'democratic_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'party_5': 'party', 'democratic_6': 'democratic', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'democratic_6': [0], '2_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'results'] | [['indiana 1', 'pete visclosky', 'democratic', '1984', 're - elected'], ['indiana 2', 'chris chocola', 'republican', '2002', 'lost re - election democratic gain'], ['indiana 3', 'mark souder', 'republican', '1994', 're - elected'], ['indiana 4', 'steve buyer', 'republican', '1992', 're - elected'], ['indiana 5', 'dan burton', 'republican', '1982', 're - elected'], ['indiana 6', 'mike pence', 'republican', '2000', 're - elected'], ['indiana 7', 'julia carson', 'democratic', '1996', 're - elected'], ['indiana 8', 'john hostettler', 'republican', '1994', 'lost re - election democratic gain'], ['indiana 9', 'mike sodrel', 'republican', '2004', 'lost re - election democratic gain']] |
2010 - 11 dallas mavericks season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Dallas_Mavericks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27723526-17.html.csv | majority | most games of the dallas mavericks ' in the 2010 - 11 season were played in the month of june . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'june', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'date', 'june'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , most of them fuzzily match to june .', 'tostr': 'most_eq { all_rows ; date ; june } = true'} | most_eq { all_rows ; date ; june } = true | for the date records of all rows , most of them fuzzily match to june . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'june_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'june_4': 'june'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'june_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'may 31', 'miami', 'l 84 - 92 ( ot )', 'dirk nowitzki ( 27 )', 'shawn marion ( 10 )', 'jason kidd ( 6 )', 'american airlines arena 20003', '0 - 1'], ['2', 'june 2', 'miami', 'w 95 - 93 ( ot )', 'dirk nowitzki ( 24 )', 'dirk nowitzki ( 11 )', 'jason kidd , jason terry ( 5 )', 'american airlines arena 20003', '1 - 1'], ['3', 'june 5', 'miami', 'l 86 - 88 ( ot )', 'dirk nowitzki ( 34 )', 'tyson chandler , dirk nowitzki ( 11 )', 'jason kidd ( 10 )', 'american airlines center 20340', '1 - 2'], ['4', 'june 7', 'miami', 'w 86 - 83 ( ot )', 'dirk nowitzki ( 21 )', 'tyson chandler ( 16 )', 'josé juan barea ( 4 )', 'american airlines center 20430', '2 - 2'], ['5', 'june 9', 'miami', 'w 112 - 103 ( ot )', 'dirk nowitzki ( 29 )', 'tyson chandler ( 7 )', 'jason kidd , jason terry ( 6 )', 'american airlines center 20433', '3 - 2']] |
1930 - 31 chicago black hawks season | https://en.wikipedia.org/wiki/1930%E2%80%9331_Chicago_Black_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12791739-5.html.csv | unique | the april 13 game was the only game in which the chicago black hawks failed to score any goals . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 0 .', 'tostr': 'filter_eq { all_rows ; score ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; score ; 0 } }', 'tointer': 'select the rows whose score record fuzzily matches to 0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 0 .', 'tostr': 'filter_eq { all_rows ; score ; 0 }'}, 'date'], 'result': 'april 13', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score ; 0 } ; date }'}, 'april 13'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; score ; 0 } ; date } ; april 13 }', 'tointer': 'the date record of this unqiue row is april 13 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; score ; 0 } } ; eq { hop { filter_eq { all_rows ; score ; 0 } ; date } ; april 13 } } = true', 'tointer': 'select the rows whose score record fuzzily matches to 0 . there is only one such row in the table . the date record of this unqiue row is april 13 .'} | and { only { filter_eq { all_rows ; score ; 0 } } ; eq { hop { filter_eq { all_rows ; score ; 0 } ; date } ; april 13 } } = true | select the rows whose score record fuzzily matches to 0 . there is only one such row in the table . the date record of this unqiue row is april 13 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'april 13_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score_7': 'score', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'april 13_10': 'april 13'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'april 13_10': [3]} | ['date', 'visitor', 'score', 'home', 'record'] | [['april 3', 'montreal canadiens', '2 - 1', 'chicago black hawks', '0 - 1'], ['april 5', 'montreal canadiens', '1 - 2', 'chicago black hawks', '1 - 1'], ['april 9', 'chicago black hawks', '3 - 2', 'montreal canadiens', '2 - 1'], ['april 11', 'chicago black hawks', '2 - 4', 'montreal canadiens', '2 - 2'], ['april 13', 'chicago black hawks', '0 - 2', 'montreal canadiens', '2 - 3']] |
2008 vanderbilt commodores baseball team | https://en.wikipedia.org/wiki/2008_Vanderbilt_Commodores_baseball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15925327-6.html.csv | count | the 2008 vanderbilt commodores baseball team was not ranked by 3 polls in week 13 of the season . | {'scope': 'all', 'criterion': 'equal', 'value': 'n / r', 'result': '3', 'col': '13', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'wk 13', 'n / r'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wk 13 record fuzzily matches to n / r .', 'tostr': 'filter_eq { all_rows ; wk 13 ; n / r }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; wk 13 ; n / r } }', 'tointer': 'select the rows whose wk 13 record fuzzily matches to n / r . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; wk 13 ; n / r } } ; 3 } = true', 'tointer': 'select the rows whose wk 13 record fuzzily matches to n / r . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; wk 13 ; n / r } } ; 3 } = true | select the rows whose wk 13 record fuzzily matches to n / r . 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, 'wk 13_5': 5, 'n / r_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', 'wk 13_5': 'wk 13', 'n / r_6': 'n / r', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'wk 13_5': [0], 'n / r_6': [0], '3_7': [2]} | ['poll', 'wk 2', 'wk 3', 'wk 4', 'wk 5', 'wk 6', 'wk 7', 'wk 8', 'wk 9', 'wk 10', 'wk 11', 'wk 12', 'wk 13', 'wk 14', 'final'] | [["usa today / espn coaches ' poll ( top 25 )", '11', '12', '8', '13', '8', '17', '14', '13', '17', '14', '13', '21', '22', 'n / r'], ['baseball america ( top 25 )', '7', '6', '5', '9', '8', '19', '17', '17', '22', '18', '19', 'n / r', 'n / r', 'n / r'], ['collegiate baseball ( top 30 )', '10', '12', '9', '14', '13', '23', '22', '20', '20', '16', '17', 'n / r', '24', '27'], ['ncbwa ( top 30 )', '10', '9', '6', '11', '6', '13', '11', '10', '13', '11', '13', '21', '21', '25'], ['rivalscom ( top 25 )', '5', '4', '4', '9', '9', '17', '18', '18', '22', '18', '19', 'n / r', 'n / r', 'n / r']] |
list of england national rugby union team results 1980 - 89 | https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1980%E2%80%9389 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178608-3.html.csv | aggregation | the average against for the england national rugby union team is 11.6 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '11.6', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'against'], 'result': '11.6', 'ind': 0, 'tostr': 'avg { all_rows ; against }'}, '11.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; against } ; 11.6 } = true', 'tointer': 'the average of the against record of all rows is 11.6 .'} | round_eq { avg { all_rows ; against } ; 11.6 } = true | the average of the against record of all rows is 11.6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'against_4': 4, '11.6_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'against_4': 'against', '11.6_5': '11.6'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'against_4': [0], '11.6_5': [1]} | ['opposing teams', 'against', 'date', 'venue', 'status'] | [['australia', '11', '02 / 01 / 1982', 'twickenham , london', 'test match'], ['scotland', '9', '16 / 01 / 1982', 'murrayfield , edinburgh', 'five nations'], ['ireland', '16', '06 / 02 / 1982', 'twickenham , london', 'five nations'], ['france', '15', '20 / 02 / 1982', 'parc des princes , paris', 'five nations'], ['wales', '7', '06 / 03 / 1982', 'twickenham , london', 'five nations']] |
croatian bol ladies open | https://en.wikipedia.org/wiki/Croatian_Bol_Ladies_Open | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16157440-1.html.csv | count | corina morariu was the runner-up in the croatian bol ladies open 2 times . | {'scope': 'all', 'criterion': 'equal', 'value': 'corina morariu', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'runner - up', 'corina morariu'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose runner - up record fuzzily matches to corina morariu .', 'tostr': 'filter_eq { all_rows ; runner - up ; corina morariu }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; runner - up ; corina morariu } }', 'tointer': 'select the rows whose runner - up record fuzzily matches to corina morariu . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; runner - up ; corina morariu } } ; 2 } = true', 'tointer': 'select the rows whose runner - up record fuzzily matches to corina morariu . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; runner - up ; corina morariu } } ; 2 } = true | select the rows whose runner - up record fuzzily matches to corina morariu . 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, 'runner - up_5': 5, 'corina morariu_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', 'runner - up_5': 'runner - up', 'corina morariu_6': 'corina morariu', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'runner - up_5': [0], 'corina morariu_6': [0], '2_7': [2]} | ['year', 'category', 'champion', 'runner - up', 'score'] | [['1991', 'v', 'sandra cecchini', 'magdalena maleeva', '6 - 4 , 3 - 6 , 7 - 5'], ['1995', 'iii', 'sabine appelmans', 'silke meier', '6 - 4 , 6 - 3'], ['1996', 'iv', 'gloria pizzichini', 'silvija talaja', '6 - 0 , 6 - 2'], ['1997', 'iv', 'mirjana lučić', 'corina morariu', '7 - 5 , 6 - 7 , 7 - 6'], ['1998', 'iva', 'mirjana lučić', 'corina morariu', '6 - 2 , 6 - 4'], ['1999', 'iv', 'corina morariu', 'julie halard', '6 - 2 , 6 - 0'], ['2000', 'iii', 'tina pisnik', 'amélie mauresmo', '7 - 6 , 7 - 6'], ['2001', 'iii', 'ángeles montolio', 'mariana díaz - oliva', '3 - 6 , 6 - 2 , 6 - 4'], ['2002', 'iii', 'åsa svensson', 'iva majoli', '6 - 3 , 4 - 6 , 6 - 1'], ['2003', 'iii', 'vera zvonareva', 'conchita martínez g', '6 - 1 , 6 - 3']] |
dominique aegerter | https://en.wikipedia.org/wiki/Dominique_Aegerter | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17273933-2.html.csv | aggregation | over nine seasons , dominique aegerter competed in a total of 119 races . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '119', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'races'], 'result': '119', 'ind': 0, 'tostr': 'sum { all_rows ; races }'}, '119'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; races } ; 119 } = true', 'tointer': 'the sum of the races record of all rows is 119 .'} | round_eq { sum { all_rows ; races } ; 119 } = true | the sum of the races record of all rows is 119 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'races_4': 4, '119_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'races_4': 'races', '119_5': '119'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'races_4': [0], '119_5': [1]} | ['season', 'races', 'wins', 'podiums', 'poles'] | [['2006', '2', '0', '0', '0'], ['2007', '17', '0', '0', '0'], ['2008', '17', '0', '0', '0'], ['2009', '16', '0', '0', '0'], ['2010', '17', '0', '0', '0'], ['2011', '17', '0', '1', '0'], ['2012', '17', '0', '0', '0'], ['2013', '16', '0', '1', '0'], ['total', '119', '0', '2', '0']] |
list of malcolm in the middle episodes | https://en.wikipedia.org/wiki/List_of_Malcolm_in_the_Middle_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1876825-5.html.csv | count | levie isaacks directed a total of five episodes of malcolm in the middle . | {'scope': 'all', 'criterion': 'equal', 'value': 'levie isaacks', 'result': '5', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'levie isaacks'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to levie isaacks .', 'tostr': 'filter_eq { all_rows ; directed by ; levie isaacks }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; directed by ; levie isaacks } }', 'tointer': 'select the rows whose directed by record fuzzily matches to levie isaacks . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; directed by ; levie isaacks } } ; 5 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to levie isaacks . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; directed by ; levie isaacks } } ; 5 } = true | select the rows whose directed by record fuzzily matches to levie isaacks . 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, 'directed by_5': 5, 'levie isaacks_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', 'directed by_5': 'directed by', 'levie isaacks_6': 'levie isaacks', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'directed by_5': [0], 'levie isaacks_6': [0], '5_7': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code'] | [['64', '1', 'zoo', 'todd holland', 'michael glouberman & andrew orenstein', 'november 3 , 2002', '06 - 02 - 401'], ['65', '2', 'humilithon', 'jeff melman', 'michael borkow', 'november 10 , 2002', '06 - 02 - 402'], ['66', '3', 'family reunion', 'ken kwapis', 'alex reid', 'november 17 , 2002', '06 - 02 - 403'], ['67', '4', 'stupid girl', 'todd holland', 'dan kopelman', 'november 24 , 2002', '06 - 02 - 404'], ['68', '5', 'forwards backwards', 'levie isaacks', 'maggie bandur', 'december 1 , 2002', '06 - 02 - 406'], ['69', '6', 'forbidden girlfriend', 'jamie babbit', 'matthew carlson', 'december 15 , 2002', '06 - 02 - 405'], ['70', '7', 'malcolm holds his tongue', 'jeff melman', 'gary murphy & neil thompson', 'january 5 , 2003', '06 - 02 - 410'], ['71', '8', 'boys at ranch', "david d'ovidio", 'gary murphy & neil thompson', 'january 12 , 2003', '06 - 02 - 412'], ['72', '9', 'grandma sues', 'jimmy simons', 'michael glouberman & andrew orenstein', 'february 2 , 2003', '06 - 02 - 407'], ['74', '11', 'long drive', 'levie isaacks', 'michael borkow', 'march 2 , 2003', '06 - 02 - 409'], ['75', '12', 'kicked out', 'jeff melman', 'alex reid', 'march 9 , 2003', '06 - 02 - 413'], ['76', '13', 'stereo store', 'bryan cranston', 'matthew carlson', 'march 16 , 2003', '06 - 02 - 414'], ['77', '14', "hal 's friend", 'jeff melman', 'dan kopelman', 'march 30 , 2003', '06 - 02 - 415'], ['78', '15', 'garage sale', 'levie isaacks', 'maggie bandur', 'april 6 , 2003', '06 - 02 - 416'], ['79', '16', 'academic octathalon', 'todd holland', 'rob hanning', 'april 13 , 2003', '06 - 02 - 411'], ['80', '17', 'clip show 2', 'levie isaacks', 'maggie bandur & dan kopelman', 'april 20 , 2003', '06 - 02 - 422'], ['81', '18', "reese 's party", 'levie isaacks', 'andy bobrow', 'april 27 , 2003', '06 - 02 - 418'], ['83', '20', 'baby : part 1', 'jimmy simons', 'rob hanning', 'may 11 , 2003', '06 - 02 - 419'], ['84', '21', 'baby : part 2', 'jamie babbit', 'michael borkow', 'may 18 , 2003', '06 - 02 - 420']] |
2008 - 09 nbl season | https://en.wikipedia.org/wiki/2008%E2%80%9309_NBL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16653153-28.html.csv | ordinal | in the 2008-09 nbl season , the game with the 2nd largest crowd was when the adelaide 36ers were the home team . | {'row': '5', 'col': '6', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 2 }'}, 'home team'], 'result': 'adelaide 36ers', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 2 } ; home team }'}, 'adelaide 36ers'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; adelaide 36ers } = true', 'tointer': 'select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is adelaide 36ers .'} | eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; home team } ; adelaide 36ers } = true | select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is adelaide 36ers . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '2_6': 6, 'home team_7': 7, 'adelaide 36ers_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '2_6': '2', 'home team_7': 'home team', 'adelaide 36ers_8': 'adelaide 36ers'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '2_6': [0], 'home team_7': [1], 'adelaide 36ers_8': [2]} | ['date', 'home team', 'score', 'away team', 'venue', 'crowd', 'box score', 'report'] | [['4 february', 'south dragons', '97 - 77', 'adelaide 36ers', 'hisense arena', '4621', 'box score', '-'], ['4 february', 'sydney spirit', '81 - 89', 'cairns taipans', 'state sports centre', '920', 'box score', '-'], ['6 february', 'townsville crocodiles', '101 - 98', 'south dragons', 'townsville entertainment centre', '4485', 'box score', '-'], ['6 february', 'wollongong hawks', '103 - 98', 'new zealand breakers', 'win entertainment centre', '2740', 'box score', '-'], ['7 february', 'adelaide 36ers', '102 - 91', 'new zealand breakers', 'distinctive homes dome', '8000', 'box score', '-'], ['7 february', 'cairns taipans', '88 - 93', 'gold coast blaze', 'cairns convention centre', '4022', 'box score', '-'], ['7 february', 'perth wildcats', '106 - 88', 'sydney spirit', 'challenge stadium', '4000', 'box score', '-'], ['8 february', 'south dragons', '93 - 83', 'melbourne tigers', 'hisense arena', '8093', 'box score', '-']] |
1989 phoenix cardinals season | https://en.wikipedia.org/wiki/1989_Phoenix_Cardinals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16642092-1.html.csv | comparative | in the 1989 phoenix cardinals season , john burch was picked one round before kendall trainor . | {'row_1': '10', 'row_2': '11', 'col': '1', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'john burch'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to john burch .', 'tostr': 'filter_eq { all_rows ; player ; john burch }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; john burch } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to john burch . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'kendall trainor'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to kendall trainor .', 'tostr': 'filter_eq { all_rows ; player ; kendall trainor }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; kendall trainor } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to kendall trainor . take the round record of this row .'}], 'result': '-1', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; player ; john burch } ; round } ; hop { filter_eq { all_rows ; player ; kendall trainor } ; round } }'}, '-1'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; player ; john burch } ; round } ; hop { filter_eq { all_rows ; player ; kendall trainor } ; round } } ; -1 } = true', 'tointer': 'select the rows whose player record fuzzily matches to john burch . take the round record of this row . select the rows whose player record fuzzily matches to kendall trainor . take the round record of this row . the second record is 1 larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; player ; john burch } ; round } ; hop { filter_eq { all_rows ; player ; kendall trainor } ; round } } ; -1 } = true | select the rows whose player record fuzzily matches to john burch . take the round record of this row . select the rows whose player record fuzzily matches to kendall trainor . take the round record of this row . the second record is 1 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'player_8': 8, 'john burch_9': 9, 'round_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'kendall trainor_13': 13, 'round_14': 14, '-1_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'player_8': 'player', 'john burch_9': 'john burch', 'round_10': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player', 'kendall trainor_13': 'kendall trainor', 'round_14': 'round', '-1_15': '-1'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'john burch_9': [0], 'round_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'kendall trainor_13': [1], 'round_14': [3], '-1_15': [5]} | ['round', 'pick', 'player', 'position', 'school / club team'] | [['1', '10', 'eric hill', 'linebacker', 'louisiana state'], ['1', '17', 'joe wolf', 'offensive guard', 'boston college'], ['2', '40', 'walter reeves', 'tight end', 'auburn'], ['3', '67', 'mike zandofsky', 'guard', 'washington'], ['4', '94', 'jim wahler', 'defensive tackle', 'ucla'], ['5', '123', 'richard tardits', 'linebacker', 'georgia'], ['5', '128', 'david edeen', 'defensive end', 'wyoming'], ['6', '150', 'jay taylor', 'defensive back', 'san jose state'], ['7', '177', 'rickey royal', 'defensive back', 'sam houston state'], ['8', '207', 'john burch', 'running back', 'tennessee - martin'], ['9', '234', 'kendall trainor', 'kicker', 'arkansas'], ['10', '261', 'chris becker', 'punter', 'texas christian'], ['11', '291', 'jeffrey hunter', 'defensive end', 'albany state'], ['12', '318', 'todd nelson', 'guard', 'wisconsin'], ['1', '2', 'timm rosenbach ( supplemental draft )', 'quarterback', 'washington state']] |
list of soccer clubs in australia | https://en.wikipedia.org/wiki/List_of_soccer_clubs_in_Australia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1742186-14.html.csv | superlative | adelaide galaxy is the australian soccer club that was founded the earliest . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'founded'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; founded }'}, 'team'], 'result': 'adelaide galaxy', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; founded } ; team }'}, 'adelaide galaxy'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; founded } ; team } ; adelaide galaxy } = true', 'tointer': 'select the row whose founded record of all rows is minimum . the team record of this row is adelaide galaxy .'} | eq { hop { argmin { all_rows ; founded } ; team } ; adelaide galaxy } = true | select the row whose founded record of all rows is minimum . the team record of this row is adelaide galaxy . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'founded_5': 5, 'team_6': 6, 'adelaide galaxy_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'founded_5': 'founded', 'team_6': 'team', 'adelaide galaxy_7': 'adelaide galaxy'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'founded_5': [0], 'team_6': [1], 'adelaide galaxy_7': [2]} | ['team', 'coach', 'home ground', 'location', 'founded'] | [['adelaide blue eagles', 'zoran karadzic', 'marden sports complex', 'marden', '1958'], ['adelaide city', 'damian mori', 'adelaide city park', 'oakden', '1946'], ['adelaide galaxy', 'brenton heirn', 'con makris park', 'novar gardens', '1933'], ['adelaide raiders', 'michael barnett', 'croatian sports centre', 'gepps cross', '1952'], ['campbelltown city', 'jason trimboli', 'newton sportsground', 'campbelltown', '1963'], ['croydon kings', 'john kosmina', 'polonia reserve', 'croydon', '1950'], ['modbury jets', 'earl pudler', 'jet park', 'modbury north', '1964'], ['metrostars', 'david terminello', 'tk shutter reserve', 'klemzig', '1994'], ['para hills knights', 'kenneth tosh', 'the paddocks', 'para hills', '1964'], ['western strikers', 'charlie villani', 'carnegie reserve', 'royal park', '1998']] |
taniec z gwiazdami | https://en.wikipedia.org/wiki/Taniec_z_gwiazdami | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15988037-19.html.csv | aggregation | the celebrities in the taniec z gwiazdami competition had a combined average score of 25.2 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '25.2', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'average'], 'result': '25.2', 'ind': 0, 'tostr': 'avg { all_rows ; average }'}, '25.2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; average } ; 25.2 } = true', 'tointer': 'the average of the average record of all rows is 25.2 .'} | round_eq { avg { all_rows ; average } ; 25.2 } = true | the average of the average record of all rows is 25.2 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'average_4': 4, '25.2_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'average_4': 'average', '25.2_5': '25.2'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'average_4': [0], '25.2_5': [1]} | ['rank', 'celebrity', 'professional partner', 'season', 'average'] | [['1', 'maciej jachowski', 'janja lesar', '12', '32.0'], ['2', 'stachursky', 'dominika kublik - marzec', '6', '29.0'], ['3', 'przemysław miarczyński', 'magdalena soszyńska - michno', '11', '28.5'], ['4', 'piotr adamski', 'blanka winiarska', '2', '28.0'], ['5', 'paweł stasiak', 'janja lesar', '8', '27.0'], ['5', 'marek kościkiewicz', 'agnieszka pomorska', '10', '27.0'], ['6', 'wojciech majchrzak', 'magdalena soszyńska - michno', '5', '25.5'], ['7', 'michał milowicz', 'izabela mika', '4', '25.0'], ['7', 'michał lesień', 'katarzyna krupa', '7', '25.0'], ['8', 'robert kudelski', 'agnieszka pomorska', '1', '24.0'], ['9', 'paolo cozza', 'kamila drezno', '3', '18.5'], ['10', 'zbigniew urbański', 'izabela janachowska', '13', '13.0']] |
azeotrope ( data ) | https://en.wikipedia.org/wiki/Azeotrope_%28data%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10181793-9.html.csv | count | acetone was the second component a total of 3 times . | {'scope': 'all', 'criterion': 'equal', 'value': 'acetone', 'result': '3', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2nd component', 'acetone'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2nd component record fuzzily matches to acetone .', 'tostr': 'filter_eq { all_rows ; 2nd component ; acetone }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; 2nd component ; acetone } }', 'tointer': 'select the rows whose 2nd component record fuzzily matches to acetone . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; 2nd component ; acetone } } ; 3 } = true', 'tointer': 'select the rows whose 2nd component record fuzzily matches to acetone . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; 2nd component ; acetone } } ; 3 } = true | select the rows whose 2nd component record fuzzily matches to acetone . 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, '2nd component_5': 5, 'acetone_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', '2nd component_5': '2nd component', 'acetone_6': 'acetone', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], '2nd component_5': [0], 'acetone_6': [0], '3_7': [2]} | ['2nd component', 'bp 2nd comp ( ˚c )', '3rd component', 'bp 3rd comp ( ˚c )', 'bp azeo ( ˚c )'] | [['acetone', '56.5', 'chloroform', '61.2', '57.5'], ['acetone', '56.5', 'methyl acetate', '57.0', '53.7'], ['acetone', '56.5', 'cyclohexane', '81.4', '51.5'], ['methyl acetate', '57.1', 'carbon disulfide', '46.2', '37.0'], ['methyl acetate', '57.1', 'cyclohexane', '81.4', '50.8'], ['methyl acetate', '57.1', 'n - hexane', '69.0', '45.0']] |
ana timotić | https://en.wikipedia.org/wiki/Ana_Timoti%C4%87 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11326124-1.html.csv | ordinal | melinda czink was the 2nd earliest opponent of ana timotić . | {'row': '2', 'col': '2', 'order': '2', 'col_other': '5', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 2 }'}, 'opponent in the final'], 'result': 'melinda czink', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 2 } ; opponent in the final }'}, 'melinda czink'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 2 } ; opponent in the final } ; melinda czink } = true', 'tointer': 'select the row whose date record of all rows is 2nd minimum . the opponent in the final record of this row is melinda czink .'} | eq { hop { nth_argmin { all_rows ; date ; 2 } ; opponent in the final } ; melinda czink } = true | select the row whose date record of all rows is 2nd minimum . the opponent in the final record of this row is melinda czink . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'opponent in the final_7': 7, 'melinda czink_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '2_6': '2', 'opponent in the final_7': 'opponent in the final', 'melinda czink_8': 'melinda czink'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'opponent in the final_7': [1], 'melinda czink_8': [2]} | ['outcome', 'date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['winner', '8 april 2001', 'athens , greece', 'clay', 'elena yaryshka', '7 - 5 , 6 - 3'], ['winner', '22 april 2001', 'belgrade , fr yugoslavia', 'clay', 'melinda czink', '6 - 3 , 5 - 7 , 7 - 5'], ['winner', '1 july 2001', 'båstad , sweden', 'clay', 'amanda hopmans', '3 - 6 , 6 - 3 , 6 - 0'], ['winner', '22 september 2002', 'barcelona , spain', 'clay', 'maría josé sánchez alayeto', '6 - 3 , 7 - 5'], ['winner', '20 october 2002', 'makarska , croatia', 'clay', 'lenka novotná', '6 - 4 , 3 - 6 , 6 - 1'], ['runner - up', '24 november 2002', 'mallorca , spain', 'clay', 'maría josé sánchez alayeto', '6 - 2 , 3 - 6 , 6 - 3'], ['runner - up', '1 december 2002', 'mallorca , spain', 'clay', 'rosa maría andrés rodríguez', '7 - 5 , 7 - 5'], ['winner', '22 june 2003', 'canet - en - roussillon , france', 'clay', 'amadine singla', '6 - 1 , 6 - 2'], ['runner - up', '27 july 2003', 'horb , germany', 'clay', 'maria kondratieva', '7 - 5 , 6 - 3'], ['winner', '3 august 2003', 'saulgau , germany', 'clay', 'tina schiechtl', '4 - 6 , 6 - 2 , 7 - 5'], ['winner', '10 august 2003', 'hechingen , germany', 'clay', 'elise tamaëla', '4 - 6 , 6 - 4 , 6 - 2'], ['runner - up', '28 september 2003', 'jounieh , lebanon', 'clay', 'kyra nagy', '6 - 1 , 7 - 5'], ['runner - up', '15 february 2004', 'mallorca , spain', 'clay', 'laura pous tió', '4 - 6 , 6 - 3 , 6 - 0'], ['runner - up', '22 february 2004', 'mallorca , spain', 'clay', 'ana ivanovic', '6 - 1 , 6 - 1'], ['winner', '10 july 2005', 'toruń , poland', 'clay', 'joanna sakowicz', '6 - 1 , 6 - 2'], ['runner - up', '25 september 2005', 'tbilisi , georgia', 'clay', 'sandra záhlavová', '6 - 0 , 6 - 3'], ['runner - up', '2 october 2005', 'batumi , georgia', 'hard', 'anastasiya yakimova', '6 - 4 , 6 - 1'], ['runner - up', '22 october 2005', 'seville , spain', 'clay', 'conchita martínez granados', '6 - 2 , 6 - 2'], ['runner - up', '21 october 2006', 'seville , spain', 'clay', 'verdiana verardi', '6 - 4 , 6 - 4'], ['runner - up', '29 july 2007', 'horb , germany', 'clay', 'natalia orlova', '1 - 6 , 6 - 0 , 6 - 3']] |
list of carnivàle episodes | https://en.wikipedia.org/wiki/List_of_Carniv%C3%A0le_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12722302-2.html.csv | unique | in the list of carnivàle episodes , the river is the only episode directed by a woman by the name alison maclean . | {'scope': 'all', 'row': '6', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'alison maclean', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'alison maclean'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to alison maclean .', 'tostr': 'filter_eq { all_rows ; directed by ; alison maclean }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; directed by ; alison maclean } }', 'tointer': 'select the rows whose directed by record fuzzily matches to alison maclean . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'alison maclean'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to alison maclean .', 'tostr': 'filter_eq { all_rows ; directed by ; alison maclean }'}, 'title'], 'result': 'the river', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; directed by ; alison maclean } ; title }'}, 'the river'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; directed by ; alison maclean } ; title } ; the river }', 'tointer': 'the title record of this unqiue row is the river .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; directed by ; alison maclean } } ; eq { hop { filter_eq { all_rows ; directed by ; alison maclean } ; title } ; the river } } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to alison maclean . there is only one such row in the table . the title record of this unqiue row is the river .'} | and { only { filter_eq { all_rows ; directed by ; alison maclean } } ; eq { hop { filter_eq { all_rows ; directed by ; alison maclean } ; title } ; the river } } = true | select the rows whose directed by record fuzzily matches to alison maclean . there is only one such row in the table . the title record of this unqiue row is the river . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'directed by_7': 7, 'alison maclean_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'the river_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'directed by_7': 'directed by', 'alison maclean_8': 'alison maclean', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'the river_10': 'the river'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'directed by_7': [0], 'alison maclean_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'the river_10': [3]} | ['no', 'title', 'directed by', 'written by', 'bens location', 'original air date', 'us viewers ( million )'] | [['1', 'milfay', 'rodrigo garcía', 'daniel knauf', 'milfay , oklahoma', 'september 14 , 2003', '5.3'], ['2', 'after the ball is over', 'jeremy podeswa', 'daniel knauf & ronald d moore', 'n / a', 'september 21 , 2003', '3.49'], ['4', 'black blizzard', 'peter medak', 'william schmidt', 'n / a', 'october 5 , 2003', '2.87'], ['5', 'babylon', 'tim hunter', 'dawn prestwich & nicole yorkin', 'babylon , texas', 'october 12 , 2003', '3.31'], ['6', 'pick a number', 'rodrigo garcía', 'ronald d moore', 'babylon , texas', 'october 19 , 2003', '3.40'], ['7', 'the river', 'alison maclean', 'toni graphia', 'texas', 'october 26 , 2003', '3.90'], ['8', 'lonnigan , texas', 'scott winant', 'daniel knauf', 'lonnigan , texas', 'november 2 , 2003', '2.96'], ['9', 'insomnia', 'jack bender', 'william schmidt', 'n / a', 'november 9 , 2003', '3.41'], ['10', 'hot and bothered', 'jeremy podeswa', 'dawn prestwich & nicole yorkin', 'loving , new mexico', 'november 16 , 2003', '3.19'], ['11', 'day of the dead', 'john patterson', 'toni graphia', 'loving , new mexico', 'november 23 , 2003', '2.56']] |
family life radio | https://en.wikipedia.org/wiki/Family_Life_Radio | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17101015-10.html.csv | majority | all family life radio 's cities of license are in texas . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'texas', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'city of license', 'texas'], 'result': True, 'ind': 0, 'tointer': 'for the city of license records of all rows , all of them fuzzily match to texas .', 'tostr': 'all_eq { all_rows ; city of license ; texas } = true'} | all_eq { all_rows ; city of license ; texas } = true | for the city of license records of all rows , all of them fuzzily match to texas . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'city of license_3': 3, 'texas_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'city of license_3': 'city of license', 'texas_4': 'texas'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'city of license_3': [0], 'texas_4': [0]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'fcc info'] | [['kamy', '90.1', 'lubbock , texas', '63000', ''], ['kflb', '88.1', 'midland , texas', '100000', ''], ['kflb', '920', 'odessa , texas', '1000 day 500 night', ''], ['krgn', '102.9', 'amarillo , texas', '100000', ''], ['k297au', '107.3', 'big spring , texas', '62', 'fcc']] |
1953 - 54 new york rangers season | https://en.wikipedia.org/wiki/1953%E2%80%9354_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17311466-7.html.csv | aggregation | the toronto maple leaves scored a total of 12 goals against the new york rangers in the 1953-54 season . | {'scope': 'subset', 'col': '4', 'type': 'sum', 'result': '12', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'toronto maple leafs'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'toronto maple leafs'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; toronto maple leafs }', 'tointer': 'select the rows whose opponent record fuzzily matches to toronto maple leafs .'}, 'score'], 'result': '12', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; opponent ; toronto maple leafs } ; score }'}, '12'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; opponent ; toronto maple leafs } ; score } ; 12 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to toronto maple leafs . the sum of the score record of these rows is 12 .'} | round_eq { sum { filter_eq { all_rows ; opponent ; toronto maple leafs } ; score } ; 12 } = true | select the rows whose opponent record fuzzily matches to toronto maple leafs . the sum of the score record of these rows is 12 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'toronto maple leafs_6': 6, 'score_7': 7, '12_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', 'toronto maple leafs_6': 'toronto maple leafs', 'score_7': 'score', '12_8': '12'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'toronto maple leafs_6': [0], 'score_7': [1], '12_8': [2]} | ['game', 'march', 'opponent', 'score', 'record'] | [['62', '3', 'toronto maple leafs', '3 - 3', '25 - 28 - 9'], ['63', '5', 'chicago black hawks', '0 - 0', '25 - 28 - 10'], ['64', '7', 'toronto maple leafs', '4 - 0', '25 - 29 - 10'], ['65', '10', 'chicago black hawks', '4 - 2', '26 - 29 - 10'], ['66', '11', 'boston bruins', '1 - 0', '26 - 30 - 10'], ['67', '13', 'detroit red wings', '5 - 2', '27 - 30 - 10'], ['68', '14', 'detroit red wings', '2 - 0', '28 - 30 - 10'], ['69', '20', 'toronto maple leafs', '5 - 2', '29 - 30 - 10'], ['70', '21', 'montreal canadiens', '3 - 1', '29 - 31 - 10']] |
moses ndiema masai | https://en.wikipedia.org/wiki/Moses_Ndiema_Masai | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16682451-1.html.csv | unique | the only senior race moses ndiema masai competed in was in 2008 . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'senior race', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'senior race'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record fuzzily matches to senior race .', 'tostr': 'filter_eq { all_rows ; event ; senior race }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; event ; senior race } }', 'tointer': 'select the rows whose event record fuzzily matches to senior race . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'senior race'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record fuzzily matches to senior race .', 'tostr': 'filter_eq { all_rows ; event ; senior race }'}, 'year'], 'result': '2008', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; event ; senior race } ; year }'}, '2008'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; event ; senior race } ; year } ; 2008 }', 'tointer': 'the year record of this unqiue row is 2008 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; event ; senior race } } ; eq { hop { filter_eq { all_rows ; event ; senior race } ; year } ; 2008 } } = true', 'tointer': 'select the rows whose event record fuzzily matches to senior race . there is only one such row in the table . the year record of this unqiue row is 2008 .'} | and { only { filter_eq { all_rows ; event ; senior race } } ; eq { hop { filter_eq { all_rows ; event ; senior race } ; year } ; 2008 } } = true | select the rows whose event record fuzzily matches to senior race . there is only one such row in the table . the year record of this unqiue row is 2008 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'event_7': 7, 'senior race_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2008_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'event_7': 'event', 'senior race_8': 'senior race', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2008_10': '2008'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'event_7': [0], 'senior race_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2008_10': [3]} | ['year', 'competition', 'venue', 'position', 'event'] | [['2004', 'world junior championships', 'grosseto , italy', '10th', '10000 m'], ['2005', 'african junior championships', 'radès , tunisia', '1st', '5000 m'], ['2005', 'african junior championships', 'radès , tunisia', '1st', '10000 m'], ['2007', 'world athletics final', 'stuttgart , germany', '3rd', '5000 m'], ['2008', 'world cross country championships', 'edinburgh , scotland', '5th', 'senior race'], ['2008', 'world cross country championships', 'edinburgh , scotland', '1st', 'team competition'], ['2009', 'world championships', 'berlin , germany', '3rd', '10000 m'], ['2013', 'okpekpe international road race', 'okpekpe , nigeria', '1st', '10 kilometres']] |
2001 cfl draft | https://en.wikipedia.org/wiki/2001_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15817998-2.html.csv | unique | montreal alouettes was the only qb picked from picks 9-16 in the 2001 cfl draft . | {'scope': 'all', 'row': '7', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'qb', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'qb'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to qb .', 'tostr': 'filter_eq { all_rows ; position ; qb }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; qb } }', 'tointer': 'select the rows whose position record fuzzily matches to qb . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'qb'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to qb .', 'tostr': 'filter_eq { all_rows ; position ; qb }'}, 'cfl team'], 'result': 'montreal alouettes', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; qb } ; cfl team }'}, 'montreal alouettes'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; qb } ; cfl team } ; montreal alouettes }', 'tointer': 'the cfl team record of this unqiue row is montreal alouettes .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; qb } } ; eq { hop { filter_eq { all_rows ; position ; qb } ; cfl team } ; montreal alouettes } } = true', 'tointer': 'select the rows whose position record fuzzily matches to qb . there is only one such row in the table . the cfl team record of this unqiue row is montreal alouettes .'} | and { only { filter_eq { all_rows ; position ; qb } } ; eq { hop { filter_eq { all_rows ; position ; qb } ; cfl team } ; montreal alouettes } } = true | select the rows whose position record fuzzily matches to qb . there is only one such row in the table . the cfl team record of this unqiue row is montreal alouettes . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'qb_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'cfl team_9': 9, 'montreal alouettes_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', 'qb_8': 'qb', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'cfl team_9': 'cfl team', 'montreal alouettes_10': 'montreal alouettes'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'qb_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'cfl team_9': [2], 'montreal alouettes_10': [3]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['9', 'saskatchewan roughriders', 'jason french', 'wr', 'murray state'], ['10', 'calgary stampeders', 'lawrence deck', 'db', 'fresno state'], ['11', 'montreal alouettes', 'pat woodcock', 'wr', 'syracuse'], ['12', 'hamilton tiger - cats', 'karim grant', 'lb', 'acadia'], ['13', 'edmonton eskimos', 'fabian burke', 'cb', 'toledo'], ['14', 'calgary stampeders', "duncan o'mahony", 'k', 'british columbia'], ['15', 'montreal alouettes', 'jesse palmer', 'qb', 'florida'], ['16', 'bc lions', 'jamie boreham', 'k / s', 'manitoba']] |
aalesunds fk | https://en.wikipedia.org/wiki/Aalesunds_FK | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1149273-1.html.csv | aggregation | the average score aalesuns fk has scored at a home game is three points . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '3', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'home'], 'result': '3', 'ind': 0, 'tostr': 'avg { all_rows ; home }'}, '3'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; home } ; 3 } = true', 'tointer': 'the average of the home record of all rows is 3 .'} | round_eq { avg { all_rows ; home } ; 3 } = true | the average of the home record of all rows is 3 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'home_4': 4, '3_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'home_4': 'home', '3_5': '3'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'home_4': [0], '3_5': [1]} | ['season', 'competition', 'round', 'club', 'home', 'away', 'aggregate'] | [['2010 - 11', 'uefa europa league', 'q3', 'motherwell', '1 - 1', '0 - 3', '1 - 4'], ['2011 - 12', 'uefa europa league', 'q1', 'neath', '4 - 1', '2 - 0', '6 - 1'], ['2011 - 12', 'uefa europa league', 'q2', 'ferencváros', '3 - 1 ( aet )', '1 - 2', '4 - 3'], ['2011 - 12', 'uefa europa league', 'q3', 'elfsborg', '4 - 0', '1 - 1', '5 - 1'], ['2011 - 12', 'uefa europa league', 'play - off', 'az', '2 - 1', '0 - 6', '2 - 7'], ['2012 - 13', 'uefa europa league', 'q2', 'tirana', '5 - 0', '1 - 1', '6 - 1'], ['2012 - 13', 'uefa europa league', 'q3', 'apoel', '0 - 1', '1 - 2', '1 - 3']] |
political appointments system in hong kong | https://en.wikipedia.org/wiki/Political_Appointments_System_in_Hong_Kong | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17964087-1.html.csv | aggregation | the average age of appointment of those of british nationality was 46 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '46', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'age at appointment'], 'result': '46', 'ind': 0, 'tostr': 'avg { all_rows ; age at appointment }'}, '46'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; age at appointment } ; 46 } = true', 'tointer': 'the average of the age at appointment record of all rows is 46 .'} | round_eq { avg { all_rows ; age at appointment } ; 46 } = true | the average of the age at appointment record of all rows is 46 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'age at appointment_4': 4, '46_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'age at appointment_4': 'age at appointment', '46_5': '46'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'age at appointment_4': [0], '46_5': [1]} | ['romanised name', 'chinese name', 'age at appointment', 'foreign nationality', 'portfolio attachment', 'govt salary'] | [['chen wei - on , kenneth', '陳維安', '43', 'n / a', 'education', 'hk223585'], ['hui hiu - fai , florence', '許曉暉', '34', 'n / a', 'home affairs', 'hk223585'], ['leung fung - yee , julia', '梁鳳儀', '48', 'british', 'financial services and the treasury', 'hk223585'], ['leung , gabriel matthew', '梁卓偉', '35', 'canadian', 'food and health', 'hk208680'], ['poon kit , kitty', '潘潔', '45', 'us', 'environment', 'hk208680'], ['tam chi - yuen , raymond', '譚志源', '44', 'british', 'constitutional and mainland affairs', 'hk208680'], ['so kam - leung , gregory', '蘇錦樑', '49', 'canadian', 'commerce and economic development', 'hk223585'], ['yau shing - mu', '邱誠武', '48', 'n / a', 'transport and housing', 'hk 208680']] |
jason leffler | https://en.wikipedia.org/wiki/Jason_Leffler | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1637041-4.html.csv | superlative | jason leffler 's highest number of top 10 positions was in the year 2009 . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'top 10'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; top 10 }'}, 'year'], 'result': '2009', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; top 10 } ; year }'}, '2009'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; top 10 } ; year } ; 2009 } = true', 'tointer': 'select the row whose top 10 record of all rows is maximum . the year record of this row is 2009 .'} | eq { hop { argmax { all_rows ; top 10 } ; year } ; 2009 } = true | select the row whose top 10 record of all rows is maximum . the year record of this row is 2009 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'top 10_5': 5, 'year_6': 6, '2009_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'top 10_5': 'top 10', 'year_6': 'year', '2009_7': '2009'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'top 10_5': [0], 'year_6': [1], '2009_7': [2]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1999', '4', '0', '0', '0', '0', '28.0', '26.8', '36400', '74th', '18 joe gibbs racing'], ['2000', '31', '0', '2', '4', '3', '24.3', '23.0', '513068', '20th', '18 joe gibbs racing'], ['2003', '6', '0', '1', '1', '0', '15.0', '14.3', '113345', '52nd', '00 haas cnc racing'], ['2004', '27', '1', '8', '17', '1', '9.4', '11.0', '1168779', '12th', '00 haas cnc racing'], ['2005', '15', '0', '2', '7', '0', '19.0', '14.6', '400883', '30th', '32 braun racing'], ['2006', '35', '0', '3', '7', '2', '20.2', '21.2', '1182579', '13th', '32 / 38 braun racing'], ['2007', '35', '1', '7', '11', '2', '17.6', '17.5', '1691099', '3rd', '38 braun racing'], ['2008', '35', '0', '3', '13', '0', '14.5', '16.2', '1350927', '9th', '38 braun racing'], ['2009', '35', '0', '8', '20', '0', '15.9', '12.4', '1699080', '4th', '38 braun racing'], ['2010', '35', '0', '6', '14', '0', '16.1', '17.5', '1272165', '9th', '10 / 38 braun racing'], ['2011', '34', '0', '2', '12', '0', '13.0', '13.9', '1131158', '6th', '30 / 38 turner motorsports'], ['2012', '2', '0', '0', '1', '0', '6.5', '10.0', '56388', '120th 1', '30 turner motorsports']] |
1987 pga tour | https://en.wikipedia.org/wiki/1987_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14640069-4.html.csv | majority | all the players which participated in the 1987 pga tour were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; country ; united states } = true'} | all_eq { all_rows ; country ; united states } = true | for the country records of all rows , all of them fuzzily match to united states . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'jack nicklaus', 'united states', '4976980', '73'], ['2', 'tom watson', 'united states', '4701629', '37'], ['3', 'tom kite', 'united states', '3445007', '10'], ['4', 'raymond floyd', 'united states', '3372339', '21'], ['5', 'lee trevino', 'united states', '3315502', '29']] |
2008 - 09 prva hnl | https://en.wikipedia.org/wiki/2008%E2%80%9309_Prva_HNL | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17563103-2.html.csv | count | a total of three outgoing managers left with mutual consent in the 2008 - 09 prva hnl season . | {'scope': 'all', 'criterion': 'equal', 'value': 'mutual consent', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'mutual consent'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to mutual consent .', 'tostr': 'filter_eq { all_rows ; manner of departure ; mutual consent }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; manner of departure ; mutual consent } }', 'tointer': 'select the rows whose manner of departure record fuzzily matches to mutual consent . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; manner of departure ; mutual consent } } ; 3 } = true', 'tointer': 'select the rows whose manner of departure record fuzzily matches to mutual consent . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; manner of departure ; mutual consent } } ; 3 } = true | select the rows whose manner of departure record fuzzily matches to mutual consent . 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, 'manner of departure_5': 5, 'mutual consent_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', 'manner of departure_5': 'manner of departure', 'mutual consent_6': 'mutual consent', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'manner of departure_5': [0], 'mutual consent_6': [0], '3_7': [2]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment', 'position in table'] | [['nk zagreb', 'miroslav blažević', 'mutual consent', '10 may 2008', 'luka pavlović', '11 may 2008', 'pre - season'], ['dinamo zagreb', 'zvonimir soldo', 'resigned', '14 may 2008', 'branko ivanković', '20 may 2008', 'pre - season'], ['slaven belupo', 'krunoslav jurčić', 'resigned', '14 may 2008', 'mile petković', '26 may 2008', 'pre - season'], ['hajduk split', 'robert jarni', 'sacked', '24 may 2008', 'goran vučević', '25 may 2008', 'pre - season'], ['croatia sesvete', 'zlatko kranjčar', 'resigned', '18 june 2008', 'ljupko petrović', '2 july 2008', 'pre - season'], ['rijeka', 'zlatko dalić', 'sacked', '1 july 2008', 'mladen ivančić', '7 july 2008', 'pre - season'], ['osijek', 'ilija lončarević', 'sacked', '26 september 2008', 'tomislav steinbrückner', '26 september 2008', '10th'], ['zadar', 'dalibor zebić', 'resigned', '28 september 2008', 'ivica datković', '9 october 2008', '12th'], ['rijeka', 'mladen ivančić', 'resigned', '8 october 2008', 'robert rubčić', '13 october 2008', '7th'], ['inter zaprešić', 'milivoj bračun', 'resigned', '20 october 2008', 'borimir perković', '20 october 2008', '11th'], ['hajduk split', 'goran vučević', 'resigned', '26 october 2008', 'ante miše', '21 november 2008', '3rd'], ['cibalia', 'srećko lušić', 'sacked', '10 november 2008', 'stanko mršić', '14 november 2008', '11th'], ['dinamo zagreb', 'branko ivanković', 'mutual consent', '24 november 2008', 'marijan vlak', '24 november 2008', '1st'], ['croatia sesvete', 'ljupko petrović', 'resigned', '7 december 2008', 'zlatko kranjčar', '30 december 2008', '10th'], ['zadar', 'ivica datković', 'mutual consent', '21 december 2008', 'dalibor zebić', '30 december 2008', '12th'], ['croatia sesvete', 'zlatko kranjčar', 'resigned', '21 february 2009', 'milan đuričić', '3 may 2009', '10th'], ['dinamo zagreb', 'marijan vlak', 'sacked', '5 march 2009', 'krunoslav jurčić', '5 march 2009', '2nd']] |
89th united states congress | https://en.wikipedia.org/wiki/89th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1847180-3.html.csv | count | two of the vacators of the 89th united states congress came from the state of south carolina . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'south carolina', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'state ( class )', 'south carolina'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose state ( class ) record fuzzily matches to south carolina .', 'tostr': 'filter_eq { all_rows ; state ( class ) ; south carolina }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; state ( class ) ; south carolina } }', 'tointer': 'select the rows whose state ( class ) record fuzzily matches to south carolina . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; state ( class ) ; south carolina } } ; 2 } = true', 'tointer': 'select the rows whose state ( class ) record fuzzily matches to south carolina . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; state ( class ) ; south carolina } } ; 2 } = true | select the rows whose state ( class ) record fuzzily matches to south carolina . 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, 'state (class)_5': 5, 'south carolina_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', 'state (class)_5': 'state ( class )', 'south carolina_6': 'south carolina', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'state (class)_5': [0], 'south carolina_6': [0], '2_7': [2]} | ['state ( class )', 'vacator', 'reason for change', 'successor', "date of successor 's formal installation"] | [['south carolina ( 3 )', 'olin d johnston ( d )', 'died april 18 , 1965', 'donald s russell ( d )', 'april 22 , 1965'], ['south carolina ( 3 )', 'donald s russell ( d )', 'successor elected november 8 , 1965', 'ernest hollings ( d )', 'november 9 , 1965'], ['virginia ( 1 )', 'harry f byrd ( d )', 'resigned november 10 , 1965', 'harry f byrd , jr ( d )', 'november 12 , 1965'], ['michigan ( 2 )', 'patrick v mcnamara ( d )', 'died april 30 , 1966', 'robert p griffin ( r )', 'may 11 , 1966'], ['virginia ( 2 )', 'a willis robertson ( d )', 'resigned december 30 , 1966', 'william b spong , jr ( d )', 'december 31 , 1966'], ['tennessee ( 2 )', 'ross bass ( d )', 'resigned january 2 , 1967', 'vacant', 'not filled this term']] |
1994 - 95 philadelphia flyers season | https://en.wikipedia.org/wiki/1994%E2%80%9395_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14022127-7.html.csv | majority | the philadelphia flyers were the home team in the majority of games . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'philadelphia', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'home', 'philadelphia'], 'result': True, 'ind': 0, 'tointer': 'for the home records of all rows , most of them fuzzily match to philadelphia .', 'tostr': 'most_eq { all_rows ; home ; philadelphia } = true'} | most_eq { all_rows ; home ; philadelphia } = true | for the home records of all rows , most of them fuzzily match to philadelphia . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'home_3': 3, 'philadelphia_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'home_3': 'home', 'philadelphia_4': 'philadelphia'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'home_3': [0], 'philadelphia_4': [0]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'series'] | [['may 7', 'buffalo', '3 - 4', 'philadelphia', 'hextall', '17380', 'flyers lead 1 - 0'], ['may 8', 'buffalo', '1 - 3', 'philadelphia', 'hextall', '17380', 'flyers lead 2 - 0'], ['may 10', 'philadelphia', '1 - 3', 'buffalo', 'hextall', '13256', 'flyers lead 2 - 1'], ['may 12', 'philadelphia', '4 - 2', 'buffalo', 'hextall', '16230', 'flyers lead 3 - 1'], ['may 14', 'buffalo', '4 - 6', 'philadelphia', 'hextall', '17380', 'flyers win 4 - 1']] |
brian watts | https://en.wikipedia.org/wiki/Brian_Watts | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10167122-1.html.csv | unique | brian only has 1 top five finish and that is at the open championship . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'top - 5', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top - 5 record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; top - 5 ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; top - 5 ; 1 } }', 'tointer': 'select the rows whose top - 5 record is equal to 1 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'top - 5', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top - 5 record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; top - 5 ; 1 }'}, 'tournament'], 'result': 'the open championship', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; top - 5 ; 1 } ; tournament }'}, 'the open championship'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; top - 5 ; 1 } ; tournament } ; the open championship }', 'tointer': 'the tournament record of this unqiue row is the open championship .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; top - 5 ; 1 } } ; eq { hop { filter_eq { all_rows ; top - 5 ; 1 } ; tournament } ; the open championship } } = true', 'tointer': 'select the rows whose top - 5 record is equal to 1 . there is only one such row in the table . the tournament record of this unqiue row is the open championship .'} | and { only { filter_eq { all_rows ; top - 5 ; 1 } } ; eq { hop { filter_eq { all_rows ; top - 5 ; 1 } ; tournament } ; the open championship } } = true | select the rows whose top - 5 record is equal to 1 . there is only one such row in the table . the tournament record of this unqiue row is the open championship . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'top - 5_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'the open championship_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'top - 5_7': 'top - 5', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'the open championship_10': 'the open championship'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'top - 5_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'the open championship_10': [3]} | ['tournament', 'wins', 'top - 5', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '0', '0', '2', '1'], ['us open', '0', '0', '1', '2', '1'], ['the open championship', '0', '1', '2', '7', '4'], ['pga championship', '0', '0', '0', '6', '4'], ['totals', '0', '1', '3', '17', '10']] |
martin kaymer | https://en.wikipedia.org/wiki/Martin_Kaymer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12821159-8.html.csv | comparative | martin kaymer had a higher margin of victory in june of 2005 than he did on july 12 , 2006 . | {'row_1': '1', 'row_2': '5', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '14 jun 2005'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 14 jun 2005 .', 'tostr': 'filter_eq { all_rows ; date ; 14 jun 2005 }'}, 'margin of victory'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 14 jun 2005 } ; margin of victory }', 'tointer': 'select the rows whose date record fuzzily matches to 14 jun 2005 . take the margin of victory record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '12 jul 2006'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 12 jul 2006 .', 'tostr': 'filter_eq { all_rows ; date ; 12 jul 2006 }'}, 'margin of victory'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 12 jul 2006 } ; margin of victory }', 'tointer': 'select the rows whose date record fuzzily matches to 12 jul 2006 . take the margin of victory record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; 14 jun 2005 } ; margin of victory } ; hop { filter_eq { all_rows ; date ; 12 jul 2006 } ; margin of victory } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 14 jun 2005 . take the margin of victory record of this row . select the rows whose date record fuzzily matches to 12 jul 2006 . take the margin of victory record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; 14 jun 2005 } ; margin of victory } ; hop { filter_eq { all_rows ; date ; 12 jul 2006 } ; margin of victory } } = true | select the rows whose date record fuzzily matches to 14 jun 2005 . take the margin of victory record of this row . select the rows whose date record fuzzily matches to 12 jul 2006 . take the margin of victory record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '14 jun 2005_8': 8, 'margin of victory_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, '12 jul 2006_12': 12, 'margin of victory_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '14 jun 2005_8': '14 jun 2005', 'margin of victory_9': 'margin of victory', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '12 jul 2006_12': '12 jul 2006', 'margin of victory_13': 'margin of victory'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], '14 jun 2005_8': [0], 'margin of victory_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], '12 jul 2006_12': [1], 'margin of victory_13': [3]} | ['date', 'tournament', 'winning score', 'margin of victory', 'runner - up'] | [['14 jun 2005', 'central german classic ( as an amateur )', '- 19 ( 67 + 64 + 66 = 197 )', '5 strokes', 'wolfgang huget'], ['1 jun 2006', 'friedberg classic', '- 13 ( 70 + 64 + 69 = 203 )', '7 strokes', 'mark grabow schytter'], ['22 jun 2006', 'habsburg classic', '- 27 ( 68 + 59 + 62 = 189 )', '10 strokes', 'rick huiskamp'], ['4 jul 2006', 'coburg brose open', '- 12 ( 68 + 68 + 68 = 204 )', '4 strokes', 'lasse jensen'], ['12 jul 2006', 'winterbrock classic', '- 17 ( 68 + 60 + 71 = 199 )', '1 stroke', 'richard treis'], ['17 aug 2006', 'hockenberg classic', '- 17 ( 72 + 64 + 63 = 199 )', '7 strokes', 'christoph günther']] |
1966 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1966_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17277136-5.html.csv | comparative | in the 1996 u.s. open , tony lema had one less stroke than johnny miller . | {'row_1': '7', 'row_2': '10', 'col': '5', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'tony lema'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to tony lema .', 'tostr': 'filter_eq { all_rows ; player ; tony lema }'}, 'to par'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; tony lema } ; to par }', 'tointer': 'select the rows whose player record fuzzily matches to tony lema . take the to par record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'johnny miller ( a )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to johnny miller ( a ) .', 'tostr': 'filter_eq { all_rows ; player ; johnny miller ( a ) }'}, 'to par'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; johnny miller ( a ) } ; to par }', 'tointer': 'select the rows whose player record fuzzily matches to johnny miller ( a ) . take the to par record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; tony lema } ; to par } ; hop { filter_eq { all_rows ; player ; johnny miller ( a ) } ; to par } } = true', 'tointer': 'select the rows whose player record fuzzily matches to tony lema . take the to par record of this row . select the rows whose player record fuzzily matches to johnny miller ( a ) . take the to par record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; tony lema } ; to par } ; hop { filter_eq { all_rows ; player ; johnny miller ( a ) } ; to par } } = true | select the rows whose player record fuzzily matches to tony lema . take the to par record of this row . select the rows whose player record fuzzily matches to johnny miller ( a ) . take the to par 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, 'player_7': 7, 'tony lema_8': 8, 'to par_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'johnny miller (a)_12': 12, 'to par_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', 'player_7': 'player', 'tony lema_8': 'tony lema', 'to par_9': 'to par', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'johnny miller (a)_12': 'johnny miller ( a )', 'to par_13': 'to par'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'tony lema_8': [0], 'to par_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'johnny miller (a)_12': [1], 'to par_13': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'arnold palmer', 'united states', '71 + 66 + 70 = 207', '3'], ['2', 'billy casper', 'united states', '69 + 68 + 73 = 210', 'e'], ['3', 'jack nicklaus', 'united states', '71 + 71 + 69 = 211', '+ 1'], ['t4', 'phil rodgers', 'united states', '70 + 70 + 73 = 213', '+ 3'], ['t4', 'dave marr', 'united states', '71 + 74 + 68 = 213', '+ 3'], ['6', 'rives mcbee', 'united states', '76 + 64 + 74 = 214', '+ 2'], ['t7', 'tony lema', 'united states', '71 + 74 + 70 = 215', '+ 5'], ['t7', 'bob goalby', 'united states', '71 + 73 + 71 = 215', '+ 5'], ['t7', 'al mengert', 'united states', '67 + 77 + 71 = 215', '+ 5'], ['10', 'johnny miller ( a )', 'united states', '70 + 72 + 74 = 216', '+ 6']] |
2005 pba draft | https://en.wikipedia.org/wiki/2005_PBA_draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11779131-3.html.csv | count | two of the players picked were from the college known as ateneo . | {'scope': 'all', 'criterion': 'equal', 'value': 'ateneo', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'ateneo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to ateneo .', 'tostr': 'filter_eq { all_rows ; college ; ateneo }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; college ; ateneo } }', 'tointer': 'select the rows whose college record fuzzily matches to ateneo . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; college ; ateneo } } ; 2 } = true', 'tointer': 'select the rows whose college record fuzzily matches to ateneo . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; college ; ateneo } } ; 2 } = true | select the rows whose college record fuzzily matches to ateneo . 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, 'ateneo_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', 'ateneo_6': 'ateneo', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'college_5': [0], 'ateneo_6': [0], '2_7': [2]} | ['pick', 'player', 'country of origin', 'pba team', 'college'] | [['10', 'cesar catli', 'philippines', 'sta lucia realtors', 'feu'], ['11', 'neil raã ± eses', 'philippines', 'coca - cola tigers', 'uv'], ['12', 'al magpayo', 'philippines', 'coca - cola tigers', 'st benilde'], ['13', 'bj manalo', 'philippines', 'purefoods chunkee giants', 'de la salle'], ['14', 'larry fonacier', 'philippines', 'red bull barako', 'ateneo'], ['15', 'mark joseph kong', 'philippines', 'alaska aces', 'adamson'], ['16', 'rey mendoza', 'philippines', 'sta lucia realtors', 'nu'], ['17', 'paolo bugia', 'philippines', 'red bull barako', 'ateneo'], ['18', 'mark macapagal', 'philippines', "talk n ' text phone pals", 'san sebastian']] |
memphis grizzlies all - time roster | https://en.wikipedia.org/wiki/Memphis_Grizzlies_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16494599-1.html.csv | ordinal | ashray amaya wore the third highest number on the memphis grizzlies all - time roster . | {'row': '4', 'col': '2', 'order': '3', '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', 'no', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; no ; 3 }'}, 'player'], 'result': 'ashraf amaya', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; no ; 3 } ; player }'}, 'ashraf amaya'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; no ; 3 } ; player } ; ashraf amaya } = true', 'tointer': 'select the row whose no record of all rows is 3rd maximum . the player record of this row is ashraf amaya .'} | eq { hop { nth_argmax { all_rows ; no ; 3 } ; player } ; ashraf amaya } = true | select the row whose no record of all rows is 3rd maximum . the player record of this row is ashraf amaya . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'no_5': 5, '3_6': 6, 'player_7': 7, 'ashraf amaya_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', 'no_5': 'no', '3_6': '3', 'player_7': 'player', 'ashraf amaya_8': 'ashraf amaya'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'no_5': [0], '3_6': [0], 'player_7': [1], 'ashraf amaya_8': [2]} | ['player', 'no', 'nationality', 'position', 'years for grizzlies', 'school / club team'] | [['mahmoud abdul - rauf', '1', 'united states', 'point guard', '2000 - 2001', 'lsu'], ['shareef abdur - rahim', '3', 'united states', 'forward', '1996 - 2001', 'california'], ['tony allen', '9', 'united states', 'guard', '2010present', 'oklahoma state'], ['ashraf amaya', '18', 'united states', 'small forward', '1995 - 1996', 'southern illinois'], ['nick anderson', '5', 'united states', 'guard / forward', '2001 - 2002', 'illinois'], ['greg anthony', '2', 'united states', 'point guard', '1995 - 1997', 'unlv'], ['robert archibald', '21', 'scotland', 'forward / center', '2002 - 2003', 'illinois'], ['gilbert arenas', '10', 'united states', 'guard', '2012', 'arizona'], ['darrell arthur', '00', 'united states', 'forward', '2009 - 2013', 'kansas'], ['chucky atkins', "32 ( 3 in '06 - ' 07 )", 'united states', 'point guard', '2006 - 2007', 'south florida'], ['isaac austin', '9', 'united states', 'center', '2000 - 2002', 'arizona state']] |
united states house of representatives elections , 1960 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1960 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341897-6.html.csv | unique | arkansas 5 is the only district with given percentage ratios of the candidates . | {'scope': 'all', 'row': '5', 'col': '6', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': '%', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidates', '%'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record fuzzily matches to % .', 'tostr': 'filter_eq { all_rows ; candidates ; % }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; candidates ; % } }', 'tointer': 'select the rows whose candidates record fuzzily matches to % . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidates', '%'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record fuzzily matches to % .', 'tostr': 'filter_eq { all_rows ; candidates ; % }'}, 'district'], 'result': 'arkansas 5', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; candidates ; % } ; district }'}, 'arkansas 5'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; candidates ; % } ; district } ; arkansas 5 }', 'tointer': 'the district record of this unqiue row is arkansas 5 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; candidates ; % } } ; eq { hop { filter_eq { all_rows ; candidates ; % } ; district } ; arkansas 5 } } = true', 'tointer': 'select the rows whose candidates record fuzzily matches to % . there is only one such row in the table . the district record of this unqiue row is arkansas 5 .'} | and { only { filter_eq { all_rows ; candidates ; % } } ; eq { hop { filter_eq { all_rows ; candidates ; % } ; district } ; arkansas 5 } } = true | select the rows whose candidates record fuzzily matches to % . there is only one such row in the table . the district record of this unqiue row is arkansas 5 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'candidates_7': 7, '%_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'district_9': 9, 'arkansas 5_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'candidates_7': 'candidates', '%_8': '%', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'district_9': 'district', 'arkansas 5_10': 'arkansas 5'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'candidates_7': [0], '%_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'district_9': [2], 'arkansas 5_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['arkansas 1', 'ezekiel c gathings', 'democratic', '1938', 're - elected', 'ezekiel c gathings ( d ) unopposed'], ['arkansas 2', 'wilbur mills', 'democratic', '1938', 're - elected', 'wilbur mills ( d ) unopposed'], ['arkansas 3', 'james william trimble', 'democratic', '1944', 're - elected', 'james william trimble ( d ) unopposed'], ['arkansas 4', 'oren harris', 'democratic', '1940', 're - elected', 'oren harris ( d ) unopposed'], ['arkansas 5', 'dale alford', 'democratic', '1958', 're - elected', 'dale alford ( d ) 82.7 % l j churchill ( r ) 17.3 %']] |
hawthorne ( season 1 ) | https://en.wikipedia.org/wiki/Hawthorne_%28season_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30030227-1.html.csv | majority | six of the hawthorne episodes have more than 3 million viewers . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '3', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'viewers ( million )', '3'], 'result': True, 'ind': 0, 'tointer': 'for the viewers ( million ) records of all rows , most of them are greater than 3 .', 'tostr': 'most_greater { all_rows ; viewers ( million ) ; 3 } = true'} | most_greater { all_rows ; viewers ( million ) ; 3 } = true | for the viewers ( million ) records of all rows , most of them are greater than 3 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'viewers (million)_3': 3, '3_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'viewers (million)_3': 'viewers ( million )', '3_4': '3'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'viewers (million)_3': [0], '3_4': [0]} | ['series', 'title', 'directed by', 'written by', 'original air date', 'viewers ( million )'] | [['1', 'pilot', 'mikael salomon', 'john masius', 'june 16 , 2009', '3.82'], ['2', 'healing time', 'arvin brown', 'john masius', 'june 23 , 2009', '3.80'], ['3', 'yielding', 'jeff bleckner', 'sarah thorp', 'june 30 , 2009', 'n / a'], ['4', 'all the wrong places', 'andy wolk', 'glen mazzara', 'july 7 , 2009', 'n / a'], ['5', 'the sense of belonging', 'mike robe', 'anna c miller', 'july 14 , 2009', '3.21'], ['6', 'trust me', 'ed bianchi', 'jeff rake', 'july 21 , 2009', 'n / a'], ['7', 'night moves', 'roxann dawson', 'bill chais', 'july 28 , 2009', '3.61'], ['8', 'no guts , no glory', 'andy wolk', 'laurie arent', 'august 4 , 2009', '3.58'], ['9', "mother 's day", 'jeff bleckner', 'glen mazzara', 'august 11 , 2009', '3.35']] |
vk selver tallinn | https://en.wikipedia.org/wiki/VK_Selver_Tallinn | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25058562-2.html.csv | majority | for vk selver , most of the players are from the country of estonia . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'estonia', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'estonia'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to estonia .', 'tostr': 'most_eq { all_rows ; nationality ; estonia } = true'} | most_eq { all_rows ; nationality ; estonia } = true | for the nationality records of all rows , most of them fuzzily match to estonia . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'estonia_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'estonia_4': 'estonia'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'estonia_4': [0]} | ['shirt no', 'nationality', 'player', 'birth date', 'height', 'position'] | [['1', 'estonia', 'meelis kivisild', 'july 28 , 1990 ( age23 )', '199', 'middle blocker'], ['2', 'estonia', 'keiro vantsi', 'december 29 , 1993 ( age20 )', '191', 'setter'], ['3', 'estonia', 'martti keel', 'january 30 , 1992 ( age22 )', '188', 'setter'], ['4', 'estonia', 'timo tammemaa', 'november 18 , 1991 ( age22 )', '200', 'middle blocker'], ['5', 'estonia', 'argo meresaar ( c )', 'january 13 , 1980 ( age34 )', '206', 'opposite'], ['6', 'estonia', 'reimo rannar', 'january 30 , 1988 ( age26 )', '203', 'middle blocker'], ['7', 'estonia', 'kristjan ã uekallas', 'january 8 , 1981 ( age33 )', '193', 'spiker'], ['8', 'estonia', 'hindrek pulk', 'november 7 , 1990 ( age23 )', '193', 'opposite'], ['9', 'estonia', 'andri aganits', 'september 7 , 1993 ( age20 )', '207', 'middle blocker'], ['10', 'estonia', 'kaur koiduste', 'february 20 , 1994 ( age19 )', '190', 'spiker'], ['11', 'estonia', 'taavi sadam', 'july 4 , 1990 ( age23 )', '189', 'spiker'], ['12', 'latvia', 'andrejs baburovs', 'october 6 , 1987 ( age26 )', '192', 'spiker'], ['13', 'estonia', 'asko esna', 'may 1 , 1986 ( age27 )', '185', 'libero'], ['14', 'estonia', 'markus keel', 'august 18 , 1995 ( age18 )', '189', 'setter'], ['15', 'estonia', 'denis losnikov', 'february 25 , 1994 ( age19 )', '196', 'spiker']] |
adelaide united fc | https://en.wikipedia.org/wiki/Adelaide_United_FC | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1257184-2.html.csv | superlative | based on the statistics , dario vidošić was the most productive player for adelaide united fc . | {'scope': 'all', 'col_superlative': '4', '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', 'goals'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; goals }'}, 'player'], 'result': 'dario vidošić', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; goals } ; player }'}, 'dario vidošić'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; goals } ; player } ; dario vidošić } = true', 'tointer': 'select the row whose goals record of all rows is maximum . the player record of this row is dario vidošić .'} | eq { hop { argmax { all_rows ; goals } ; player } ; dario vidošić } = true | select the row whose goals record of all rows is maximum . the player record of this row is dario vidošić . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'goals_5': 5, 'player_6': 6, 'dario vidošić_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'goals_5': 'goals', 'player_6': 'player', 'dario vidošić_7': 'dario vidošić'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'goals_5': [0], 'player_6': [1], 'dario vidošić_7': [2]} | ['player', 'country', 'caps', 'goals', 'years active', 'years at club'] | [['eugene galeković', 'australia', '8', '( 0 )', '2009 -', '2007 -'], ['jonathan mckain', 'australia', '16', '( 0 )', '2004 -', '2011 -'], ['dario vidošić', 'australia', '18', '( 1 )', '2009 -', '2011 - 2013'], ['bruce djite', 'australia', '9', '( 0 )', '2008 -', '2006 - 2008 , 2011 -'], ['fabian barbiero', 'australia', '1', '( 0 )', '2009', '2007 - 2013']] |
pádraig harrington | https://en.wikipedia.org/wiki/P%C3%A1draig_Harrington | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1157761-9.html.csv | count | padraig harringtron had zero wins in two of the tournaments . | {'scope': 'all', 'criterion': 'equal', 'value': '0', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; wins ; 0 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; wins ; 0 } }', 'tointer': 'select the rows whose wins record is equal to 0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; wins ; 0 } } ; 2 } = true', 'tointer': 'select the rows whose wins record is equal to 0 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; wins ; 0 } } ; 2 } = true | select the rows whose wins record is equal to 0 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'wins_5': 5, '0_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'wins_5': 'wins', '0_6': '0', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'wins_5': [0], '0_6': [0], '2_7': [2]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '2', '4', '6', '14', '9'], ['us open', '0', '3', '5', '7', '16', '12'], ['the open championship', '2', '4', '4', '7', '17', '12'], ['pga championship', '1', '1', '2', '4', '14', '9'], ['totals', '3', '10', '15', '24', '61', '42']] |
lori chalupny | https://en.wikipedia.org/wiki/Lori_Chalupny | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12265902-2.html.csv | unique | lori chalupny 's second goal was the only goal that happened in virginia beach . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'virginia beach', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'virginia beach'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to virginia beach .', 'tostr': 'filter_eq { all_rows ; location ; virginia beach }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location ; virginia beach } }', 'tointer': 'select the rows whose location record fuzzily matches to virginia beach . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'virginia beach'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to virginia beach .', 'tostr': 'filter_eq { all_rows ; location ; virginia beach }'}, 'goal'], 'result': '2', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; virginia beach } ; goal }'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location ; virginia beach } ; goal } ; 2 }', 'tointer': 'the goal record of this unqiue row is 2 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location ; virginia beach } } ; eq { hop { filter_eq { all_rows ; location ; virginia beach } ; goal } ; 2 } } = true', 'tointer': 'select the rows whose location record fuzzily matches to virginia beach . there is only one such row in the table . the goal record of this unqiue row is 2 .'} | and { only { filter_eq { all_rows ; location ; virginia beach } } ; eq { hop { filter_eq { all_rows ; location ; virginia beach } ; goal } ; 2 } } = true | select the rows whose location record fuzzily matches to virginia beach . there is only one such row in the table . the goal record of this unqiue row is 2 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'virginia beach_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'goal_9': 9, '2_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location_7': 'location', 'virginia beach_8': 'virginia beach', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'goal_9': 'goal', '2_10': '2'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'virginia beach_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'goal_9': [2], '2_10': [3]} | ['goal', 'location', 'lineup', 'assist / pass', 'score', 'result', 'competition'] | [['1', 'usa albuquerque nm', "on 70 ' ( off lilly )", 'tarpley', '3 - 0', '3 - 0', 'friendly'], ['2', 'usa virginia beach', '90 . start', 'unassisted', '1 - 0', '2 - 0', 'friendly'], ['3', 'chn guangzhou', '90 . start', 'unassisted', '1 - 0', '2 - 0', 'four nations tournament'], ['4', 'usa frisco tx', "off 72 ' ( on wagner )", 'tarpley', '3 - 1', '6 - 2', 'friendly'], ['5', 'chn shanghai', '90 . start', 'wambach', '1 - 0', '1 - 0', 'world cup group b'], ['6', 'chn shanghai', '90 . start', 'unassisted', '3 - 0', '4 - 1', 'world cup final - third place playoff'], ['7', 'chn beijing', '90 . start', 'rodriguez', '2 - 1', '4 - 2', 'olympics tournament'], ['8', 'usa bridgeview il', '90 . start', 'tarpley', '1 - 0', '2 - 0', 'friendly']] |
volleyball at the 2008 summer olympics - men 's team rosters | https://en.wikipedia.org/wiki/Volleyball_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_team_rosters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18499677-2.html.csv | count | two of the players on the 2008 summer olympic volelyball team came from the henan club . | {'scope': 'all', 'criterion': 'equal', 'value': 'henan', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2008 club', 'henan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2008 club record fuzzily matches to henan .', 'tostr': 'filter_eq { all_rows ; 2008 club ; henan }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; 2008 club ; henan } }', 'tointer': 'select the rows whose 2008 club record fuzzily matches to henan . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; 2008 club ; henan } } ; 2 } = true', 'tointer': 'select the rows whose 2008 club record fuzzily matches to henan . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; 2008 club ; henan } } ; 2 } = true | select the rows whose 2008 club record fuzzily matches to henan . 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, '2008 club_5': 5, 'henan_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', '2008 club_5': '2008 club', 'henan_6': 'henan', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], '2008 club_5': [0], 'henan_6': [0], '2_7': [2]} | ['name', 'height', 'weight', 'spike', '2008 club'] | [['bian hongmin', 'm', '-', 'cm ( in )', 'zhejiang'], ['yuan zhi', 'm', '-', 'cm ( in )', 'liaoning'], ['guo peng', 'm', '-', 'cm ( in )', 'army'], ['shi hairong', 'm', '-', 'cm ( in )', 'jiangsu'], ['cui jianjun', 'm', '-', 'cm ( in )', 'henan'], ['jiao shuai', 'm', '-', 'cm ( in )', 'henan'], ['yu dawei', 'm', '-', 'cm ( in )', 'shangdong'], ['shen qiong', 'm', '-', 'cm ( in )', 'shanghai'], ['jiang fudong', 'm', '-', 'cm ( in )', 'sichuan'], ['ren qi', 'm', '-', 'cm ( in )', 'shanghai'], ['sui shengsheng', 'm', '-', 'cm ( in )', 'liaoning'], ['fang yingchao', 'm', '-', 'cm ( in )', 'shanghai']] |
john mcenroe career statistics | https://en.wikipedia.org/wiki/John_McEnroe_career_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22597626-17.html.csv | majority | john mcenroe has won most of his appearances in legends over 45 doubles championship finals . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'winner', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'outcome', 'winner'], 'result': True, 'ind': 0, 'tointer': 'for the outcome records of all rows , most of them fuzzily match to winner .', 'tostr': 'most_eq { all_rows ; outcome ; winner } = true'} | most_eq { all_rows ; outcome ; winner } = true | for the outcome records of all rows , most of them fuzzily match to winner . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'outcome_3': 3, 'winner_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'outcome_3': 'outcome', 'winner_4': 'winner'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'outcome_3': [0], 'winner_4': [0]} | ['outcome', 'year', 'championship', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['winner', '2007', 'french open', 'clay', 'järryd', 'fitzgerald vilas', '6 - 1 , 6 - 2'], ['winner', '2008', 'french open', 'clay', 'järryd', 'bahrami leconte', '6 - 4 , 7 - 6 2'], ['winner', '2009', 'french open', 'clay', 'järryd', 'bahrami leconte', '7 - 6 2 , 6 - 1'], ['winner', '2010', 'french open', 'clay', 'gómez', 'bahrami leconte', '6 - 1 , 6 - 1'], ['runner - up', '2011', 'french open', 'clay', 'gómez', 'forget leconte', '6 - 3 , 5 - 7 ,']] |
list of ra - aus certified aircraft types | https://en.wikipedia.org/wiki/List_of_RA-Aus_certified_aircraft_types | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17699890-1.html.csv | unique | pipistrel manufactures the only short wing aus certified aircraft types . | {'scope': 'all', 'row': '11', 'col': '2', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'short wing', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', 'short wing'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose model record fuzzily matches to short wing .', 'tostr': 'filter_eq { all_rows ; model ; short wing }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; model ; short wing } }', 'tointer': 'select the rows whose model record fuzzily matches to short wing . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', 'short wing'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose model record fuzzily matches to short wing .', 'tostr': 'filter_eq { all_rows ; model ; short wing }'}, 'manufacturer'], 'result': 'pipistrel', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; model ; short wing } ; manufacturer }'}, 'pipistrel'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; model ; short wing } ; manufacturer } ; pipistrel }', 'tointer': 'the manufacturer record of this unqiue row is pipistrel .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; model ; short wing } } ; eq { hop { filter_eq { all_rows ; model ; short wing } ; manufacturer } ; pipistrel } } = true', 'tointer': 'select the rows whose model record fuzzily matches to short wing . there is only one such row in the table . the manufacturer record of this unqiue row is pipistrel .'} | and { only { filter_eq { all_rows ; model ; short wing } } ; eq { hop { filter_eq { all_rows ; model ; short wing } ; manufacturer } ; pipistrel } } = true | select the rows whose model record fuzzily matches to short wing . there is only one such row in the table . the manufacturer record of this unqiue row is pipistrel . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'model_7': 7, 'short wing_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'manufacturer_9': 9, 'pipistrel_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'model_7': 'model', 'short wing_8': 'short wing', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'manufacturer_9': 'manufacturer', 'pipistrel_10': 'pipistrel'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'model_7': [0], 'short wing_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'manufacturer_9': [2], 'pipistrel_10': [3]} | ['manufacturer', 'model', 'kit / factory', 'wing', 'seats'] | [['aeroprakt', 'a - 22 foxbat', 'factory', 'high wing', '2'], ['allegro', 'allegro 2000 and allegro 2007', 'approved kit and factory built', 'high wing', '2'], ['evektor', 'sportstar', 'factory', 'low', '2'], ['jabiru', 'j120', 'factory', 'high', '2'], ['jabiru', 'j160', 'both', 'high', '2'], ['jabiru', 'j170', 'both', 'high', '2'], ['jabiru', 'j230', 'both', 'high', '2'], ['jabiru', 'j250', 'kit', 'high', '2'], ['jabiru', 'ul - d', 'kit', 'high', '2'], ['pipistrel', 'sinus', 'factory & kit built approved', 'high wing', '2'], ['pipistrel', 'virus - virus sw ( short wing )', 'factory & kit built approved', 'high wing', '2'], ['savage classic , savage cruiser , savage cub', 'cub', 'factory & kit built approved', 'high wing', '2'], ['tl 2000 sting carbon', 'sting', 'approved factory built', 'low wing', '2'], ['raj hamsa ultralights', 'x - air hanuman', 'approved kit or lsa', 'high wing', '2'], ['x - air standard', 'x - air standard', 'approved kit', 'high wing', '2']] |
1978 vfl season | https://en.wikipedia.org/wiki/1978_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10887680-10.html.csv | ordinal | vfl park venue recorded the highest crowd participation during the 1978 season . | {'row': '6', 'col': '6', 'order': '1', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'vfl park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'vfl park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; vfl park } = true', 'tointer': 'select the row whose crowd record of all rows is 1st maximum . the venue record of this row is vfl park .'} | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; vfl park } = true | select the row whose crowd record of all rows is 1st maximum . the venue record of this row is vfl park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'vfl park_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '1_6': '1', 'venue_7': 'venue', 'vfl park_8': 'vfl park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'vfl park_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '12.24 ( 96 )', 'geelong', '8.13 ( 61 )', 'princes park', '11066', '3 june 1978'], ['richmond', '12.14 ( 86 )', 'fitzroy', '11.14 ( 80 )', 'mcg', '21122', '3 june 1978'], ['north melbourne', '13.7 ( 85 )', 'essendon', '12.10 ( 82 )', 'arden street oval', '28828', '3 june 1978'], ['south melbourne', '24.18 ( 162 )', 'melbourne', '14.8 ( 92 )', 'lake oval', '15738', '5 june 1978'], ['footscray', '19.11 ( 125 )', 'carlton', '15.14 ( 104 )', 'western oval', '30197', '5 june 1978'], ['collingwood', '18.23 ( 131 )', 'st kilda', '14.13 ( 97 )', 'vfl park', '72669', '5 june 1978']] |
list of tallest buildings in the european union | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_the_European_Union | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10728418-4.html.csv | unique | the shard is the only building in the eu over 300 metres tall . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'greater_than', 'value': '300', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'metres', '300'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose metres record is greater than 300 .', 'tostr': 'filter_greater { all_rows ; metres ; 300 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; metres ; 300 } }', 'tointer': 'select the rows whose metres record is greater than 300 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'metres', '300'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose metres record is greater than 300 .', 'tostr': 'filter_greater { all_rows ; metres ; 300 }'}, 'name'], 'result': 'the shard', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; metres ; 300 } ; name }'}, 'the shard'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; metres ; 300 } ; name } ; the shard }', 'tointer': 'the name record of this unqiue row is the shard .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; metres ; 300 } } ; eq { hop { filter_greater { all_rows ; metres ; 300 } ; name } ; the shard } } = true', 'tointer': 'select the rows whose metres record is greater than 300 . there is only one such row in the table . the name record of this unqiue row is the shard .'} | and { only { filter_greater { all_rows ; metres ; 300 } } ; eq { hop { filter_greater { all_rows ; metres ; 300 } ; name } ; the shard } } = true | select the rows whose metres record is greater than 300 . there is only one such row in the table . the name record of this unqiue row is the shard . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'metres_7': 7, '300_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'the shard_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'metres_7': 'metres', '300_8': '300', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'the shard_10': 'the shard'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'metres_7': [0], '300_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'the shard_10': [3]} | ['name', 'city', 'years as tallest', 'metres', 'feet', 'floors'] | [['the shard', 'london', '2011 - present', '306', '1004', '87'], ['commerzbank tower', 'frankfurt', '1997 - 2011', '259', '850', '56'], ['messeturm', 'frankfurt', '1990 - 1997', '257', '843', '55'], ['tour montparnasse', 'paris', '1972 - 1990', '210', '689', '59'], ['tour du midi / zuidertoren', 'brussels', '1966 - 1972', '150', '492', '38'], ['pirelli tower', 'milan', '1958 - 1966', '127', '417', '32'], ['torre breda', 'milan', '1957 - 1958', '117', '384', '30']] |
just a closer walk with thee ( album ) | https://en.wikipedia.org/wiki/Just_a_Closer_Walk_with_Thee_%28album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13536392-2.html.csv | unique | on the album just a closer walk with thee , only the song swing low , sweet chariot has the writer wallis willis . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'wallis willis', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'songwriter ( s )', 'wallis willis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose songwriter ( s ) record fuzzily matches to wallis willis .', 'tostr': 'filter_eq { all_rows ; songwriter ( s ) ; wallis willis }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; songwriter ( s ) ; wallis willis } }', 'tointer': 'select the rows whose songwriter ( s ) record fuzzily matches to wallis willis . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'songwriter ( s )', 'wallis willis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose songwriter ( s ) record fuzzily matches to wallis willis .', 'tostr': 'filter_eq { all_rows ; songwriter ( s ) ; wallis willis }'}, 'title'], 'result': 'swing low , sweet chariot', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; songwriter ( s ) ; wallis willis } ; title }'}, 'swing low , sweet chariot'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; songwriter ( s ) ; wallis willis } ; title } ; swing low , sweet chariot }', 'tointer': 'the title record of this unqiue row is swing low , sweet chariot .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; songwriter ( s ) ; wallis willis } } ; eq { hop { filter_eq { all_rows ; songwriter ( s ) ; wallis willis } ; title } ; swing low , sweet chariot } } = true', 'tointer': 'select the rows whose songwriter ( s ) record fuzzily matches to wallis willis . there is only one such row in the table . the title record of this unqiue row is swing low , sweet chariot .'} | and { only { filter_eq { all_rows ; songwriter ( s ) ; wallis willis } } ; eq { hop { filter_eq { all_rows ; songwriter ( s ) ; wallis willis } ; title } ; swing low , sweet chariot } } = true | select the rows whose songwriter ( s ) record fuzzily matches to wallis willis . there is only one such row in the table . the title record of this unqiue row is swing low , sweet chariot . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'songwriter (s)_7': 7, 'wallis willis_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'swing low , sweet chariot_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'songwriter (s)_7': 'songwriter ( s )', 'wallis willis_8': 'wallis willis', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'swing low , sweet chariot_10': 'swing low , sweet chariot'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'songwriter (s)_7': [0], 'wallis willis_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'swing low , sweet chariot_10': [3]} | ['track number', 'title', 'songwriter ( s )', 'recording date', 'time'] | [['1', 'swing low , sweet chariot', 'wallis willis ( adapted by malcolm dodds )', 'november 13 , 1959', '3:15'], ['2', 'steal away', '( adapted by malcolm dodds )', 'november 13 , 1959', '3:15'], ['3', 'little david', '( adapted by malcolm dodds )', 'january 28 , 1960', '2:20'], ['4', 'nobody knows', '( adapted by malcolm dodds )', 'november 13 , 1959', '3:10'], ['5', "i could n't hear nobody pray", '( adapted by malcolm dodds )', 'november 16 , 1959', '2:55'], ['6', 'motherless child', 'traditional ( adapted by malcolm dodds )', 'november 13 , 1959', '2:48'], ['7', 'just a closer walk with thee', 'stuart hine ( adapted by malcolm dodds )', 'november 16 , 1959', '3:30'], ['8', "my lord what a mornin '", 'h t burleigh ( adapted by malcolm dodds )', 'january 28 , 1960', '2:30'], ['9', "great getting up mornin '", '( adapted by malcolm dodds )', 'january 28 , 1960', '3:25'], ['10', 'were you there', '( adapted by malcolm dodds )', 'november 16 , 1959', '3:23'], ['11', 'break bread', '( adapted by malcolm dodds )', 'november 16 , 1959', '3:25'], ['12', 'me ! oh lord', '( adapted by malcolm dodds )', 'november 13 , 1959', '2:10']] |
agriculture in australia | https://en.wikipedia.org/wiki/Agriculture_in_Australia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1057262-1.html.csv | unique | of these commodities , only cattle had a quantity of 5849 in 2002-2003 . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '5849', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', '2002 - 03', '5849'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2002 - 03 record is equal to 5849 .', 'tostr': 'filter_eq { all_rows ; 2002 - 03 ; 5849 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; 2002 - 03 ; 5849 } }', 'tointer': 'select the rows whose 2002 - 03 record is equal to 5849 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', '2002 - 03', '5849'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2002 - 03 record is equal to 5849 .', 'tostr': 'filter_eq { all_rows ; 2002 - 03 ; 5849 }'}, 'commodity'], 'result': 'cattle and calves', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; 2002 - 03 ; 5849 } ; commodity }'}, 'cattle and calves'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; 2002 - 03 ; 5849 } ; commodity } ; cattle and calves }', 'tointer': 'the commodity record of this unqiue row is cattle and calves .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; 2002 - 03 ; 5849 } } ; eq { hop { filter_eq { all_rows ; 2002 - 03 ; 5849 } ; commodity } ; cattle and calves } } = true', 'tointer': 'select the rows whose 2002 - 03 record is equal to 5849 . there is only one such row in the table . the commodity record of this unqiue row is cattle and calves .'} | and { only { filter_eq { all_rows ; 2002 - 03 ; 5849 } } ; eq { hop { filter_eq { all_rows ; 2002 - 03 ; 5849 } ; commodity } ; cattle and calves } } = true | select the rows whose 2002 - 03 record is equal to 5849 . there is only one such row in the table . the commodity record of this unqiue row is cattle and calves . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, '2002 - 03_7': 7, '5849_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'commodity_9': 9, 'cattle and calves_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', '2002 - 03_7': '2002 - 03', '5849_8': '5849', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'commodity_9': 'commodity', 'cattle and calves_10': 'cattle and calves'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], '2002 - 03_7': [0], '5849_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'commodity_9': [2], 'cattle and calves_10': [3]} | ['commodity', '2001 - 02', '2002 - 03', '2003 - 04', '2004 - 05', '2005 - 06', '2006 - 07'] | [['cattle and calves', '6617', '5849', '6345', '7331', '7082', '6517'], ['wheat', '6356', '2692', '5636', '4320', '5905', '6026'], ['milk', '3717', '2795', '2808', '3194', '3268', '3245'], ['fruit and nuts', '2333', '2408', '2350', '2640', '2795', '2915'], ['s vegetable', '2269', '2126', '2356', '2490', '2601', '2715'], ['wool', '2713', '3318', '2397', '2196', '2187', '2138'], ['barley', '1725', '984', '1750', '1240', '1744', '1624'], ['poultry', '1175', '1273', '1264', '1358', '1416', '1461'], ['s lamb', '1181', '1161', '1318', '1327', '1425', '1348'], ['sugar cane', '989', '1019', '854', '968', '1037', '1208']] |
türk telekom arena | https://en.wikipedia.org/wiki/T%C3%BCrk_Telekom_Arena | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12243387-4.html.csv | superlative | friendly game that drew the highest attendance to türk telekom arena occurred on 14 november 2012 . | {'scope': 'subset', 'col_superlative': '7', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,6', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'friendly'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'round', 'friendly'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; round ; friendly }', 'tointer': 'select the rows whose round record fuzzily matches to friendly .'}, 'spectators'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; round ; friendly } ; spectators }'}, 'date'], 'result': '14 november 2012', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; round ; friendly } ; spectators } ; date }'}, '14 november 2012'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; round ; friendly } ; spectators } ; date } ; 14 november 2012 } = true', 'tointer': 'select the rows whose round record fuzzily matches to friendly . select the row whose spectators record of these rows is maximum . the date record of this row is 14 november 2012 .'} | eq { hop { argmax { filter_eq { all_rows ; round ; friendly } ; spectators } ; date } ; 14 november 2012 } = true | select the rows whose round record fuzzily matches to friendly . select the row whose spectators record of these rows is maximum . the date record of this row is 14 november 2012 . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'round_6': 6, 'friendly_7': 7, 'spectators_8': 8, 'date_9': 9, '14 november 2012_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'round_6': 'round', 'friendly_7': 'friendly', 'spectators_8': 'spectators', 'date_9': 'date', '14 november 2012_10': '14 november 2012'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'round_6': [0], 'friendly_7': [0], 'spectators_8': [1], 'date_9': [2], '14 november 2012_10': [3]} | ['date', 'time ( cest )', 'team 1', 'res', 'team 2', 'round', 'spectators'] | [['10 august 2011', '20.30', 'turkey', '3 - 0', 'estonia', 'friendly', '25000'], ['2 september 2011', '19.00', 'turkey', '2 - 1', 'kazakhstan', 'euro 2012 qualifying', '47756'], ['7 october 2011', '20.30', 'turkey', '1 - 3', 'germany', 'euro 2012 qualifying', '49532'], ['11 october 2011', '19.00', 'turkey', '1 - 0', 'azerbaijan', 'euro 2012 qualifying', '32174'], ['11 november 2011', '20.05', 'turkey', '0 - 3', 'croatia', 'euro 2012 qualifying', '42863'], ['14 november 2012', '20.30', 'turkey', '1 - 1', 'denmark', 'friendly', '30000']] |
weightlifting at the 1999 pan american games | https://en.wikipedia.org/wiki/Weightlifting_at_the_1999_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11279593-11.html.csv | unique | out of all the competitors , only maryse turcotte was able to clean & jerk over 110 kg . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'greater_than', 'value': '110', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'clean & jerk', '110'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose clean & jerk record is greater than 110 .', 'tostr': 'filter_greater { all_rows ; clean & jerk ; 110 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; clean & jerk ; 110 } }', 'tointer': 'select the rows whose clean & jerk record is greater than 110 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'clean & jerk', '110'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose clean & jerk record is greater than 110 .', 'tostr': 'filter_greater { all_rows ; clean & jerk ; 110 }'}, 'name'], 'result': 'maryse turcotte ( can )', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; clean & jerk ; 110 } ; name }'}, 'maryse turcotte ( can )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; clean & jerk ; 110 } ; name } ; maryse turcotte ( can ) }', 'tointer': 'the name record of this unqiue row is maryse turcotte ( can ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; clean & jerk ; 110 } } ; eq { hop { filter_greater { all_rows ; clean & jerk ; 110 } ; name } ; maryse turcotte ( can ) } } = true', 'tointer': 'select the rows whose clean & jerk record is greater than 110 . there is only one such row in the table . the name record of this unqiue row is maryse turcotte ( can ) .'} | and { only { filter_greater { all_rows ; clean & jerk ; 110 } } ; eq { hop { filter_greater { all_rows ; clean & jerk ; 110 } ; name } ; maryse turcotte ( can ) } } = true | select the rows whose clean & jerk record is greater than 110 . there is only one such row in the table . the name record of this unqiue row is maryse turcotte ( can ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'clean & jerk_7': 7, '110_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'maryse turcotte ( can )_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'clean & jerk_7': 'clean & jerk', '110_8': '110', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'maryse turcotte ( can )_10': 'maryse turcotte ( can )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'clean & jerk_7': [0], '110_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'maryse turcotte ( can )_10': [3]} | ['name', 'bodyweight', 'snatch', 'clean & jerk', 'total ( kg )'] | [['maryse turcotte ( can )', '57.56', '87.5', '112.5', '200.0'], ['nancy niro ( can )', '57.92', '87.5', '105.0', '192.5'], ['soraya jiménez ( mex )', '57.19', '85.0', '105.0', '190.0'], ['ruth rivera ( pur )', '57.56', '67.5', '95.0', '162.5'], ['patricia sosa ( esa )', '57.41', '67.5', '92.5', '160.0'], ['liliana garcía ( ven )', '57.32', '80.0', '105.0', '-']] |
1957 vfl season | https://en.wikipedia.org/wiki/1957_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10774891-1.html.csv | aggregation | the average attendance for venues during the 1957 vfl season was around 28861 people . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '28861', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '28861', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '28861'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 28861 } = true', 'tointer': 'the average of the crowd record of all rows is 28861 .'} | round_eq { avg { all_rows ; crowd } ; 28861 } = true | the average of the crowd record of all rows is 28861 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '28861_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '28861_5': '28861'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '28861_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '12.16 ( 88 )', 'south melbourne', '7.17 ( 59 )', 'junction oval', '37000', '20 april 1957'], ['collingwood', '8.10 ( 58 )', 'essendon', '13.15 ( 93 )', 'victoria park', '30000', '20 april 1957'], ['carlton', '10.6 ( 66 )', 'hawthorn', '15.12 ( 102 )', 'princes park', '24321', '20 april 1957'], ['fitzroy', '7.11 ( 53 )', 'melbourne', '6.14 ( 50 )', 'brunswick street oval', '24000', '22 april 1957'], ['richmond', '19.14 ( 128 )', 'north melbourne', '15.15 ( 105 )', 'punt road oval', '23000', '22 april 1957'], ['geelong', '11.11 ( 77 )', 'footscray', '10.17 ( 77 )', 'kardinia park', '34844', '22 april 1957']] |
rajgarh ( lok sabha constituency ) | https://en.wikipedia.org/wiki/Rajgarh_%28Lok_Sabha_constituency%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18517323-1.html.csv | ordinal | susner has the second highest number of electorates in the rajgarh ( lok sabha constituency ) . | {'row': '8', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'number of electorates ( 2009 )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; number of electorates ( 2009 ) ; 2 }'}, 'name'], 'result': 'susner', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; number of electorates ( 2009 ) ; 2 } ; name }'}, 'susner'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; number of electorates ( 2009 ) ; 2 } ; name } ; susner } = true', 'tointer': 'select the row whose number of electorates ( 2009 ) record of all rows is 2nd maximum . the name record of this row is susner .'} | eq { hop { nth_argmax { all_rows ; number of electorates ( 2009 ) ; 2 } ; name } ; susner } = true | select the row whose number of electorates ( 2009 ) record of all rows is 2nd maximum . the name record of this row is susner . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'number of electorates (2009)_5': 5, '2_6': 6, 'name_7': 7, 'susner_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', 'number of electorates (2009)_5': 'number of electorates ( 2009 )', '2_6': '2', 'name_7': 'name', 'susner_8': 'susner'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'number of electorates (2009)_5': [0], '2_6': [0], 'name_7': [1], 'susner_8': [2]} | ['constituency number', 'name', 'reserved for ( sc / st / none )', 'district', 'number of electorates ( 2009 )'] | [['30', 'chachoura', 'none', 'guna', '149857'], ['31', 'raghogarh', 'none', 'guna', '146874'], ['160', 'narsinghgarh', 'none', 'rajgarh', '162429'], ['161', 'biaora', 'none', 'rajgarh', '162340'], ['162', 'rajgarh', 'none', 'rajgarh', '161219'], ['163', 'khilchipur', 'none', 'rajgarh', '169412'], ['164', 'sarangpur', 'sc', 'rajgarh', '140001'], ['165', 'susner', 'none', 'shajapur', '169378']] |
acc - big ten challenge | https://en.wikipedia.org/wiki/ACC%E2%80%93Big_Ten_Challenge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1672976-6.html.csv | unique | nc state is the only acc team to play at kohl center madison , wi . | {'scope': 'all', 'row': '8', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'kohl center madison , wi', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'kohl center madison , wi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to kohl center madison , wi .', 'tostr': 'filter_eq { all_rows ; location ; kohl center madison , wi }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location ; kohl center madison , wi } }', 'tointer': 'select the rows whose location record fuzzily matches to kohl center madison , wi . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'kohl center madison , wi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to kohl center madison , wi .', 'tostr': 'filter_eq { all_rows ; location ; kohl center madison , wi }'}, 'acc team'], 'result': 'nc state', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; kohl center madison , wi } ; acc team }'}, 'nc state'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location ; kohl center madison , wi } ; acc team } ; nc state }', 'tointer': 'the acc team record of this unqiue row is nc state .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location ; kohl center madison , wi } } ; eq { hop { filter_eq { all_rows ; location ; kohl center madison , wi } ; acc team } ; nc state } } = true', 'tointer': 'select the rows whose location record fuzzily matches to kohl center madison , wi . there is only one such row in the table . the acc team record of this unqiue row is nc state .'} | and { only { filter_eq { all_rows ; location ; kohl center madison , wi } } ; eq { hop { filter_eq { all_rows ; location ; kohl center madison , wi } ; acc team } ; nc state } } = true | select the rows whose location record fuzzily matches to kohl center madison , wi . there is only one such row in the table . the acc team record of this unqiue row is nc state . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'kohl center madison , wi_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'acc team_9': 9, 'nc state_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location_7': 'location', 'kohl center madison , wi_8': 'kohl center madison , wi', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'acc team_9': 'acc team', 'nc state_10': 'nc state'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'kohl center madison , wi_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'acc team_9': [2], 'nc state_10': [3]} | ['date', 'time', 'acc team', 'big ten team', 'location', 'television', 'attendance', 'winner', 'challenge leader'] | [['mon , nov 29', '7:00 pm', 'virginia', '13 minnesota', 'williams arena minneapolis , mn', 'espn2', '12089', 'virginia ( 87 - 79 )', 'acc ( 1 - 0 )'], ['tue , nov 30', '7:00 pm', 'wake forest', 'iowa', 'ljvm coliseum winston - salem , nc', 'espnu', '9086', 'wake forest ( 76 - 73 )', 'acc ( 2 - 0 )'], ['tue , nov 30', '7:00 pm', 'georgia tech', 'northwestern', 'welsh - ryan arena evanston , il', 'espn2', '4455', 'northwestern ( 91 - 71 )', 'acc ( 2 - 1 )'], ['tue , nov 30', '7:30 pm', 'florida state', '2 ohio state', 'donald l tucker center tallahassee , fl', 'espn', '10457', 'ohio state ( 58 - 44 )', 'tied ( 2 - 2 )'], ['tue , nov 30', '9:00 pm', 'clemson', 'michigan', 'littlejohn coliseum clemson , sc', 'espn2', '7237', 'michigan ( 69 - 61 )', 'big ten ( 3 - 2 )'], ['tue , nov 30', '9:30 pm', 'north carolina', '21 illinois', 'assembly hall champaign , il', 'espn', '16618', 'illinois ( 79 - 67 )', 'big ten ( 4 - 2 )'], ['wed , dec 1', '7:15 pm', 'boston college', 'indiana', 'conte forum chestnut hill , ma', 'espnu', '5329', 'boston college ( 88 - 76 )', 'big ten ( 4 - 3 )'], ['wed , dec 1', '7:15 pm', 'nc state', 'wisconsin', 'kohl center madison , wi', 'espn2', '17230', 'wisconsin ( 87 - 48 )', 'big ten ( 5 - 3 )'], ['wed , dec 1', '7:30 pm', 'virginia tech', '18 purdue', 'cassell coliseum blacksburg , va', 'espn', '9847', 'purdue ( 58 - 55 ot )', 'big ten ( 6 - 3 )'], ['wed , dec 1', '9:15 pm', 'maryland', 'penn state', 'bryce jordan center university park , pa', 'espn2', '9078', 'maryland ( 62 - 39 )', 'big ten ( 6 - 4 )']] |
1985 - 86 houston rockets season | https://en.wikipedia.org/wiki/1985%E2%80%9386_Houston_Rockets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17383484-1.html.csv | ordinal | in the 1985-86 houston rockets season , their first draft from mercer was sam mitchell . | {'scope': 'subset', 'row': '2', 'col': '2', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'mercer'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'mercer'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; college ; mercer }', 'tointer': 'select the rows whose college record fuzzily matches to mercer .'}, 'pick', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; college ; mercer } ; pick ; 1 }'}, 'player'], 'result': 'sam mitchell', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; college ; mercer } ; pick ; 1 } ; player }'}, 'sam mitchell'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; college ; mercer } ; pick ; 1 } ; player } ; sam mitchell } = true', 'tointer': 'select the rows whose college record fuzzily matches to mercer . select the row whose pick record of these rows is 1st minimum . the player record of this row is sam mitchell .'} | eq { hop { nth_argmin { filter_eq { all_rows ; college ; mercer } ; pick ; 1 } ; player } ; sam mitchell } = true | select the rows whose college record fuzzily matches to mercer . select the row whose pick record of these rows is 1st minimum . the player record of this row is sam mitchell . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'college_6': 6, 'mercer_7': 7, 'pick_8': 8, '1_9': 9, 'player_10': 10, 'sam mitchell_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'college_6': 'college', 'mercer_7': 'mercer', 'pick_8': 'pick', '1_9': '1', 'player_10': 'player', 'sam mitchell_11': 'sam mitchell'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'college_6': [0], 'mercer_7': [0], 'pick_8': [1], '1_9': [1], 'player_10': [2], 'sam mitchell_11': [3]} | ['round', 'pick', 'player', 'nationality', 'college'] | [['1', '19', 'steve harris', 'united states', 'tulsa'], ['3', '54', 'sam mitchell', 'united states', 'mercer'], ['3', '57', 'michael payne', 'united states', 'iowa'], ['4', '88', 'mike brooks', 'united states', 'tennessee'], ['6', '134', 'sam potter', 'united states', 'oral roberts']] |
kuala lumpur fa season 2005 | https://en.wikipedia.org/wiki/Kuala_Lumpur_FA_season_2005 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15192848-6.html.csv | count | there are two people who won 7 league matches in the kuala lumpur fa 2005 season . | {'scope': 'all', 'criterion': 'equal', 'value': '7', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'league', '7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose league record is equal to 7 .', 'tostr': 'filter_eq { all_rows ; league ; 7 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; league ; 7 } }', 'tointer': 'select the rows whose league record is equal to 7 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; league ; 7 } } ; 2 } = true', 'tointer': 'select the rows whose league record is equal to 7 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; league ; 7 } } ; 2 } = true | select the rows whose league record is equal to 7 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'league_5': 5, '7_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'league_5': 'league', '7_6': '7', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'league_5': [0], '7_6': [0], '2_7': [2]} | ['player', 'league', 'malaysia cup', 'fa cup', 'total'] | [['safee sali', '7', '1', '3', '11'], ['carlos augusto quinonez', '7', '1', '2', '10'], ['zamri hassan', '4', '0', '2', '6'], ['s sunder', '5', '0', '0', '5'], ['kamsi joel', '2', '0', '3', '5'], ['shariful hisham ibrahim', '3', '1', '0', '4'], ['sanjos sundawat', '1', '2', '0', '3'], ['k kumaran', '1', '1', '1', '3'], ['azlan hussain', '2', '0', '0', '2'], ['v saysupelan', '1', '0', '1', '2'], ['hector federico carballo', '0', '1', '1', '2'], ['reeshafiq alwi', '1', '0', '0', '1'], ['gasili pengalot', '0', '0', '0', '0'], ['faizal desa', '0', '0', '0', '0'], ['syahman zainuddin', '0', '0', '0', '0'], ['zaki tumpang ( gk )', '0', '0', '0', '0'], ['m patrick maria', '0', '0', '0', '0'], ['saiful amar sudar ( gk )', '0', '0', '0', '0'], ['zulkifli derus', '0', '0', '0', '0']] |
1970 isle of man tt | https://en.wikipedia.org/wiki/1970_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10301911-8.html.csv | ordinal | maico machine has the second highest points in the 1970 isle of man tt . | {'row': '2', 'col': '7', 'order': '2', 'col_other': '4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'points', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points ; 2 }'}, 'machine'], 'result': 'maico', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points ; 2 } ; machine }'}, 'maico'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; points ; 2 } ; machine } ; maico } = true', 'tointer': 'select the row whose points record of all rows is 2nd maximum . the machine record of this row is maico .'} | eq { hop { nth_argmax { all_rows ; points ; 2 } ; machine } ; maico } = true | select the row whose points record of all rows is 2nd maximum . the machine record of this row is maico . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, '2_6': 6, 'machine_7': 7, 'maico_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', '2_6': '2', 'machine_7': 'machine', 'maico_8': 'maico'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], '2_6': [0], 'machine_7': [1], 'maico_8': [2]} | ['place', 'rider', 'country', 'machine', 'speed', 'time', 'points'] | [['1', 'dieter braun', 'west germany', 'suzuki', '89.27 mph', '1:16.05.0', '15'], ['2', 'bãrje jansson', 'sweden', 'maico', '86.56 mph', '1:18.24.4', '12'], ['3', 'gunter bartusch', 'east germany', 'mz', '85.93 mph', '1:19.02.8', '10'], ['4', 'steve murray', 'united kingdom', 'honda', '84.65 mph', '1:20.14.6', '8'], ['5', 'fred launchbury', 'united kingdom', 'bultaco', '84.25 mph', '1:20.37.8', '6'], ['6', 'jcurry', 'united kingdom', 'honda', '83.99 mph', '1:20.52.0', '5'], ['7', 'tommy robb', 'united kingdom', 'maico', '81.70 mph', '1.23.08.8', '4'], ['8', 'john kiddie', 'united kingdom', 'honda', '81.27 mph', '1.23.34.8', '3'], ['9', 'barrie dickinson', 'united kingdom', 'honda', '80.43 mph', '1.24.27.0', '2'], ['10', 'ken armstrong', 'united kingdom', 'honda', '79.21 mph', '1.25.45.2', '1']] |
1988 - 89 argentine primera división | https://en.wikipedia.org/wiki/1988%E2%80%9389_Argentine_Primera_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17968265-1.html.csv | majority | most of the teams finished with over 100 points . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '100', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'points', '100'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are greater than 100 .', 'tostr': 'most_greater { all_rows ; points ; 100 } = true'} | most_greater { all_rows ; points ; 100 } = true | for the points records of all rows , most of them are greater than 100 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '100_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '100_4': '100'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '100_4': [0]} | ['team', 'average', 'points', 'played', '1986 - 87', '1987 - 88', '1988 - 89'] | [['independiente', '1.219', '139', '114', '47', '37', '55'], ["newell 's old boys", '1.193', '136', '114', '48', '55', '33'], ['san lorenzo', '1.184', '135', '114', '44', '49', '42'], ['racing club', '1.158', '132', '114', '44', '48', '40'], ['boca juniors', '1.140', '130', '114', '46', '35', '49'], ['river plate', '1.140', '130', '114', '39', '46', '45'], ['rosario central', '1.079', '123', '114', '49', '40', '34'], ['deportivo español', '1.070', '122', '114', '36', '40', '46'], ['gimnasia de la plata', '1.018', '116', '114', '37', '43', '36'], ['vélez sársfield', '1.009', '115', '114', '41', '41', '33'], ['estudiantes de la plata', '0.974', '111', '114', '37', '32', '42'], ['argentinos juniors', '0.965', '110', '114', '28', '40', '42'], ['talleres de córdoba', '0.956', '109', '114', '38', '27', '44'], ['ferro carril oeste', '0.939', '107', '114', '44', '33', '30'], ['deportivo mandiyú', '0.868', '33', '38', 'n / a', 'n / a', '33'], ['platense', '0.860', '98', '114', '27', '38', '33'], ['instituto de córdoba', '0.851', '97', '114', '41', '33', '23'], ['racing de córdoba', '0.851', '97', '114', '33', '31', '33'], ['san martín de tucumán', '0.842', '32', '38', 'n / a', 'n / a', '32'], ['deportivo armenio', '0.776', '59', '76', 'n / a', '34', '25']] |
american dad ! ( season 1 ) | https://en.wikipedia.org/wiki/American_Dad%21_%28season_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23242933-2.html.csv | count | two episodes of american dad ! ( season 1 ) were directed by brent woods . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'brent woods', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'brent woods'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to brent woods .', 'tostr': 'filter_eq { all_rows ; directed by ; brent woods }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; directed by ; brent woods } }', 'tointer': 'select the rows whose directed by record fuzzily matches to brent woods . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; directed by ; brent woods } } ; 2 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to brent woods . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; directed by ; brent woods } } ; 2 } = true | select the rows whose directed by record fuzzily matches to brent woods . 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, 'directed by_5': 5, 'brent woods_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', 'directed by_5': 'directed by', 'brent woods_6': 'brent woods', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'directed by_5': [0], 'brent woods_6': [0], '2_7': [2]} | ['no in series', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( millions )'] | [['1', 'pilot', 'ron hughart', 'seth macfarlane , mike barker & matt weitzman', 'february 6 , 2005', '1ajn01', '15.10'], ['2', 'threat levels', 'brent woods', 'david zuckerman', 'may 1 , 2005', '1ajn02', '9.47'], ['3', 'stan knows best', 'pam cooke', 'mike barker & matt weitzman', 'may 8 , 2005', '1ajn03', '8.23'], ['4', "francine 's flashback", 'caleb meurer & brent woods', 'rick wiener & kenny schwartz', 'may 15 , 2005', '1ajn05', '7.84'], ['5', 'roger codger', 'albert calleros', 'dan vebber', 'june 5 , 2005', '1ajn04', '6.09'], ['6', 'homeland insecurity', 'rodney clouden', "neal boushell & sam o'neal", 'june 12 , 2005', '1ajn06', '6.85']] |
world 's busiest passenger air routes | https://en.wikipedia.org/wiki/World%27s_busiest_passenger_air_routes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16066063-1.html.csv | superlative | for worlds busiest passenger air routes , sao paulo to rio de janiero is the shortest distance . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2,3', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'distance'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; distance }'}, 'city 1'], 'result': 'são paulo', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; distance } ; city 1 }'}, 'são paulo'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; distance } ; city 1 } ; são paulo }', 'tointer': 'select the row whose distance record of all rows is minimum . the city 1 record of this row is são paulo .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'distance'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; distance }'}, 'city 2'], 'result': 'rio de janeiro', 'ind': 3, 'tostr': 'hop { argmin { all_rows ; distance } ; city 2 }'}, 'rio de janeiro'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmin { all_rows ; distance } ; city 2 } ; rio de janeiro }', 'tointer': 'the city 2 record of this row is rio de janeiro .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { argmin { all_rows ; distance } ; city 1 } ; são paulo } ; eq { hop { argmin { all_rows ; distance } ; city 2 } ; rio de janeiro } } = true', 'tointer': 'select the row whose distance record of all rows is minimum . the city 1 record of this row is são paulo . the city 2 record of this row is rio de janeiro .'} | and { eq { hop { argmin { all_rows ; distance } ; city 1 } ; são paulo } ; eq { hop { argmin { all_rows ; distance } ; city 2 } ; rio de janeiro } } = true | select the row whose distance record of all rows is minimum . the city 1 record of this row is são paulo . the city 2 record of this row is rio de janeiro . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_7': 7, 'distance_8': 8, 'city 1_9': 9, 'são paulo_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'city 2_11': 11, 'rio de janeiro_12': 12} | {'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_7': 'all_rows', 'distance_8': 'distance', 'city 1_9': 'city 1', 'são paulo_10': 'são paulo', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'city 2_11': 'city 2', 'rio de janeiro_12': 'rio de janeiro'} | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmin_0': [1, 3], 'all_rows_7': [0], 'distance_8': [0], 'city 1_9': [1], 'são paulo_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'city 2_11': [3], 'rio de janeiro_12': [4]} | ['rank', 'city 1', 'city 2', '2012 passengers ( in millions )', '2011 passengers ( in millions )', 'distance'] | [['1', 'seoul', 'jeju', '10.156', '9.9', '450 km'], ['2', 'tokyo', 'sapporo', '8.211', '7.5', '819 km'], ['3', 'são paulo', 'rio de janeiro', '7.716', '7.6 +', '366 km'], ['4', 'beijing', 'shanghai', '7.246', '6.6 +', '1075 km'], ['5', 'sydney', 'melbourne', '6.943', '7.0 +', '706 km'], ['6', 'tokyo', 'osaka', '6.744', '7.5', '405 km'], ['7', 'tokyo', 'fukuoka', '6.640', '6.6 +', '883 km'], ['8', 'hong kong', 'taipei', '5.513', '6.2 +', '780 km'], ['9', 'tokyo', 'okinawa', '4.584', '4.1', '1554 km'], ['10', 'johannesburg', 'cape town', '4.407', '4.5', '1271 km']] |
50 metres | https://en.wikipedia.org/wiki/50_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18811246-1.html.csv | aggregation | in the 50 metres , the average time that the athletes had was 5.603 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '5.603', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'time'], 'result': '5.603', 'ind': 0, 'tostr': 'avg { all_rows ; time }'}, '5.603'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; time } ; 5.603 } = true', 'tointer': 'the average of the time record of all rows is 5.603 .'} | round_eq { avg { all_rows ; time } ; 5.603 } = true | the average of the time record of all rows is 5.603 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'time_4': 4, '5.603_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'time_4': 'time', '5.603_5': '5.603'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'time_4': [0], '5.603_5': [1]} | ['rank', 'time', 'athlete', 'date', 'place'] | [['1', '5.56 b', 'donovan bailey', '9 february 1996', 'reno'], ['1', '5.56 b', 'maurice greene', '13 february 1999', 'los angeles'], ['3', '5.58', 'leonard scott', '26 february 2005', 'liévin'], ['4', '5.61', 'manfred kokot', '4 february 1973', 'berlin'], ['4', '5.61', 'james sanford', '20 february 1981', 'san diego'], ['4', '5.61', 'michael green', '16 february 1997', 'liévin'], ['4', '5.61', 'deji aliu', '21 february 1999', 'liévin'], ['4', '5.61', 'jason gardener', '16 february 2000', 'madrid'], ['4', '5.61', 'freddy mayola', '16 february 2000', 'madrid'], ['10', '5.62', 'emmit king', '5 march 1986', 'kobe'], ['10', '5.62', 'andre cason', '15 february 1992', 'los angeles'], ['10', '5.62', 'eric nkansah', '21 february 1999', 'liévin'], ['10', '5.62', 'morne nagel', '24 february 2002', 'liévin']] |
comparison of java remote desktop projects | https://en.wikipedia.org/wiki/Comparison_of_Java_Remote_Desktop_projects | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18418837-1.html.csv | unique | in comparison of java remote desktop projects , jxta remote desktop is the only project with apache license among those with proprietary protocol . | {'scope': 'subset', 'row': '6', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'apache license', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'proprietary'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'protocol', 'proprietary'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; protocol ; proprietary }', 'tointer': 'select the rows whose protocol record fuzzily matches to proprietary .'}, 'license', 'apache license'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose protocol record fuzzily matches to proprietary . among these rows , select the rows whose license record fuzzily matches to apache license .', 'tostr': 'filter_eq { filter_eq { all_rows ; protocol ; proprietary } ; license ; apache license }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; protocol ; proprietary } ; license ; apache license } }', 'tointer': 'select the rows whose protocol record fuzzily matches to proprietary . among these rows , select the rows whose license record fuzzily matches to apache license . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'protocol', 'proprietary'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; protocol ; proprietary }', 'tointer': 'select the rows whose protocol record fuzzily matches to proprietary .'}, 'license', 'apache license'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose protocol record fuzzily matches to proprietary . among these rows , select the rows whose license record fuzzily matches to apache license .', 'tostr': 'filter_eq { filter_eq { all_rows ; protocol ; proprietary } ; license ; apache license }'}, 'project'], 'result': 'jxta remote desktop', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; protocol ; proprietary } ; license ; apache license } ; project }'}, 'jxta remote desktop'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; protocol ; proprietary } ; license ; apache license } ; project } ; jxta remote desktop }', 'tointer': 'the project record of this unqiue row is jxta remote desktop .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; protocol ; proprietary } ; license ; apache license } } ; eq { hop { filter_eq { filter_eq { all_rows ; protocol ; proprietary } ; license ; apache license } ; project } ; jxta remote desktop } } = true', 'tointer': 'select the rows whose protocol record fuzzily matches to proprietary . among these rows , select the rows whose license record fuzzily matches to apache license . there is only one such row in the table . the project record of this unqiue row is jxta remote desktop .'} | and { only { filter_eq { filter_eq { all_rows ; protocol ; proprietary } ; license ; apache license } } ; eq { hop { filter_eq { filter_eq { all_rows ; protocol ; proprietary } ; license ; apache license } ; project } ; jxta remote desktop } } = true | select the rows whose protocol record fuzzily matches to proprietary . among these rows , select the rows whose license record fuzzily matches to apache license . there is only one such row in the table . the project record of this unqiue row is jxta remote desktop . | 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, 'protocol_8': 8, 'proprietary_9': 9, 'license_10': 10, 'apache license_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'project_12': 12, 'jxta remote desktop_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', 'protocol_8': 'protocol', 'proprietary_9': 'proprietary', 'license_10': 'license', 'apache license_11': 'apache license', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'project_12': 'project', 'jxta remote desktop_13': 'jxta remote desktop'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'protocol_8': [0], 'proprietary_9': [0], 'license_10': [1], 'apache license_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'project_12': [3], 'jxta remote desktop_13': [4]} | ['project', 'license', 'date', 'protocol', 'technology', 'server', 'client', 'web client', 'multiple sessions', 'encryption', 'authentication', 'data compression', 'image quality', 'color quality', 'file transfer', 'clipboard transfer', 'chat', 'relay', 'http tunnel', 'proxy'] | [['ajax remote desktop viewer ( ajaxrd )', 'proprietary', 'june 24 , 2006', 'proprietary', 'socket', '✓', 'x', '✓', '✓', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'], ['dayon !', 'gpl', 'january 3 , 2009', 'proprietary', 'socket', '✓', '✓', 'x', 'x', 'x', 'x', '✓', '✓', '✓', 'x', 'x', 'x', 'x', 'x', 'x'], ['goto servers vnc java server ( gsvncj )', 'proprietary', 'february 17 , 2008', 'rdp , rfb ( vnc )', 'socket', '✓', 'x', 'x', 'x', 'des', '✓', 'x', '✓', '✓', 'x', 'x', 'x', 'x', 'x', 'x'], ['java remote control', 'mit', 'november 14 , 2007', 'proprietary', 'socket', '✓', '✓', 'x', 'x', 'x', '✓', '✓', 'x', 'x', 'x', 'x', 'x', '✓', '✓', '✓'], ['java remote desktop ( jrdesktop )', 'gpl', 'september 16 , 2009', 'proprietary', 'rmi', '✓', '✓', '✓', '✓', 'ssl', '✓', 'x', '✓', '✓', '✓', '✓', 'x', 'x', 'x', '✓'], ['jxta remote desktop', 'apache license', 'february 15 , 2005', 'proprietary', 'socket', '✓', '✓', 'x', '✓', 'x', '✓', 'x', '✓', 'x', '✓', 'x', '✓', '✓', '✓', '✓'], ['j remote desktop', 'gpl', 'may 25 , 2006', 'proprietary', 'rmi', '✓', '✓', 'x', 'x', 'x', '✓', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x', 'x'], ['n - central', 'commercial', 'may 2011', 'ssh , udp , http', 'socket', '✓', '✓', '✓', '✓', '✓', '✓', 'x', '✓', '✓', '✓', 'x', '✓', '✓', '✓', '✓'], ['properjavardp', 'gpl', 'may 15 , 2007', 'rdp', 'socket', 'x', '✓', 'x', 'x', 'rc4', '✓', 'x', 'x', '✓', 'x', '✓', 'x', 'x', 'x', 'x'], ['webrdp', 'proprietary', 'june 17 , 2010', 'rdp', 'socket', 'html5 gateway', '✓', '✓', '✓', 'rc4 / ssl', '✓', '✓', '✓', '✓', 'x', '✓', 'x', '✓', '✓', '✓'], ['hoblink jwt', 'proprietary', 'february 6 , 2010', 'rdp', 'socket', 'x', '✓', '✓', '✓', 'ssl', '✓', '✓', '✓', '✓', '✓', '✓', 'x', '✓', '✓', '✓'], ['robo', 'gpl', 'november 21 , 2002', 'proprietary', 'socket', '✓', '✓', '✓', '✓', 'ssl', '✓', '✓', 'x', '✓', 'x', 'x', 'x', 'x', '✓', 'x'], ['vnc viewer', 'proprietary', '2004', 'rfb ( vnc )', 'socket', 'x', '✓', 'x', '✓', 'x', '✓', 'x', '✓', '✓', 'x', '✓', 'x', 'x', 'x', 'x'], ['vedivi vpn', 'proprietary', '2008', 'proprietary', 'socket', '✓', '✓', '✓', '✓', 'ssl', '✓', '✓', '✓', '✓', '✓', '✓', 'x', '✓', '✓', '✓'], ['wificheema', 'proprietary', '2010', 'proprietary', 'socket', '✓', '✓', '✓', '✓', 'ssl', '✓', '✓', '✓', '✓', 'x', 'x', '✓', 'x', 'x', 'x'], ['project', 'license', 'date', 'protocol', 'technology', 'server', 'client', 'web client', 'multiple sessions', 'encryption', 'authentication', 'data compression', 'image quality', 'color quality', 'file transfer', 'clipboard transfer', 'chat', 'relay', 'http tunnel', 'proxy']] |
2008 - 09 segunda división | https://en.wikipedia.org/wiki/2008%E2%80%9309_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12951990-4.html.csv | comparative | juan calatayud allowed more goals in the 2008 - 09 segunda división than eduardo navarro . | {'row_1': '6', 'row_2': '7', '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', 'goalkeeper', 'juan calatayud'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goalkeeper record fuzzily matches to juan calatayud .', 'tostr': 'filter_eq { all_rows ; goalkeeper ; juan calatayud }'}, 'goals'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; goalkeeper ; juan calatayud } ; goals }', 'tointer': 'select the rows whose goalkeeper record fuzzily matches to juan calatayud . take the goals record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'goalkeeper', 'eduardo navarro'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose goalkeeper record fuzzily matches to eduardo navarro .', 'tostr': 'filter_eq { all_rows ; goalkeeper ; eduardo navarro }'}, 'goals'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; goalkeeper ; eduardo navarro } ; goals }', 'tointer': 'select the rows whose goalkeeper record fuzzily matches to eduardo navarro . take the goals record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; goalkeeper ; juan calatayud } ; goals } ; hop { filter_eq { all_rows ; goalkeeper ; eduardo navarro } ; goals } } = true', 'tointer': 'select the rows whose goalkeeper record fuzzily matches to juan calatayud . take the goals record of this row . select the rows whose goalkeeper record fuzzily matches to eduardo navarro . take the goals record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; goalkeeper ; juan calatayud } ; goals } ; hop { filter_eq { all_rows ; goalkeeper ; eduardo navarro } ; goals } } = true | select the rows whose goalkeeper record fuzzily matches to juan calatayud . take the goals record of this row . select the rows whose goalkeeper record fuzzily matches to eduardo navarro . take the goals record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'goalkeeper_7': 7, 'juan calatayud_8': 8, 'goals_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'goalkeeper_11': 11, 'eduardo navarro_12': 12, 'goals_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'goalkeeper_7': 'goalkeeper', 'juan calatayud_8': 'juan calatayud', 'goals_9': 'goals', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'goalkeeper_11': 'goalkeeper', 'eduardo navarro_12': 'eduardo navarro', 'goals_13': 'goals'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'goalkeeper_7': [0], 'juan calatayud_8': [0], 'goals_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'goalkeeper_11': [1], 'eduardo navarro_12': [1], 'goals_13': [3]} | ['goalkeeper', 'goals', 'matches', 'average', 'team'] | [['david cobeño', '35', '40', '0.88', 'rayo vallecano'], ['claudio bravo', '28', '32', '0.88', 'real sociedad'], ['chema', '41', '41', '1', 'xerez cd'], ['carlos sánchez', '34', '34', '1', 'cd castellón'], ['alberto cifuentes', '34', '33', '1.03', 'ud salamanca'], ['juan calatayud', '42', '40', '1.05', 'hércules cf'], ['eduardo navarro', '39', '36', '1.08', 'sd huesca'], ['wilfredo caballero', '40', '36', '1.11', 'elche cf'], ['rubén pérez', '38', '33', '1.15', 'gimnàstic de tarragona'], ['roberto santamaría', '45', '39', '1.15', 'ud las palmas']] |
world golf championships | https://en.wikipedia.org/wiki/World_Golf_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1458666-4.html.csv | unique | england is the only nation that had 4 individual wins in the world golf championships . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '4', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'individual wins', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose individual wins record is equal to 4 .', 'tostr': 'filter_eq { all_rows ; individual wins ; 4 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; individual wins ; 4 } }', 'tointer': 'select the rows whose individual wins record is equal to 4 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'individual wins', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose individual wins record is equal to 4 .', 'tostr': 'filter_eq { all_rows ; individual wins ; 4 }'}, 'nation'], 'result': 'england', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; individual wins ; 4 } ; nation }'}, 'england'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; individual wins ; 4 } ; nation } ; england }', 'tointer': 'the nation record of this unqiue row is england .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; individual wins ; 4 } } ; eq { hop { filter_eq { all_rows ; individual wins ; 4 } ; nation } ; england } } = true', 'tointer': 'select the rows whose individual wins record is equal to 4 . there is only one such row in the table . the nation record of this unqiue row is england .'} | and { only { filter_eq { all_rows ; individual wins ; 4 } } ; eq { hop { filter_eq { all_rows ; individual wins ; 4 } ; nation } ; england } } = true | select the rows whose individual wins record is equal to 4 . there is only one such row in the table . the nation record of this unqiue row is england . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'individual wins_7': 7, '4_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'england_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'individual wins_7': 'individual wins', '4_8': '4', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'england_10': 'england'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'individual wins_7': [0], '4_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'england_10': [3]} | ['nation', 'total wins', 'team wins', 'individual wins', 'individual winners'] | [['united states', '32', '1', '31', '12'], ['australia', '5', '0', '5', '3'], ['england', '5', '1', '4', '3'], ['south africa', '4', '2', '2', '1'], ['northern ireland', '2', '0', '2', '1'], ['germany', '2', '1', '1', '1'], ['canada', '1', '0', '1', '1'], ['fiji', '1', '0', '1', '1'], ['sweden', '1', '0', '1', '1'], ['italy', '1', '0', '1', '1'], ['japan', '1', '1', '0', '0'], ['wales', '1', '1', '0', '0']] |
1967 syracuse orangemen football team | https://en.wikipedia.org/wiki/1967_Syracuse_Orangemen_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20850339-1.html.csv | superlative | penn state scored the most points against the 1967 syracuse orangemen football team . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'opponents'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; opponents }'}, 'opponent'], 'result': 'penn state', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; opponents } ; opponent }'}, 'penn state'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; opponents } ; opponent } ; penn state } = true', 'tointer': 'select the row whose opponents record of all rows is maximum . the opponent record of this row is penn state .'} | eq { hop { argmax { all_rows ; opponents } ; opponent } ; penn state } = true | select the row whose opponents record of all rows is maximum . the opponent record of this row is penn state . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'opponents_5': 5, 'opponent_6': 6, 'penn state_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'opponents_5': 'opponents', 'opponent_6': 'opponent', 'penn state_7': 'penn state'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'opponents_5': [0], 'opponent_6': [1], 'penn state_7': [2]} | ['game', 'date', 'opponent', 'result', 'orangemen points', 'opponents', 'record'] | [['1', 'sept 23', 'baylor', 'win', '7', '0', '1 - 0'], ['2', 'sept 30', 'west virginia', 'win', '23', '6', '2 - 0'], ['3', 'oct 7', 'maryland', 'win', '7', '3', '3 - 0'], ['4', 'oct 14', 'navy', 'loss', '14', '27', '3 - 1'], ['5', 'oct 21', 'california', 'win', '20', '14', '4 - 1'], ['6', 'oct 28', 'penn state', 'loss', '20', '29', '4 - 2'], ['7', 'nov 4', 'pittsburgh', 'win', '14', '7', '5 - 2'], ['8', 'nov 11', 'holy cross', 'win', '41', '7', '6 - 2'], ['9', 'nov 18', 'boston college', 'win', '32', '20', '7 - 2']] |
united states house of representatives elections , 2000 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341423-21.html.csv | superlative | joe moakley from district 9 in massachusetts had the highest percentage of electoral votes among the other massachusetts incumbents that ran against an opponent in the 2000 united states house of representatives elections . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'candidates'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; candidates }'}, 'incumbent'], 'result': 'joe moakley', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; candidates } ; incumbent }'}, 'joe moakley'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; candidates } ; incumbent } ; joe moakley } = true', 'tointer': 'select the row whose candidates record of all rows is maximum . the incumbent record of this row is joe moakley .'} | eq { hop { argmax { all_rows ; candidates } ; incumbent } ; joe moakley } = true | select the row whose candidates record of all rows is maximum . the incumbent record of this row is joe moakley . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'candidates_5': 5, 'incumbent_6': 6, 'joe moakley_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'candidates_5': 'candidates', 'incumbent_6': 'incumbent', 'joe moakley_7': 'joe moakley'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'candidates_5': [0], 'incumbent_6': [1], 'joe moakley_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['massachusetts 1', 'john olver', 'democratic', '1991', 're - elected', 'john olver ( d ) 69 % peter abair ( r ) 30 %'], ['massachusetts 2', 'richard neal', 'democratic', '1988', 're - elected', 'richard neal ( d ) unopposed'], ['massachusetts 3', 'jim mcgovern', 'democratic', '1996', 're - elected', 'jim mcgovern ( d ) unopposed'], ['massachusetts 4', 'barney frank', 'democratic', '1980', 're - elected', 'barney frank ( d ) 71 % martin travis ( r ) 21 %'], ['massachusetts 5', 'marty meehan', 'democratic', '1992', 're - elected', 'marty meehan ( d ) unopposed'], ['massachusetts 6', 'john f tierney', 'democratic', '1996', 're - elected', 'john f tierney ( d ) 71 % paul mccarthy ( r ) 29 %'], ['massachusetts 7', 'ed markey', 'democratic', '1976', 're - elected', 'ed markey ( d ) unopposed'], ['massachusetts 8', 'mike capuano', 'democratic', '1998', 're - elected', 'mike capuano ( d ) unopposed'], ['massachusetts 9', 'joe moakley', 'democratic', '1972', 're - elected', 'joe moakley ( d ) 78 % janet jeghelian ( r ) 20 %']] |
weightlifting at the 1999 pan american games | https://en.wikipedia.org/wiki/Weightlifting_at_the_1999_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11279593-11.html.csv | ordinal | soraya jiménez of mexico came in third in women 's weightlifting at the 1999 pan american games . | {'row': '3', 'col': '5', 'order': '3', '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', 'total ( kg )', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ( kg ) ; 3 }'}, 'name'], 'result': 'soraya jiménez ( mex )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ( kg ) ; 3 } ; name }'}, 'soraya jiménez ( mex )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ( kg ) ; 3 } ; name } ; soraya jiménez ( mex ) } = true', 'tointer': 'select the row whose total ( kg ) record of all rows is 3rd maximum . the name record of this row is soraya jiménez ( mex ) .'} | eq { hop { nth_argmax { all_rows ; total ( kg ) ; 3 } ; name } ; soraya jiménez ( mex ) } = true | select the row whose total ( kg ) record of all rows is 3rd maximum . the name record of this row is soraya jiménez ( mex ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total (kg)_5': 5, '3_6': 6, 'name_7': 7, 'soraya jiménez ( mex )_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'total (kg)_5': 'total ( kg )', '3_6': '3', 'name_7': 'name', 'soraya jiménez ( mex )_8': 'soraya jiménez ( mex )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total (kg)_5': [0], '3_6': [0], 'name_7': [1], 'soraya jiménez ( mex )_8': [2]} | ['name', 'bodyweight', 'snatch', 'clean & jerk', 'total ( kg )'] | [['maryse turcotte ( can )', '57.56', '87.5', '112.5', '200.0'], ['nancy niro ( can )', '57.92', '87.5', '105.0', '192.5'], ['soraya jiménez ( mex )', '57.19', '85.0', '105.0', '190.0'], ['ruth rivera ( pur )', '57.56', '67.5', '95.0', '162.5'], ['patricia sosa ( esa )', '57.41', '67.5', '92.5', '160.0'], ['liliana garcía ( ven )', '57.32', '80.0', '105.0', '-']] |
2008 - 09 west ham united f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_West_Ham_United_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18539546-7.html.csv | count | in the 2008 - 09 west ham united f.c. season , when the type is transferred , there are three times the transfer fee was undisclosed . | {'scope': 'subset', 'criterion': 'equal', 'value': 'undisclosed', 'result': '3', 'col': '5', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'transferred'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'transferred'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; type ; transferred }', 'tointer': 'select the rows whose type record fuzzily matches to transferred .'}, 'transfer fee', 'undisclosed'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose type record fuzzily matches to transferred . among these rows , select the rows whose transfer fee record fuzzily matches to undisclosed .', 'tostr': 'filter_eq { filter_eq { all_rows ; type ; transferred } ; transfer fee ; undisclosed }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; type ; transferred } ; transfer fee ; undisclosed } }', 'tointer': 'select the rows whose type record fuzzily matches to transferred . among these rows , select the rows whose transfer fee record fuzzily matches to undisclosed . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; type ; transferred } ; transfer fee ; undisclosed } } ; 3 } = true', 'tointer': 'select the rows whose type record fuzzily matches to transferred . among these rows , select the rows whose transfer fee record fuzzily matches to undisclosed . the number of such rows is 3 .'} | eq { count { filter_eq { filter_eq { all_rows ; type ; transferred } ; transfer fee ; undisclosed } } ; 3 } = true | select the rows whose type record fuzzily matches to transferred . among these rows , select the rows whose transfer fee record fuzzily matches to undisclosed . 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, 'type_6': 6, 'transferred_7': 7, 'transfer fee_8': 8, 'undisclosed_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', 'type_6': 'type', 'transferred_7': 'transferred', 'transfer fee_8': 'transfer fee', 'undisclosed_9': 'undisclosed', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'type_6': [0], 'transferred_7': [0], 'transfer fee_8': [1], 'undisclosed_9': [1], '3_10': [3]} | ['name', 'country', 'type', 'moving from', 'transfer fee'] | [['eyjólfsson', 'isl', 'transferred', 'hk', 'undisclosed'], ['bajner', 'hun', 'transferred', 'liberty oradea', 'undisclosed'], ['behrami', 'sui', 'transferred', 'lazio', '5 m'], ['laštůvka', 'cze', 'loaned', 'shakhtardonetsk', 'n / a'], ['grasser', 'aut', 'transferred', 'grazer ak', 'undisclosed'], ['ilunga', 'cod', 'loaned', 'toulouse', 'n / a'], ['di michele', 'ita', 'loaned', 'torino', 'n / a'], ['lópez', 'uru', 'transferred', 'river plate', 'free agent'], ['tristán', 'esp', 'transferred', 'livorno', 'free agent']] |
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