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eurovision song contest 1985 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_1985 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-185276-2.html.csv | count | in the 1985 eurovision song contest , two of the songs were in the english language . | {'scope': 'all', 'criterion': 'equal', 'value': 'english', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'language', 'english'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose language record fuzzily matches to english .', 'tostr': 'filter_eq { all_rows ; language ; english }'}], 'result': '2', 'ind': 1, 'tostr':... | eq { count { filter_eq { all_rows ; language ; english } } ; 2 } = true | select the rows whose language record fuzzily matches to english . 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, 'language_5': 5, 'english_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', 'language_5': 'language', 'english_6': 'english', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'language_5': [0], 'english_6': [0], '2_7': [2]} | ['draw', 'language', 'song', 'english translation', 'place', 'points'] | [['01', 'english', 'wait until the weekend comes', '-', '6', '91'], ['02', 'finnish', 'eläköön elämä', 'long live life', '9', '58'], ['03', 'greek', 'to katalava arga ( το κατάλαβα αργά )', 'i realised it too late', '16', '15'], ['04', 'danish', "sku ' du spørg ' fra no'en", 'what business is it of yours', '11', '41'],... |
loonie | https://en.wikipedia.org/wiki/Loonie | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18400-2.html.csv | count | the artist arnold nogy has been responsible for the art of three of the special loonies series . | {'scope': 'all', 'criterion': 'equal', 'value': 'arnold nogy', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'artist', 'arnold nogy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose artist record fuzzily matches to arnold nogy .', 'tostr': 'filter_eq { all_rows ; artist ; arnold nogy }'}], 'result': '3', 'ind': 1, 't... | eq { count { filter_eq { all_rows ; artist ; arnold nogy } } ; 3 } = true | select the rows whose artist record fuzzily matches to arnold nogy . 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, 'artist_5': 5, 'arnold nogy_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', 'artist_5': 'artist', 'arnold nogy_6': 'arnold nogy', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'artist_5': [0], 'arnold nogy_6': [0], '3_7': [2]} | ['year', 'theme', 'artist', 'mintage', 'issue price'] | [['2002', '15th anniversary loonie', 'dora de pãdery - hunt', '67672', '39.95'], ['2004', 'jack miner bird sanctuary', 'susan taylor', '46493', '39.95'], ['2005', 'tufted puffin', 'n / a', '39818', '39.95'], ['2006', 'snowy owl', 'glen loates', '39935', '44.95'], ['2007', 'trumpeter swan', 'kerri burnett', '40000', '45... |
sebastian prödl | https://en.wikipedia.org/wiki/Sebastian_Pr%C3%B6dl | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12253254-1.html.csv | unique | the 15 october 2013 competition is the only one for sebastian prödl that was a 2014 fifa world cup qualification . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '2014 fifa world cup qualification', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '2014 fifa world cup qualification'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to 2014 fifa world cup qualification .', 'tostr': 'filter_eq { all_rows ; ... | and { only { filter_eq { all_rows ; competition ; 2014 fifa world cup qualification } } ; eq { hop { filter_eq { all_rows ; competition ; 2014 fifa world cup qualification } ; date } ; 15 october 2013 } } = true | select the rows whose competition record fuzzily matches to 2014 fifa world cup qualification . there is only one such row in the table . the date record of this unqiue row is 15 october 2013 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'competition_7': 7, '2014 fifa world cup qualification_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '15 october 2013_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'competition_7': 'competition', '2014 fifa world cup qualification_8': '2014 fifa world cup qualification', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '15 october 2013_10': '15 octob... | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'competition_7': [0], '2014 fifa world cup qualification_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '15 october 2013_10': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['26 march 2008', 'ernst - happel - stadion , vienna , austria', '2 - 0', '3 - 4', 'friendly'], ['26 march 2008', 'ernst - happel - stadion , vienna , austria', '3 - 0', '3 - 4', 'friendly'], ['8 october 2010', 'ernst - happel - stadion , vienna , austria', '1 - 0', '3 - 0', 'uefa euro 2012 qualifying'], ['15 october ... |
suburban league | https://en.wikipedia.org/wiki/Suburban_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28051859-3.html.csv | comparative | mogadore 's tenure in the suburban league began before field 's tenure began . | {'row_1': '6', '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', 'school', 'mogadore'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to mogadore .', 'tostr': 'filter_eq { all_rows ; school ; mogadore }'}, 'tenure'], 'result': None, 'ind':... | less { hop { filter_eq { all_rows ; school ; mogadore } ; tenure } ; hop { filter_eq { all_rows ; school ; field } ; tenure } } = true | select the rows whose school record fuzzily matches to mogadore . take the tenure record of this row . select the rows whose school record fuzzily matches to field . take the tenure 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, 'school_7': 7, 'mogadore_8': 8, 'tenure_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'school_11': 11, 'field_12': 12, 'tenure_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', 'school_7': 'school', 'mogadore_8': 'mogadore', 'tenure_9': 'tenure', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'school_11': 'school', 'field_12': 'fi... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'school_7': [0], 'mogadore_8': [0], 'tenure_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'school_11': [1], 'field_12': [1], 'tenure_13': [3]} | ['school', 'nickname', 'location', 'colors', 'tenure'] | [['barberton', 'magics', 'barberton , summit county', 'purple , white', '2005 - 2011'], ['coventry', 'comets', 'coventry twp , summit county', 'blue , gold', '1969 - 1983'], ['field', 'falcons', 'brimfield , portage county', 'red , white , black', '1978 - 1990'], ['hudson', 'explorers', 'hudson , summit county', 'navy ... |
netflow | https://en.wikipedia.org/wiki/NetFlow | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1206114-2.html.csv | majority | the majority of netflow implementations are software implementations . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'software', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'implementation', 'software'], 'result': True, 'ind': 0, 'tointer': 'for the implementation records of all rows , most of them fuzzily match to software .', 'tostr': 'most_eq { all_rows ; implementation ; software } = true'} | most_eq { all_rows ; implementation ; software } = true | for the implementation records of all rows , most of them fuzzily match to software . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'implementation_3': 3, 'software_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'implementation_3': 'implementation', 'software_4': 'software'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'implementation_3': [0], 'software_4': [0]} | ['vendor and type', 'models', 'netflow version', 'implementation', 'comments'] | [['cisco ios - xr routers', 'crs , asr9000 old 12000', 'v5 , v8 , v9', 'software running on line card cpu', 'comprehensive support for ipv6 and mpls'], ['alcatel - lucent routers', '7750sr', 'v5 , v8 , v9 , ipfix', 'software running on central processor module', 'ipv6 or mpls using iom3 line cards or better'], ['huawei... |
list of csi : ny characters | https://en.wikipedia.org/wiki/List_of_CSI%3A_NY_characters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11240028-5.html.csv | ordinal | out of the list of csi : ny characters who were criminals , character shane casey had the second-highest murder count . | {'row': '5', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crime', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crime ; 2 }'}, 'character'], 'result': 'shane casey', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crime ; 2 } ; character }'}, 'shane case... | eq { hop { nth_argmax { all_rows ; crime ; 2 } ; character } ; shane casey } = true | select the row whose crime record of all rows is 2nd maximum . the character record of this row is shane casey . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crime_5': 5, '2_6': 6, 'character_7': 7, 'shane casey_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', 'crime_5': 'crime', '2_6': '2', 'character_7': 'character', 'shane casey_8': 'shane casey'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crime_5': [0], '2_6': [0], 'character_7': [1], 'shane casey_8': [2]} | ['character', 'portrayed by', 'crime', 'first appearance', 'last appearance'] | [['sonny sassone', 'michael deluise', 'murder ( 2 counts )', 'tanglewood', 'run silent , run deep'], ['frankie mala', 'ed quinn', 'attempted murder ( attacked stella )', 'grand murder at central station', 'all access'], ['henry darius', 'james badge dale', 'murder ( 15 counts )', 'felony flight ( csi : miami crossover ... |
haarlem baseball week | https://en.wikipedia.org/wiki/Haarlem_Baseball_Week | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18532667-2.html.csv | count | 13 nations were represented in the haarlem baseball week tournament . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '13', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'nation'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record is arbitrary .', 'tostr': 'filter_all { all_rows ; nation }'}], 'result': '13', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; nation }... | eq { count { filter_all { all_rows ; nation } } ; 13 } = true | select the rows whose nation record is arbitrary . the number of such rows is 13 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'nation_5': 5, '13_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'nation_5': 'nation', '13_6': '13'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'nation_5': [0], '13_6': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'united states', '13', '7', '10', '30'], ['2', 'cuba', '5', '6', '2', '13'], ['3', 'netherlands', '3', '7', '7', '17'], ['4', 'japan', '3', '1', '2', '6'], ['5', 'canada', '1', '1', '0', '2'], ['6', 'netherlands antilles', '1', '0', '1', '2'], ['7', 'south korea', '0', '2', '0', '2'], ['8', 'germany', '0', '1', ... |
rowing at the 2008 summer olympics - men 's single sculls | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_single_sculls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662643-6.html.csv | ordinal | peter hardcastle recorded the 2nd fasted time of the 2008 olympics men 's single sculls rowing competition . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'time', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; time ; 2 }'}, 'athlete'], 'result': 'peter hardcastle', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; time ; 2 } ; athlete }'}, 'peter hardca... | eq { hop { nth_argmin { all_rows ; time ; 2 } ; athlete } ; peter hardcastle } = true | select the row whose time record of all rows is 2nd minimum . the athlete record of this row is peter hardcastle . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, '2_6': 6, 'athlete_7': 7, 'peter hardcastle_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', '2_6': '2', 'athlete_7': 'athlete', 'peter hardcastle_8': 'peter hardcastle'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], '2_6': [0], 'athlete_7': [1], 'peter hardcastle_8': [2]} | ['rank', 'athlete', 'country', 'time', 'notes'] | [['1', 'alan campbell', 'great britain', '7:14.98', 'q'], ['2', 'peter hardcastle', 'australia', '7:17.74', 'q'], ['3', 'patrick loliger', 'mexico', '7:22.55', 'q'], ['4', 'ken jurkowski', 'united states', '7:25.13', 'q'], ['5', 'ruslan naurzaliev', 'uzbekistan', '7:58.43', 'se / f']] |
2006 - 07 macedonian cup | https://en.wikipedia.org/wiki/2006%E2%80%9307_Macedonian_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17065288-2.html.csv | unique | the only game of the macedonian cup for 2006 - 07 having a team score a 2nd . leg score of 4 is rabotnički vs. ilinden . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': '1,3', 'criterion': 'fuzzily_match', 'value': '4', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2nd leg', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2nd leg record fuzzily matches to 4 .', 'tostr': 'filter_eq { all_rows ; 2nd leg ; 4 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq {... | and { only { filter_eq { all_rows ; 2nd leg ; 4 } } ; and { eq { hop { filter_eq { all_rows ; 2nd leg ; 4 } ; team 1 } ; rabotnički } ; eq { hop { filter_eq { all_rows ; 2nd leg ; 4 } ; team 2 } ; ilinden } } } = true | select the rows whose 2nd leg record fuzzily matches to 4 . there is only one such row in the table . the team 1 record of this unqiue row is rabotnički . the team 2 record of this unqiue row is ilinden . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, '2nd leg_10': 10, '4_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'team 1_12': 12, 'rabotnički_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'team 2_14': 14, 'ilinden_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', '2nd leg_10': '2nd leg', '4_11': '4', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team 1_12': 'team 1', 'rabotnički_13': 'rabotnički', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'te... | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], '2nd leg_10': [0], '4_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'team 1_12': [2], 'rabotnički_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'team 2_14': [4], 'ilinden_15': [5]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['pobeda', '3 - 0', 'shkëndija 79', '2 - 0', '1 - 0'], ['vardar', '5 - 1', 'metalurg', '4 - 1', '1 - 0'], ['drita', '4 - 2', 'bregalnica kraun', '3 - 0', '1 - 2'], ['gostivar', '3 - 6', 'renova', '1 - 4', '2 - 2'], ['milano', '4 - 3', 'baškimi', '2 - 1', '2 - 2'], ['rabotnički', '5 - 4', 'ilinden', '4 - 0', '1 - 4'], ... |
1976 los angeles rams season | https://en.wikipedia.org/wiki/1976_Los_Angeles_Rams_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11159520-2.html.csv | unique | the only los angeles rams game in november 1976 with an attendance of over 60000 was on november 14th . | {'scope': 'subset', 'row': '10', 'col': '5', 'col_other': '2', 'criterion': 'greater_than', 'value': '60000', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'november'}} | {'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; november }', 'tointer': 'select the rows whose date record fuzzily matches to november .'}, 'attendance', '60000'], 'result'... | only { filter_greater { filter_eq { all_rows ; date ; november } ; attendance ; 60000 } } = true | select the rows whose date record fuzzily matches to november . among these rows , select the rows whose attendance record is greater than 60000 . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'november_6': 6, 'attendance_7': 7, '60000_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'november_6': 'november', 'attendance_7': 'attendance', '60000_8': '60000'} | {'only_2': [3], 'result_3': [], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'november_6': [0], 'attendance_7': [1], '60000_8': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 12 , 1976', 'atlanta falcons', 'w 30 - 14', '53607'], ['2', 'september 19 , 1976', 'minnesota vikings', 't 10 - 10', '47310'], ['3', 'september 26 , 1976', 'new york giants', 'w 24 - 10', '60698'], ['4', 'october 3 , 1976', 'miami dolphins', 'w 31 - 28', '60753'], ['5', 'october 11 , 1976', 'san franc... |
2003 - 04 european challenge cup | https://en.wikipedia.org/wiki/2003%E2%80%9304_European_Challenge_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27987767-3.html.csv | aggregation | in the 2003-04 european challenge cup the players had a points margin average of 20 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '20', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points margin'], 'result': '20', 'ind': 0, 'tostr': 'avg { all_rows ; points margin }'}, '20'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points margin } ; 20 } = true', 'tointer': 'the average of the points margin record of all r... | round_eq { avg { all_rows ; points margin } ; 20 } = true | the average of the points margin record of all rows is 20 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points margin_4': 4, '20_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points margin_4': 'points margin', '20_5': '20'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points margin_4': [0], '20_5': [1]} | ['proceed to quarter - final', 'match points', 'aggregate score', 'points margin', 'eliminated from competition'] | [['nec harlequins', '4 - 0', '89 - 25', '64', 'montauban'], ['béziers', '4 - 0', '43 - 23', '20', 'grenoble'], ['bath', '4 - 0', '58 - 42', '16', 'colomiers'], ['connacht', '2 - 2', '35 - 17', '18', 'pau'], ['narbonne', '2 - 2', '42 - 30', '12', 'london irish'], ['brive', '2 - 2', '58 - 48', '10', 'castres olympique'],... |
1967 - 68 new york rangers season | https://en.wikipedia.org/wiki/1967%E2%80%9368_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17311408-4.html.csv | unique | the only game against the detroit red wings in the 1967 - 68 new york rangers season to finish in a draw was on 6 december . | {'scope': 'subset', 'row': '3', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '3-3', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'detroit red wings'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'detroit red wings'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; detroit red wings }', 'tointer': 'select the rows whose opponent record fuzzily mat... | and { only { filter_eq { filter_eq { all_rows ; opponent ; detroit red wings } ; score ; 3-3 } } ; eq { hop { filter_eq { filter_eq { all_rows ; opponent ; detroit red wings } ; score ; 3-3 } ; december } ; 6 } } = true | select the rows whose opponent record fuzzily matches to detroit red wings . among these rows , select the rows whose score record fuzzily matches to 3-3 . there is only one such row in the table . the december record of this unqiue row is 6 . | 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, 'opponent_8': 8, 'detroit red wings_9': 9, 'score_10': 10, '3-3_11': 11, 'eq_4': 4, 'num_hop_3': 3, 'december_12': 12, '6_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', 'opponent_8': 'opponent', 'detroit red wings_9': 'detroit red wings', 'score_10': 'score', '3-3_11': '3-3', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'december_12': 'decem... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'opponent_8': [0], 'detroit red wings_9': [0], 'score_10': [1], '3-3_11': [1], 'eq_4': [5], 'num_hop_3': [4], 'december_12': [3], '6_13': [4]} | ['game', 'december', 'opponent', 'score', 'record'] | [['21', '2', 'pittsburgh penguins', '4 - 1', '10 - 8 - 3'], ['22', '3', 'los angeles kings', '4 - 2', '11 - 8 - 3'], ['23', '6', 'detroit red wings', '3 - 3', '11 - 8 - 4'], ['24', '7', 'boston bruins', '3 - 1', '11 - 9 - 4'], ['25', '9', 'detroit red wings', '3 - 2', '11 - 10 - 4'], ['26', '10', 'montreal canadiens', ... |
2008 - 09 süper lig | https://en.wikipedia.org/wiki/2008%E2%80%9309_S%C3%BCper_Lig | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17356873-2.html.csv | majority | in the süper lig , the manner of departure for most of the managers , was that they resigned . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'resigned', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'manner of departure', 'resigned'], 'result': True, 'ind': 0, 'tointer': 'for the manner of departure records of all rows , most of them fuzzily match to resigned .', 'tostr': 'most_eq { all_rows ; manner of departure ; resigned } = true'} | most_eq { all_rows ; manner of departure ; resigned } = true | for the manner of departure records of all rows , most of them fuzzily match to resigned . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'manner of departure_3': 3, 'resigned_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'manner of departure_3': 'manner of departure', 'resigned_4': 'resigned'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'manner of departure_3': [0], 'resigned_4': [0]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment'] | [['konyaspor', 'raşit çetiner', 'sacked', '17 september 2008', 'giray bulak', '24 september 2008'], ['kocaelispor', 'engin ipekoğlu', 'sacked', '25 september 2008', 'yılmaz vural', '28 september 2008'], ['beşiktaş', 'ertuğrul sağlam', 'resigned', '7 october 2008', 'mustafa denizli', '9 october 2008'], ['ankaragücü', 'h... |
1964 oakland raiders season | https://en.wikipedia.org/wiki/1964_Oakland_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12828281-1.html.csv | count | the oakland raiders won just 5 of their games in 1964 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'w', 'result': '5', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; result ; w }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { al... | eq { count { filter_eq { all_rows ; result ; w } } ; 5 } = true | select the rows whose result record fuzzily matches to w . 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, 'result_5': 5, 'w_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', 'result_5': 'result', 'w_6': 'w', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'w_6': [0], '5_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 13 , 1964', 'boston patriots', 'l 17 - 14', '21126'], ['2', 'september 19 , 1964', 'houston oilers', 'l 42 - 28', '26482'], ['3', 'september 27 , 1964', 'kansas city chiefs', 'l 21 - 9', '18163'], ['4', 'october 3 , 1964', 'buffalo bills', 'l 23 - 20', '36451'], ['5', 'october 10 , 1964', 'new york je... |
khym | https://en.wikipedia.org/wiki/KHYM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14993391-1.html.csv | comparative | the khym radio channel with the call sign k297al operates on a higher frequency than the call sign k239ax . | {'row_1': '1', 'row_2': '4', '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', 'call sign', 'k297al'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose call sign record fuzzily matches to k297al .', 'tostr': 'filter_eq { all_rows ; call sign ; k297al }'}, 'frequency mhz'], 'result':... | greater { hop { filter_eq { all_rows ; call sign ; k297al } ; frequency mhz } ; hop { filter_eq { all_rows ; call sign ; k239ax } ; frequency mhz } } = true | select the rows whose call sign record fuzzily matches to k297al . take the frequency mhz record of this row . select the rows whose call sign record fuzzily matches to k239ax . take the frequency mhz 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, 'call sign_7': 7, 'k297al_8': 8, 'frequency mhz_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'call sign_11': 11, 'k239ax_12': 12, 'frequency mhz_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', 'call sign_7': 'call sign', 'k297al_8': 'k297al', 'frequency mhz_9': 'frequency mhz', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'call sign_11': ... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'call sign_7': [0], 'k297al_8': [0], 'frequency mhz_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'call sign_11': [1], 'k239ax_12': [1], 'frequency mhz_13': [3]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['k297al', '107.3', 'dighton , kansas', '170', 'd', 'fcc'], ['k236 am', '95.1', 'elkhart , kansas', '170', 'd', 'fcc'], ['k207et', '89.3', 'healy , kansas', '75', 'd', 'fcc'], ['k239ax', '95.7', 'larned , kansas', '170', 'd', 'fcc'], ['k211ch', '90.5', 'leoti , kansas', '250', 'd', 'fcc'], ['k232dh', '94.3', 'ulysses ... |
julian bailey | https://en.wikipedia.org/wiki/Julian_Bailey | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235920-4.html.csv | count | julian bailey drove with the team mg sport & racing ltd for a total of two years . | {'scope': 'all', 'criterion': 'equal', 'value': 'mg sport & racing ltd', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'mg sport & racing ltd'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to mg sport & racing ltd .', 'tostr': 'filter_eq { all_rows ; team ; mg sport & racing ltd }'}], 're... | eq { count { filter_eq { all_rows ; team ; mg sport & racing ltd } } ; 2 } = true | select the rows whose team record fuzzily matches to mg sport & racing ltd . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'mg sport & racing ltd_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'mg sport & racing ltd_6': 'mg sport & racing ltd', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'mg sport & racing ltd_6': [0], '2_7': [2]} | ['year', 'class', 'tyres', 'team', 'co - drivers', 'laps', 'pos'] | [['1989', 'c1', 'd', 'nissan motorsports', 'mark blundell martin donnelly', '5', 'dnf'], ['1990', 'c1', 'd', 'nissan motorsports international', 'mark blundell gianfranco brancatelli', '142', 'dnf'], ['1997', 'gt1', 'd', 'newcastle united lister', 'thomas erdos mark skaife', '77', 'dnf'], ['2001', 'lmp675', 'm', 'mg sp... |
2008 - 09 in scottish football | https://en.wikipedia.org/wiki/2008%E2%80%9309_in_Scottish_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17327458-19.html.csv | majority | the majority of scottish football games are recorded by the bbc . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'bbc', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'report', 'bbc'], 'result': True, 'ind': 0, 'tointer': 'for the report records of all rows , all of them fuzzily match to bbc .', 'tostr': 'all_eq { all_rows ; report ; bbc } = true'} | all_eq { all_rows ; report ; bbc } = true | for the report records of all rows , all of them fuzzily match to bbc . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'report_3': 3, 'bbc_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'report_3': 'report', 'bbc_4': 'bbc'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'report_3': [0], 'bbc_4': [0]} | ['date', 'venue', 'score', 'competition', 'report'] | [['20 august', 'hampden park , glasgow ( h )', '0 - 0', 'friendly', 'bbc sport'], ['6 september', 'skopje city stadium , skopje ( a )', '0 - 1', 'wcq ( 9 )', 'bbc sport'], ['10 september', 'laugardalsvöllur , reykjavík ( a )', '2 - 1', 'wcq ( 9 )', 'bbc sport'], ['11 october', 'hampden park , glasgow ( h )', '0 - 0', '... |
list of olympic medalists in athletics ( men ) | https://en.wikipedia.org/wiki/List_of_Olympic_medalists_in_athletics_%28men%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22355-26.html.csv | majority | most of the men 's olympic medalists did not win any bronze medals . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'bronze', '0'], 'result': True, 'ind': 0, 'tointer': 'for the bronze records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; bronze ; 0 } = true'} | most_eq { all_rows ; bronze ; 0 } = true | for the bronze records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'bronze_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'bronze_3': 'bronze', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'bronze_3': [0], '0_4': [0]} | ['rank', 'athlete', 'nation', 'olympics', 'gold', 'silver', 'bronze', 'total ( min 2 medals )'] | [['1', 'lee calhoun', 'united states ( usa )', '1952 - 1956', '2', '0', '0', '2'], ['1', 'roger kingdom', 'united states ( usa )', '1984 - 1988', '2', '0', '0', '2'], ['3', 'sydney atkinson', 'south africa ( rsa )', '1924 - 1928', '1', '1', '0', '2'], ['3', 'guy drut', 'france ( fra )', '1972 - 1976', '1', '1', '0', '2... |
list of whose line is it anyway ? uk episodes | https://en.wikipedia.org/wiki/List_of_Whose_Line_Is_It_Anyway%3F_UK_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14934885-7.html.csv | count | tony slattery was performer 4 on whose line is it anyway ? uk a total of seven times . | {'scope': 'all', 'criterion': 'equal', 'value': 'tony slattery', 'result': '7', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'performer 4', 'tony slattery'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose performer 4 record fuzzily matches to tony slattery .', 'tostr': 'filter_eq { all_rows ; performer 4 ; tony slattery }'}], 'resul... | eq { count { filter_eq { all_rows ; performer 4 ; tony slattery } } ; 7 } = true | select the rows whose performer 4 record fuzzily matches to tony slattery . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'performer 4_5': 5, 'tony slattery_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'performer 4_5': 'performer 4', 'tony slattery_6': 'tony slattery', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'performer 4_5': [0], 'tony slattery_6': [0], '7_7': [2]} | ['date', 'episode', 'performer 1', 'performer 2', 'performer 3', 'performer 4'] | [['1 july 1994', '1', 'stephen frost', 'colin mochrie', 'ryan stiles', 'tony slattery'], ['8 july 1994', '2', 'josie lawrence', 'ryan stiles', 'greg proops', 'mike mcshane'], ['15 july 1994', '3', 'stephen frost', 'colin mochrie', 'ryan stiles', 'tony slattery'], ['22 july 1994', '4', 'mike mcshane', 'greg proops', 'ry... |
2009 nrl season | https://en.wikipedia.org/wiki/2009_NRL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17678435-10.html.csv | majority | the majority of the games featured a losing team that scored more than 10 points . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'score', '10'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them are greater than 10 .', 'tostr': 'most_greater { all_rows ; score ; 10 } = true'} | most_greater { all_rows ; score ; 10 } = true | for the score records of all rows , most of them are greater than 10 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, '10_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', '10_4': '10'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], '10_4': [0]} | ['team', 'opponent', 'score', 'venue', 'round'] | [['brisbane broncos', 'penrith panthers', '58 - 24', 'suncorp stadium', 'round 23'], ['wests tigers', 'cronulla sharks', '56 - 10', 'toyota stadium', 'round 23'], ['canberra raiders', 'brisbane broncos', '56 - 0', 'canberra stadium', 'round 21'], ['wests tigers', 'south sydney rabbitohs', '54 - 20', 'anz stadium', 'rou... |
united states house of representatives elections , 1972 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1972 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341707-15.html.csv | unique | roman c pucinski was the only incumbent who decided to retire their house seat to run for the us senate . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'retired to run for us senate', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'retired to run for us senate'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to retired to run for us senate .', 'tostr': 'filter_eq { all_rows ; result ; retired to ... | and { only { filter_eq { all_rows ; result ; retired to run for us senate } } ; eq { hop { filter_eq { all_rows ; result ; retired to run for us senate } ; incumbent } ; roman c pucinski } } = true | select the rows whose result record fuzzily matches to retired to run for us senate . there is only one such row in the table . the incumbent record of this unqiue row is roman c pucinski . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'retired to run for us senate_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'roman c pucinski_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'retired to run for us senate_8': 'retired to run for us senate', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'roman c pucinski_10': 'roman c pucinski'... | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'retired to run for us senate_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'roman c pucinski_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['illinois 1', 'ralph h metcalfe', 'democratic', '1970', 're - elected', 'ralph h metcalfe ( d ) 91.4 % louis coggs ( r ) 8.6 %'], ['illinois 4', 'ed derwinski', 'republican', '1958', 're - elected', "ed derwinski ( r ) 70.5 % c f ' bob ' dore ( d ) 29.5 %"], ['illinois 10', 'abner j mikva redistricted from the 2nd di... |
1995 pga tour | https://en.wikipedia.org/wiki/1995_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14611590-4.html.csv | comparative | of the players listed as winners on the 1995 pga tour nick price had more wins than fred couples . | {'row_1': '4', 'row_2': '5', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'nick price'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to nick price .', 'tostr': 'filter_eq { all_rows ; player ; nick price }'}, 'wins'], 'result': None,... | greater { hop { filter_eq { all_rows ; player ; nick price } ; wins } ; hop { filter_eq { all_rows ; player ; fred couples } ; wins } } = true | select the rows whose player record fuzzily matches to nick price . take the wins record of this row . select the rows whose player record fuzzily matches to fred couples . take the wins record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'nick price_8': 8, 'wins_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'fred couples_12': 12, 'wins_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'nick price_8': 'nick price', 'wins_9': 'wins', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'fred cou... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'nick price_8': [0], 'wins_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'fred couples_12': [1], 'wins_13': [3]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'greg norman', 'australia', '9592829', '17'], ['2', 'tom kite', 'united states', '9337998', '19'], ['3', 'payne stewart', 'united states', '7389479', '9'], ['4', 'nick price', 'zimbabwe', '7338119', '15'], ['5', 'fred couples', 'united states', '7188408', '11']] |
germany | https://en.wikipedia.org/wiki/Germany | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11867-3.html.csv | comparative | the revenue of metro ag is lower than the revenue of daimler ag . | {'row_1': '7', 'row_2': '3', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'metro ag'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to metro ag .', 'tostr': 'filter_eq { all_rows ; name ; metro ag }'}, 'revenue ( mil )'], 'result': None, 'in... | less { hop { filter_eq { all_rows ; name ; metro ag } ; revenue ( mil ) } ; hop { filter_eq { all_rows ; name ; daimler ag } ; revenue ( mil ) } } = true | select the rows whose name record fuzzily matches to metro ag . take the revenue ( mil ) record of this row . select the rows whose name record fuzzily matches to daimler ag . take the revenue ( mil ) 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, 'metro ag_8': 8, 'revenue (mil)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'daimler ag_12': 12, 'revenue (mil)_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', 'metro ag_8': 'metro ag', 'revenue (mil)_9': 'revenue ( mil )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'daimle... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'metro ag_8': [0], 'revenue (mil)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'daimler ag_12': [1], 'revenue (mil)_13': [3]} | ['rank', 'name', 'headquarters', 'revenue ( mil )', 'profit ( mil )', 'employees ( world )'] | [['0 1', 'volkswagen ag', 'wolfsburg', '159.000', '15.800', '502 ,000'], ['0 2', 'eon se', 'düsseldorf', '113.000', '1.900', '79 ,000'], ['0 3', 'daimler ag', 'stuttgart', '107.000', '6.000', '271 ,000'], ['0 4', 'siemens ag', 'berlin , münchen', '74.000', '6.300', '360 ,000'], ['0 5', 'basf se', 'ludwigshafen am rhein... |
woden valley | https://en.wikipedia.org/wiki/Woden_Valley | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1174162-1.html.csv | unique | the only place in woden valley that had less than one thousand inhabitants was o ' malley . | {'scope': 'all', 'row': '9', 'col': '2', 'col_other': '1', 'criterion': 'less_than', 'value': '1000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'population ( in 2008 )', '1000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose population ( in 2008 ) record is less than 1000 .', 'tostr': 'filter_less { all_rows ; population ( in 2008 ) ; 1000 }'}], 'resul... | and { only { filter_less { all_rows ; population ( in 2008 ) ; 1000 } } ; eq { hop { filter_less { all_rows ; population ( in 2008 ) ; 1000 } ; suburb } ; o'malley } } = true | select the rows whose population ( in 2008 ) record is less than 1000 . there is only one such row in the table . the suburb record of this unqiue row is o'malley . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'population (in 2008)_7': 7, '1000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'suburb_9': 9, "o'malley_10": 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'population (in 2008)_7': 'population ( in 2008 )', '1000_8': '1000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'suburb_9': 'suburb', "o'malley_10": "o'malley"} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'population (in 2008)_7': [0], '1000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'suburb_9': [2], "o'malley_10": [3]} | ['suburb', 'population ( in 2008 )', 'median age ( in 2006 )', 'mean household size ( in 2006 )', 'area ( km square )', 'density ( / km square )', 'date first settled as a suburb', 'gazetted as a division name'] | [['chifley', '2325', '36 years', '2.3 persons', '1.6', '1453', '1966', '12 may 1966'], ['curtin', '5133', '41 years', '2.5 persons', '4.8', '1069', '1962', '20 september 1962'], ['farrer', '3360', '41 years', '2.7 persons', '2.1', '1600', '1967', '12 may 1966'], ['garran', '3175', '39 years', '2.5 persons', '2.7', '117... |
1976 - 77 segunda división | https://en.wikipedia.org/wiki/1976%E2%80%9377_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12239755-2.html.csv | comparative | sporting de gijon got more points than cadiz cf in the 1976 - 77 segunda división . | {'row_1': '1', 'row_2': '2', 'col': '4', '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', 'club', 'sporting de gijón'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to sporting de gijón .', 'tostr': 'filter_eq { all_rows ; club ; sporting de gijón }'}, 'points']... | greater { hop { filter_eq { all_rows ; club ; sporting de gijón } ; points } ; hop { filter_eq { all_rows ; club ; cádiz cf } ; points } } = true | select the rows whose club record fuzzily matches to sporting de gijón . take the points record of this row . select the rows whose club record fuzzily matches to cádiz cf . take the points 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, 'club_7': 7, 'sporting de gijón_8': 8, 'points_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'club_11': 11, 'cádiz cf_12': 12, 'points_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', 'club_7': 'club', 'sporting de gijón_8': 'sporting de gijón', 'points_9': 'points', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'club_11': 'club',... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'club_7': [0], 'sporting de gijón_8': [0], 'points_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'club_11': [1], 'cádiz cf_12': [1], 'points_13': [3]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'sporting de gijón', '38', '47 + 9', '18', '11', '9', '62', '35', '+ 27'], ['2', 'cádiz cf', '38', '46 + 8', '17', '12', '9', '60', '42', '+ 18'], ['3', 'rayo vallecano', '38', '45 + 7', '17', '11', '10', '46', '34', '+ 12'], ['4', 'real jaén', '38', '43 + 5', '15', '13', '10', '42', '32', '+ 10'], ['5', 'real o... |
2009 - 10 fis ski jumping world cup | https://en.wikipedia.org/wiki/2009%E2%80%9310_FIS_Ski_Jumping_World_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24489942-10.html.csv | count | there are three jumpers that are from austria . | {'scope': 'all', 'criterion': 'equal', 'value': 'austria', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'austria'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to austria .', 'tostr': 'filter_eq { all_rows ; nationality ; austria }'}], 'result': '3', 'ind': 1,... | eq { count { filter_eq { all_rows ; nationality ; austria } } ; 3 } = true | select the rows whose nationality record fuzzily matches to austria . 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, 'nationality_5': 5, 'austria_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', 'nationality_5': 'nationality', 'austria_6': 'austria', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nationality_5': [0], 'austria_6': [0], '3_7': [2]} | ['rank', 'name', 'nationality', '1st ( m )', '2nd ( m )', 'points', 'overall fht points', 'overall wc points ( rank )'] | [['1', 'thomas morgenstern', 'austria', '133.0', '136.0', '264.7', '987.1 ( 6 )', '440 ( 4 )'], ['2', 'janne ahonen', 'finland', '134.0', '133.5', '264.0', '1013.9 ( 2 )', '350 ( 7 )'], ['3', 'simon ammann', 'switzerland', '136.0', '131.5', '261.5', '1008.3 ( 5 )', '669 ( 1 )'], ['4', 'wolfgang loitzl', 'austria', '130... |
1997 - 98 toronto raptors season | https://en.wikipedia.org/wiki/1997%E2%80%9398_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13619053-9.html.csv | aggregation | during april of the 1997 - 98 toronto raptors season , toronto scored an average of almost 100 points per game . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '100', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '100', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '100'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 100 } = true', 'tointer': 'the average of the score record of all rows is 100 .'} | round_eq { avg { all_rows ; score } ; 100 } = true | the average of the score record of all rows is 100 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '100_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '100_5': '100'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '100_5': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['72', 'april 1', 'atlanta', 'l 91 - 105 ( ot )', 'doug christie , gary trent ( 14 )', 'marcus camby , tracy mcgrady ( 9 )', 'doug christie ( 3 )', 'georgia dome 10441', '15 - 57'], ['73', 'april 3', 'washington', 'l 112 - 120 ( ot )', 'dee brown ( 30 )', 'gary trent ( 10 )', 'dee brown ( 6 )', 'mci center 18324', '15... |
television in thailand | https://en.wikipedia.org/wiki/Television_in_Thailand | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18987481-3.html.csv | comparative | modernine tv had a higher market share of television in thailand than nbt in 2005 . | {'row_1': '4', 'row_2': '5', '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', 'tv station ( operator )', 'modernine tv'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tv station ( operator ) record fuzzily matches to modernine tv .', 'tostr': 'filter_eq { all_rows ; tv station ... | greater { hop { filter_eq { all_rows ; tv station ( operator ) ; modernine tv } ; 2005 } ; hop { filter_eq { all_rows ; tv station ( operator ) ; nbt } ; 2005 } } = true | select the rows whose tv station ( operator ) record fuzzily matches to modernine tv . take the 2005 record of this row . select the rows whose tv station ( operator ) record fuzzily matches to nbt . take the 2005 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, 'tv station (operator)_7': 7, 'modernine tv_8': 8, '2005_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'tv station (operator)_11': 11, 'nbt_12': 12, '2005_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', 'tv station (operator)_7': 'tv station ( operator )', 'modernine tv_8': 'modernine tv', '2005_9': '2005', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_row... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'tv station (operator)_7': [0], 'modernine tv_8': [0], '2005_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'tv station (operator)_11': [1], 'nbt_12': [1], '2005_13': [3]} | ['tv station ( operator )', '2005', '2006', '2007', '2008', '2009', '2010', '2011 1h'] | [['bbtv ch7', '42.4', '41.3', '42.0', '44.7', '45.4', '43.8', '47.5'], ['tv3', '24.5', '25.6', '29.5', '26.8', '27.7', '29.5', '29.0'], ['tv5', '8.1', '7.3', '6.7', '7.6', '8.6', '8.0', '6.9'], ['modernine tv', '10.3', '10.2', '9.2', '9.6', '9.9', '9.7', '9.2'], ['nbt', '2.9', '3.0', '2.4', '4.9', '3.4', '3.4', '2.4'],... |
list of intel atom microprocessors | https://en.wikipedia.org/wiki/List_of_Intel_Atom_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16729930-17.html.csv | majority | all of the atom microprocessors in this list were released on september 14 , 2010 . | {'scope': 'all', 'col': '10', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'september 14 , 2010', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'release date', 'september 14 , 2010'], 'result': True, 'ind': 0, 'tointer': 'for the release date records of all rows , all of them fuzzily match to september 14 , 2010 .', 'tostr': 'all_eq { all_rows ; release date ; september 14 , 2010 } = true'} | all_eq { all_rows ; release date ; september 14 , 2010 } = true | for the release date records of all rows , all of them fuzzily match to september 14 , 2010 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'release date_3': 3, 'september 14, 2010_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'release date_3': 'release date', 'september 14, 2010_4': 'september 14 , 2010'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'release date_3': [0], 'september 14, 2010_4': [0]} | ['model number', 'sspec number', 'frequency', 'gpu frequency', 'l2 cache', 'i / o bus', 'memory', 'voltage', 'socket', 'release date', 'part number ( s )', 'release price ( usd )'] | [['atom e620', 'slh56 ( b0 ) slj32 ( b1 )', '600 mhz', '320 mhz', '512 kb', 'pcie', '1 ddr2 - 800', '0.8 - 1.175 v', 'fc - bga 676', 'september 14 , 2010', 'ct80618005844aa', '19'], ['atom e620t', 'slh5n ( b0 ) slj36 ( b1 )', '600 mhz', '320 mhz', '512 kb', 'pcie', '1 ddr2 - 800', '0.8 - 1.175 v', 'fc - bga 676', 'sept... |
1965 vfl season | https://en.wikipedia.org/wiki/1965_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10788451-13.html.csv | aggregation | the average crowd attendance of games in the 1965 vfl season was 20301 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '20301', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '20301', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '20301'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 20301 } = true', 'tointer': 'the average of the crowd record of all rows is 20301 .'} | round_eq { avg { all_rows ; crowd } ; 20301 } = true | the average of the crowd record of all rows is 20301 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '20301_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '20301_5': '20301'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '20301_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '18.9 ( 117 )', 'south melbourne', '6.12 ( 48 )', 'moorabbin oval', '18709', '24 july 1965'], ['fitzroy', '7.13 ( 55 )', 'footscray', '6.6 ( 42 )', 'brunswick street oval', '7456', '24 july 1965'], ['north melbourne', '11.15 ( 81 )', 'melbourne', '9.6 ( 60 )', 'city of coburg oval', '8312', '24 july 1965'... |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-37.html.csv | majority | in the us house of representatives elections of 1954 , most of the pennsylvania incumbents were reelected . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 're - elected', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to re - elected .', 'tostr': 'most_eq { all_rows ; result ; re - elected } = true'} | most_eq { all_rows ; result ; re - elected } = true | for the result records of all rows , most of them fuzzily match to re - elected . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 're - elected_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 're - elected_4': 're - elected'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 're - elected_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['pennsylvania 6', 'hugh scott', 'republican', '1946', 're - elected', 'hugh scott ( r ) 50.6 % alexander hemphill ( d ) 49.4 %'], ['pennsylvania 8', 'karl c king', 'republican', '1951', 're - elected', 'karl c king ( r ) 51.2 % john p fullam ( d ) 48.8 %'], ['pennsylvania 9', 'paul b dague', 'republican', '1946', 're... |
casualty ( series 5 ) | https://en.wikipedia.org/wiki/Casualty_%28series_5%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27208817-1.html.csv | count | 3 episodes in series 5 of casualty were directed by alan wareing . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'alan wareing', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'alan wareing'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to alan wareing .', 'tostr': 'filter_eq { all_rows ; director ; alan wareing }'}], 'result': '3', 'in... | eq { count { filter_eq { all_rows ; director ; alan wareing } } ; 3 } = true | select the rows whose director record fuzzily matches to alan wareing . 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, 'director_5': 5, 'alan wareing_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', 'director_5': 'director', 'alan wareing_6': 'alan wareing', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'director_5': [0], 'alan wareing_6': [0], '3_7': [2]} | ['episode no episode no refers to the episodes number in the overall series , whereas series no refers to the episodes number in this particular series', 'series no', 'episode', 'director', 'writer', 'original airdate'] | [['53', '1', 'penalty', 'michael owen morris', 'ginnie hole', '7 september 1990'], ['54', '2', 'results', 'andrew morgan', 'ben aaronovitch', '14 september 1990'], ['55', '3', 'close to home', 'alan wareing', 'jim hill', '21 september 1990'], ['56', '4', 'street life', 'jim hill', 'ian briggs', '28 september 1990'], ['... |
soo line locomotives | https://en.wikipedia.org/wiki/Soo_Line_locomotives | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17248696-6.html.csv | comparative | a higher number of f-20 soo line locomotives were made than f-22 soo line locomotives . | {'row_1': '13', 'row_2': '15', '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', 'class', 'f - 20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose class record fuzzily matches to f - 20 .', 'tostr': 'filter_eq { all_rows ; class ; f - 20 }'}, 'quantity made'], 'result': None, 'ind'... | greater { hop { filter_eq { all_rows ; class ; f - 20 } ; quantity made } ; hop { filter_eq { all_rows ; class ; f - 22 } ; quantity made } } = true | select the rows whose class record fuzzily matches to f - 20 . take the quantity made record of this row . select the rows whose class record fuzzily matches to f - 22 . take the quantity made 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, 'class_7': 7, 'f - 20_8': 8, 'quantity made_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'class_11': 11, 'f - 22_12': 12, 'quantity made_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', 'class_7': 'class', 'f - 20_8': 'f - 20', 'quantity made_9': 'quantity made', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'class_11': 'class', 'f ... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'class_7': [0], 'f - 20_8': [0], 'quantity made_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'class_11': [1], 'f - 22_12': [1], 'quantity made_13': [3]} | ['class', 'wheel arrangement', 'fleet number ( s )', 'manufacturer', 'year made', 'quantity made', 'quantity preserved'] | [['2 - 8 - 0 - ooooo - consolidation', '2 - 8 - 0 - ooooo - consolidation', '2 - 8 - 0 - ooooo - consolidation', '2 - 8 - 0 - ooooo - consolidation', '2 - 8 - 0 - ooooo - consolidation', '2 - 8 - 0 - ooooo - consolidation', '2 - 8 - 0 - ooooo - consolidation'], ['f - 1', '2 - 8 - 0', '403 - 405 , 407 - 412', 'schenecta... |
1984 - 85 philadelphia flyers season | https://en.wikipedia.org/wiki/1984%E2%80%9385_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14208855-10.html.csv | comparative | in the game of the 18 th of april against the new york islanders the philadelphia flyers defense was more successful than on the 21st of april . | {'row_1': '1', 'row_2': '2', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'april 18'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to april 18 .', 'tostr': 'filter_eq { all_rows ; date ; april 18 }'}, 'score'], 'result': None, 'ind': 2, 'to... | less { hop { filter_eq { all_rows ; date ; april 18 } ; score } ; hop { filter_eq { all_rows ; date ; april 21 } ; score } } = true | select the rows whose date record fuzzily matches to april 18 . take the score record of this row . select the rows whose date record fuzzily matches to april 21 . take the score 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, 'date_7': 7, 'april 18_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'april 21_12': 12, 'score_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', 'date_7': 'date', 'april 18_8': 'april 18', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'april 21_12': 'april 21'... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'april 18_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'april 21_12': [1], 'score_13': [3]} | ['game', 'date', 'opponent', 'score', 'series'] | [['1', 'april 18', 'new york islanders', '3 - 0', 'flyers lead 1 - 0'], ['2', 'april 21', 'new york islanders', '5 - 2', 'flyers lead 2 - 0'], ['3', 'april 23', 'new york islanders', '5 - 3', 'flyers lead 3 - 0'], ['4', 'april 25', 'new york islanders', '2 - 6', 'flyers lead 3 - 1'], ['5', 'april 28', 'new york islande... |
stefan johansson | https://en.wikipedia.org/wiki/Stefan_Johansson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226329-2.html.csv | unique | 1983 was the only year that stefan johansson drove as an entrant with the spirit racing team . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'spirit racing', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'entrant', 'spirit racing'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose entrant record fuzzily matches to spirit racing .', 'tostr': 'filter_eq { all_rows ; entrant ; spirit racing }'}], 'result': True, 'i... | and { only { filter_eq { all_rows ; entrant ; spirit racing } } ; eq { hop { filter_eq { all_rows ; entrant ; spirit racing } ; year } ; 1983 } } = true | select the rows whose entrant record fuzzily matches to spirit racing . there is only one such row in the table . the year record of this unqiue row is 1983 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'entrant_7': 7, 'spirit racing_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1983_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'entrant_7': 'entrant', 'spirit racing_8': 'spirit racing', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1983_10': '1983'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'entrant_7': [0], 'spirit racing_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1983_10': [3]} | ['year', 'entrant', 'chassis', 'engine', 'pts'] | [['1980', 'shadow cars', 'shadow dn11', 'ford cosworth dfv v8', '0'], ['1983', 'spirit racing', 'spirit 201c', 'honda v6 ( t / c )', '0'], ['1984', 'tyrrell racing organisation', 'tyrrell 012', 'ford cosworth dfy v8', '3'], ['1984', 'toleman group motorsport', 'toleman tg184', 'hart straight - 4 ( t / c )', '3'], ['198... |
2011 icf canoe sprint world championships | https://en.wikipedia.org/wiki/2011_ICF_Canoe_Sprint_World_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18771517-7.html.csv | aggregation | at the 2011 icf canoe sprint world championships there were a total of 8 golds awarded . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'gold'], 'result': '8', 'ind': 0, 'tostr': 'sum { all_rows ; gold }'}, '8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; gold } ; 8 } = true', 'tointer': 'the sum of the gold record of all rows is 8 .'} | round_eq { sum { all_rows ; gold } ; 8 } = true | the sum of the gold record of all rows is 8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'gold_4': 4, '8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '8_5': '8'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'gold_4': [0], '8_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'canada', '2', '1', '0', '3'], ['2', 'brazil', '2', '0', '1', '3'], ['3', 'great britain', '1', '1', '1', '3'], ['4', 'hungary', '1', '0', '1', '2'], ['5', 'austria', '1', '0', '0', '1'], ['5', 'romania', '1', '0', '0', '1'], ['7', 'germany', '0', '1', '1', '2'], ['7', 'italy', '0', '1', '1', '2'], ['7', 'poland... |
2008 thailand national games | https://en.wikipedia.org/wiki/2008_Thailand_National_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14892957-1.html.csv | unique | bangkok was the only province to receive more than 100 gold medals . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'greater_than', 'value': '100', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'gold', '100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is greater than 100 .', 'tostr': 'filter_greater { all_rows ; gold ; 100 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_grea... | and { only { filter_greater { all_rows ; gold ; 100 } } ; eq { hop { filter_greater { all_rows ; gold ; 100 } ; province } ; bangkok } } = true | select the rows whose gold record is greater than 100 . there is only one such row in the table . the province record of this unqiue row is bangkok . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'gold_7': 7, '100_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'province_9': 9, 'bangkok_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'gold_7': 'gold', '100_8': '100', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'province_9': 'province', 'bangkok_10': 'bangkok'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'gold_7': [0], '100_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'province_9': [2], 'bangkok_10': [3]} | ['rank', 'province', 'gold', 'silver', 'bronze', 'total'] | [['1', 'bangkok', '125', '90', '76', '291'], ['2', 'chonburi', '44', '34', '48', '126'], ['3', 'chiang mai', '37', '34', '41', '112'], ['4', 'phitsanulok', '24', '15', '31', '70'], ['5', 'suphan buri', '21', '27', '24', '72'], ['6', 'nakhon ratchasima', '21', '21', '31', '73'], ['7', 'nakhon si thammarat', '11', '10', ... |
delaware valley collegiate hockey conference | https://en.wikipedia.org/wiki/Delaware_Valley_Collegiate_Hockey_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16432543-1.html.csv | comparative | the shippensburg university was established earlier than the penn state harrisburg . | {'row_1': '7', 'row_2': '4', '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', 'institution', 'shippensburg university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record fuzzily matches to shippensburg university .', 'tostr': 'filter_eq { all_rows ; institution ; sh... | less { hop { filter_eq { all_rows ; institution ; shippensburg university } ; established } ; hop { filter_eq { all_rows ; institution ; penn state harrisburg } ; established } } = true | select the rows whose institution record fuzzily matches to shippensburg university . take the established record of this row . select the rows whose institution record fuzzily matches to penn state harrisburg . take the established 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, 'institution_7': 7, 'shippensburg university_8': 8, 'established_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'institution_11': 11, 'penn state harrisburg_12': 12, 'established_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', 'institution_7': 'institution', 'shippensburg university_8': 'shippensburg university', 'established_9': 'established', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': ... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'institution_7': [0], 'shippensburg university_8': [0], 'established_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'institution_11': [1], 'penn state harrisburg_12': [1], 'established_13': [3]} | ['institution', 'location', 'nickname', 'enrollment', 'established'] | [['university of delaware', 'newark , de', 'blue hens', '19391', '1743'], ['dickinson college', 'carlisle , pa', 'red devils', '2300', '1773'], ["mount saint mary 's university", 'emmitsburg , md', 'mountaineers', '2100', '1808'], ['penn state harrisburg', 'lower swatara township , pa', 'nittany lions', '4700', '1966']... |
1971 icf canoe sprint world championships | https://en.wikipedia.org/wiki/1971_ICF_Canoe_Sprint_World_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18567469-4.html.csv | superlative | the soviet union won the most medals overall in the 1971 icf canoe sprint world championships . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'nation'], 'result': 'soviet union', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; nation }'}, 'soviet union'], 'result': True, 'ind': 2... | eq { hop { argmax { all_rows ; total } ; nation } ; soviet union } = true | select the row whose total record of all rows is maximum . the nation record of this row is soviet union . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'nation_6': 6, 'soviet union_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'nation_6': 'nation', 'soviet union_7': 'soviet union'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'nation_6': [1], 'soviet union_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'soviet union', '7', '2', '6', '15'], ['2', 'hungary', '4', '5', '2', '11'], ['3', 'romania', '2', '2', '5', '9'], ['4', 'west germany', '2', '2', '1', '5'], ['5', 'east germany', '1', '1', '2', '4'], ['6', 'sweden', '1', '1', '0', '2'], ['7', 'bulgaria', '0', '0', '2', '2'], ['8', 'poland', '1', '0', '0', '1'],... |
1959 vfl season | https://en.wikipedia.org/wiki/1959_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10775038-8.html.csv | unique | only the game between fitzroy and collingwood was played at the brunswick street oval . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '1,3', 'criterion': 'equal', 'value': 'brunswick street oval', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'brunswick street oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to brunswick street oval .', 'tostr': 'filter_eq { all_rows ; venue ; brunswick street oval }'}], ... | and { only { filter_eq { all_rows ; venue ; brunswick street oval } } ; and { eq { hop { filter_eq { all_rows ; venue ; brunswick street oval } ; home team } ; fitzroy } ; eq { hop { filter_eq { all_rows ; venue ; brunswick street oval } ; away team } ; collingwood } } } = true | select the rows whose venue record fuzzily matches to brunswick street oval . there is only one such row in the table . the home team record of this unqiue row is fitzroy . the away team record of this unqiue row is collingwood . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'venue_10': 10, 'brunswick street oval_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'home team_12': 12, 'fitzroy_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'away team_14': 14, 'collingwood_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'venue_10': 'venue', 'brunswick street oval_11': 'brunswick street oval', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'home team_12': 'home team', 'fitzroy_13': 'fitzroy', 'str_eq_5': '... | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'venue_10': [0], 'brunswick street oval_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'home team_12': [2], 'fitzroy_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'away team_14': [4], 'collingwood_15': [5]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '4.13 ( 37 )', 'richmond', '9.9 ( 63 )', 'western oval', '11533', '13 june 1959'], ['north melbourne', '12.12 ( 84 )', 'hawthorn', '8.6 ( 54 )', 'arden street oval', '12500', '13 june 1959'], ['fitzroy', '5.10 ( 40 )', 'collingwood', '3.12 ( 30 )', 'brunswick street oval', '17632', '13 june 1959'], ['sou... |
b " the women 's ashes " | https://en.wikipedia.org/wiki/The_Women%27s_Ashes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2554479-2.html.csv | count | 7 series of the the women 's ashes competition resulted in a draw . | {'scope': 'all', 'criterion': 'equal', 'value': 'drawn', 'result': '7', 'col': '9', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'series result', 'drawn'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose series result record fuzzily matches to drawn .', 'tostr': 'filter_eq { all_rows ; series result ; drawn }'}], 'result': '7', 'ind': 1,... | eq { count { filter_eq { all_rows ; series result ; drawn } } ; 7 } = true | select the rows whose series result record fuzzily matches to drawn . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'series result_5': 5, 'drawn_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'series result_5': 'series result', 'drawn_6': 'drawn', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'series result_5': [0], 'drawn_6': [0], '7_7': [2]} | ['series', 'season', 'played in', 'first match', 'tests played ( sched )', 'tests won by australia', 'tests won by england', 'tests drawn', 'series result', 'holder at series end'] | [['1', '1934 - 35', 'australia', '28 december 1934', '3', '0', '2', '1', 'england', 'england'], ['2', '1937', 'england', '12 june 1937', '3', '1', '1', '1', 'drawn', 'england'], ['3', '1949 - 50', 'australia', '15 january 1949', '3', '1', '0', '2', 'australia', 'australia'], ['4', '1951', 'england', '16 june 1951', '3'... |
1989 pga championship | https://en.wikipedia.org/wiki/1989_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18135029-1.html.csv | aggregation | the avergae total for all players in the 1989 pga championship was 289.5 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '289.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '289.5', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '289.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 289.5 } = true', 'tointer': 'the average of the total record of all rows is 289.5 .'} | round_eq { avg { all_rows ; total } ; 289.5 } = true | the average of the total record of all rows is 289.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '289.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '289.5_5': '289.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '289.5_5': [1]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['jeff sluman', 'united states', '1988', '284', '- 4', 't24'], ['jack nicklaus', 'united states', '1963 , 1971 , 1973 1975 , 1980', '285', '- 3', 't27'], ['larry nelson', 'united states', '1981 , 1987', '288', 'e', 't46'], ['raymond floyd', 'united states', '1969 , 1982', '288', 'e', 't46'], ['hubert green', 'united s... |
nikon coolpix series | https://en.wikipedia.org/wiki/Nikon_Coolpix_series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1017391-7.html.csv | aggregation | from nikon coolpix series models p1 to p7100 , released from september 1 , 2005 to august 16 , 2011 , the sensor resolution average is 9.88125 megapixels . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '9.88125', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'sensor res , size'], 'result': '9.88125', 'ind': 0, 'tostr': 'avg { all_rows ; sensor res , size }'}, '9.88125'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; sensor res , size } ; 9.88125 } = true', 'tointer': 'the average of the se... | round_eq { avg { all_rows ; sensor res , size } ; 9.88125 } = true | the average of the sensor res , size record of all rows is 9.88125 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'sensor res , size_4': 4, '9.88125_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'sensor res , size_4': 'sensor res , size', '9.88125_5': '9.88125'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'sensor res , size_4': [0], '9.88125_5': [1]} | ['model', 'release date', 'sensor res , size', 'lens ( 35 mmequiv ) zoom , aperture', 'screen size , pixels', 'dimensions whd ( mm )', 'weight'] | [['p1', 'sep 1 , 2005', '8.0 mp 32642448 1 / 1.8', '36 - 126 mm ( 3.5 ) f / 2.7 - 5.2', '2.5 110000', '916039', '170 g ( w / out batt )'], ['p2', 'sep 1 , 2005', '5.0 mp 25921944 1 / 1.8', '36 - 126 mm ( 3.5 ) f / 2.7 - 5.2', '2.5 110000', '916039', '170 g ( w / out batt )'], ['p3', 'feb 21 , 2006', '8.1 mp 32642448 1 ... |
2008 - 09 temple owls men 's basketball team | https://en.wikipedia.org/wiki/2008%E2%80%9309_Temple_Owls_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30054758-3.html.csv | ordinal | the december 20 game against kansas was the 4th earliest game played by the 2008-09 temple owls . | {'row': '4', 'col': '2', 'order': '4', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'date', '4'], 'result': 'december 20', 'ind': 0, 'tostr': 'nth_min { all_rows ; date ; 4 }', 'tointer': 'the 4th minimum date record of all rows is december 20 .'}, 'december 20'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min ... | and { eq { nth_min { all_rows ; date ; 4 } ; december 20 } ; eq { hop { nth_argmin { all_rows ; date ; 4 } ; team } ; kansas } } = true | the 4th minimum date record of all rows is december 20 . the team record of the row with 4th minimum date record is kansas . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'date_8': 8, '4_9': 9, 'december 20_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'date_12': 12, '4_13': 13, 'team_14': 14, 'kansas_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'date_8': 'date', '4_9': '4', 'december 20_10': 'december 20', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'date_12': 'date', '4_13': '4', 'team_14': 'team', 'k... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'date_8': [0], '4_9': [0], 'december 20_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'date_12': [2], '4_13': [2], 'team_14': [3], 'kansas_15': [4]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['6', 'december 3', 'miami ( oh )', 'l 68 - 52', 'sergio olmos - 12', 'brooks - 6', 'inge - 5', 'liacouras center , philadelphia , pa ( 5029 )', '3 - 3'], ['7', 'december 6', 'penn state', 'w 65 - 59', 'inge - 19', 'allen - 10', 'inge - 6', 'bryce jordan center , state college , pa ( 9833 )', '4 - 3'], ['8', 'december... |
1980 buffalo bills season | https://en.wikipedia.org/wiki/1980_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16677887-2.html.csv | ordinal | in the 1980 buffalo bills season , the 2nd highest attendance was at the game on september 7th . | {'row': '1', 'col': '9', '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', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'date'], 'result': 'sept 7', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; date }'}, 'sept 7'], ... | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; sept 7 } = true | select the row whose attendance record of all rows is 2nd maximum . the date record of this row is sept 7 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'date_7': 7, 'sept 7_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'date_7': 'date', 'sept 7_8': 'sept 7'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'date_7': [1], 'sept 7_8': [2]} | ['game', 'date', 'opponent', 'result', 'bills points', 'opponents', 'bills first downs', 'record', 'attendance'] | [['1', 'sept 7', 'miami dolphins', 'win', '17', '7', '22', '1 - 0', '79598'], ['2', 'sept 14', 'new york jets', 'win', '20', '10', '22', '2 - 0', '65315'], ['3', 'sept 21', 'new orleans saints', 'win', '35', '26', '26', '3 - 0', '51154'], ['4', 'sept 28', 'oakland raiders', 'win', '24', '7', '25', '4 - 0', '77259'], ['... |
2007 - 08 tampa bay lightning season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Tampa_Bay_Lightning_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11766617-3.html.csv | count | in the 2007 - 08 tampa bay lightning season , when tampa bay was the home team , there were 4 games where attendance was over 19000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '19,000', 'result': '4', 'col': '6', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'tampa bay'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home', 'tampa bay'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; home ; tampa bay }', 'tointer': 'select the rows whose home record fuzzily matches to tampa bay .'}, 'att... | eq { count { filter_greater { filter_eq { all_rows ; home ; tampa bay } ; attendance ; 19,000 } } ; 4 } = true | select the rows whose home record fuzzily matches to tampa bay . among these rows , select the rows whose attendance record is greater than 19,000 . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'home_6': 6, 'tampa bay_7': 7, 'attendance_8': 8, '19,000_9': 9, '4_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', 'home_6': 'home', 'tampa bay_7': 'tampa bay', 'attendance_8': 'attendance', '19,000_9': '19,000', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'home_6': [0], 'tampa bay_7': [0], 'attendance_8': [1], '19,000_9': [1], '4_10': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['october 4', 'new jersey', '1 - 3', 'tampa bay', 'holmqvist', '19454', '1 - 0 - 0'], ['october 6', 'atlanta', '2 - 5', 'tampa bay', 'holmqvist', '19220', '2 - 0 - 0'], ['october 10', 'florida', '1 - 2', 'tampa bay', 'holmqvist', '18540', '3 - 0 - 0'], ['october 13', 'tampa bay', '4 - 6', 'florida', 'denis', '15801', ... |
rotores de portugal | https://en.wikipedia.org/wiki/Rotores_de_Portugal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16965464-1.html.csv | ordinal | in rotores de portugal , squadron 33 is the earliest between the year 1976 and 2005 . | {'scope': 'subset', 'row': '1', 'col': '5', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '5', 'criterion': 'less_than_eq', 'value': '2005'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'dates', '2005'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; dates ; 2005 }', 'tointer': 'select the rows whose dates record is less than or equal to 2005 .'}, 'd... | eq { hop { nth_argmin { filter_less_eq { all_rows ; dates ; 2005 } ; dates ; 1 } ; squadron } ; squadron 33 } = true | select the rows whose dates record is less than or equal to 2005 . select the row whose dates record of these rows is 1st minimum . the squadron record of this row is squadron 33 . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_less_eq_0': 0, 'all_rows_5': 5, 'dates_6': 6, '2005_7': 7, 'dates_8': 8, '1_9': 9, 'squadron_10': 10, 'squadron 33_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_5': 'all_rows', 'dates_6': 'dates', '2005_7': '2005', 'dates_8': 'dates', '1_9': '1', 'squadron_10': 'squadron', 'squadron 33_11': 'squadron 33'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_less_eq_0': [1], 'all_rows_5': [0], 'dates_6': [0], '2005_7': [0], 'dates_8': [1], '1_9': [1], 'squadron_10': [2], 'squadron 33_11': [3]} | ['aircraft', 'origin', 'squadron', 'display aircraft', 'dates'] | [['sud aviation alouette iii', 'france', 'squadron 33', '4', '1976-1980'], ['sud aviation alouette iii', 'france', 'squadron 102', '2', '1982-1992'], ['sud aviation alouette iii', 'france', 'squadron 111', '4', '1993-1994'], ['sud aviation alouette iii', 'france', 'squadron 552', '2', '2004-2005'], ['sud aviation aloue... |
2008 - 09 orlando magic season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Orlando_Magic_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17311797-11.html.csv | count | rafer alston had the most assists on three occasions . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'rafer alston', 'result': '3', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'rafer alston'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high assists record fuzzily matches to rafer alston .', 'tostr': 'filter_eq { all_rows ; high assists ; rafer alston }'}], 'resul... | eq { count { filter_eq { all_rows ; high assists ; rafer alston } } ; 3 } = true | select the rows whose high assists record fuzzily matches to rafer alston . 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, 'high assists_5': 5, 'rafer alston_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', 'high assists_5': 'high assists', 'rafer alston_6': 'rafer alston', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high assists_5': [0], 'rafer alston_6': [0], '3_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'april 19', '76ers', 'l 98 - 100 ( ot )', 'dwight howard ( 31 )', 'dwight howard ( 16 )', 'rafer alston ( 5 )', 'amway arena 17461', '0 - 1'], ['2', 'april 22', '76ers', 'w 96 - 87 ( ot )', 'courtney lee ( 24 )', 'dwight howard ( 10 )', 'rashard lewis ( 6 )', 'amway arena 17461', '1 - 1'], ['3', 'april 24', '76e... |
new england women 's and men 's athletic conference | https://en.wikipedia.org/wiki/New_England_Women%27s_and_Men%27s_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1974782-1.html.csv | superlative | the school in the new england athletic conference with the highest enrollment is massachusetts institute of technology . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'enrollment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment }'}, 'institution'], 'result': 'massachusetts institute of technology', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; institut... | eq { hop { argmax { all_rows ; enrollment } ; institution } ; massachusetts institute of technology } = true | select the row whose enrollment record of all rows is maximum . the institution record of this row is massachusetts institute of technology . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'institution_6': 6, 'massachusetts institute of technology_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', 'institution_6': 'institution', 'massachusetts institute of technology_7': 'massachusetts institute of technology'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'institution_6': [1], 'massachusetts institute of technology_7': [2]} | ['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'joined'] | [['babson college', 'wellesley , massachusetts', 'beavers', '1919', 'private / non - sectarian', '3200', '1985'], ['clark university', 'worcester , massachusetts', 'cougars', '1887', 'private / non - sectarian', '2780', '1995'], ['emerson college', 'boston , massachusetts', 'lions', '1880', 'private / non - sectarian',... |
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/2-10301911-2.html.csv | unique | brian finch was the only driver to not ride either a suzuki or triumph motorcycle in the top 7 . | {'scope': 'all', 'row': '7', 'col': '3', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'velocette', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'velocette'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to velocette .', 'tostr': 'filter_eq { all_rows ; team ; velocette }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; team ; velocette } } ; eq { hop { filter_eq { all_rows ; team ; velocette } ; rider } ; brian finch } } = true | select the rows whose team record fuzzily matches to velocette . there is only one such row in the table . the rider record of this unqiue row is brian finch . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team_7': 7, 'velocette_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'rider_9': 9, 'brian finch_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team_7': 'team', 'velocette_8': 'velocette', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'rider_9': 'rider', 'brian finch_10': 'brian finch'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'team_7': [0], 'velocette_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'rider_9': [2], 'brian finch_10': [3]} | ['rank', 'rider', 'team', 'speed', 'time'] | [['1', 'frank whiteway', 'suzuki', '89.94 mph', '2:05.52.0'], ['2', 'gordon pantall', 'triumph', '88.90 mph', '2:07.20.0'], ['3', 'ray knight', 'triumph', '88.89 mph', '2:07.20.4'], ['4', 'rbaylie', 'triumph', '87.58 mph', '2:09.15.0'], ['5', 'graham penny', 'triumph', '86.70 mph', '2:10.34.4'], ['6', 'jwade', 'suzuki'... |
swiss locomotive and machine works | https://en.wikipedia.org/wiki/Swiss_Locomotive_and_Machine_Works | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1562368-2.html.csv | comparative | the locomotive nicknamed enid was built before the locamotive nicknamed snowden . | {'row_1': '2', 'row_2': '4', 'col': '1', 'col_other': '7', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'notes', 'enid'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose notes record fuzzily matches to enid .', 'tostr': 'filter_eq { all_rows ; notes ; enid }'}, 'built'], 'result': None, 'ind': 2, 'tostr': 'ho... | less { hop { filter_eq { all_rows ; notes ; enid } ; built } ; hop { filter_eq { all_rows ; notes ; snowdon } ; built } } = true | select the rows whose notes record fuzzily matches to enid . take the built record of this row . select the rows whose notes record fuzzily matches to snowdon . take the built 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, 'notes_7': 7, 'enid_8': 8, 'built_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'notes_11': 11, 'snowdon_12': 12, 'built_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', 'notes_7': 'notes', 'enid_8': 'enid', 'built_9': 'built', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'notes_11': 'notes', 'snowdon_12': 'snowdon', 'bui... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'notes_7': [0], 'enid_8': [0], 'built_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'notes_11': [1], 'snowdon_12': [1], 'built_13': [3]} | ['built', 'number', 'type', 'slm number', 'wheel arrangement', 'location', 'notes'] | [['1895', '1', 'mountain railway rack steam locomotive', '923', '0 - 4 - 2 t', 'snowdon mountain railway', 'ladas'], ['1895', '2', 'mountain railway rack steam locomotive', '924', '0 - 4 - 2 t', 'snowdon mountain railway', 'enid'], ['1895', '3', 'mountain railway rack steam locomotive', '925', '0 - 4 - 2 t', 'snowdon m... |
2009 - 10 louisville cardinals men 's basketball team | https://en.wikipedia.org/wiki/2009%E2%80%9310_Louisville_Cardinals_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25118909-3.html.csv | count | the height of 4 players on the 2009 - 10 louisville cardinals men 's basketball team is 6 - 4 . | {'scope': 'all', 'criterion': 'equal', 'value': '6-4', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'height', '6-4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height record fuzzily matches to 6-4 .', 'tostr': 'filter_eq { all_rows ; height ; 6-4 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_e... | eq { count { filter_eq { all_rows ; height ; 6-4 } } ; 4 } = true | select the rows whose height record fuzzily matches to 6-4 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'height_5': 5, '6-4_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'height_5': 'height', '6-4_6': '6-4', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'height_5': [0], '6-4_6': [0], '4_7': [2]} | ['name', '-', 'position', 'height', 'weight', 'year', 'former school', 'hometown'] | [['chris brickley', '11', 'guard', '6 - 4', '175', 'senior', 'northeastern university', 'manchester , nh'], ['rakeem buckles', '4', 'forward', '6 - 8', '200', 'freshman', 'pace', 'miami , fl'], ['reginald delk', '12', 'guard', '6 - 4', '175', 'senior', 'mississippi state university', 'jackson , tn'], ['george goode', '... |
tamil nadu legislative assembly | https://en.wikipedia.org/wiki/Tamil_Nadu_Legislative_Assembly | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23512864-4.html.csv | count | for the tamil nadu legislative assembly , there were three times when the indian national congress was the winning party . | {'scope': 'all', 'criterion': 'equal', 'value': 'indian national congress', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winning party / coalition', 'indian national congress'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winning party / coalition record fuzzily matches to indian national congress .', 'tostr': 'filter_eq { a... | eq { count { filter_eq { all_rows ; winning party / coalition ; indian national congress } } ; 3 } = true | select the rows whose winning party / coalition record fuzzily matches to indian national congress . 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, 'winning party / coalition_5': 5, 'indian national congress_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', 'winning party / coalition_5': 'winning party / coalition', 'indian national congress_6': 'indian national congress', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winning party / coalition_5': [0], 'indian national congress_6': [0], '3_7': [2]} | ['election year', 'assembly', 'winning party / coalition', 'chief minister', 'speaker'] | [['1952', 'first assembly', 'indian national congress', 'c rajagopalachari k kamaraj', 'j shivashanmugam pillai ( 2 )'], ['1957', 'second assembly', 'indian national congress', 'k kamaraj ( 2 )', 'n gopala menon u krishna rao'], ['1962', 'third assembly', 'indian national congress', 'k kamaraj ( 3 ) m bakthavatsalam', ... |
gambrinus liga | https://en.wikipedia.org/wiki/Gambrinus_Liga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2429942-2.html.csv | majority | sparta prague was the champion team in the majority of gambrinus liga seasons . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'sparta prague', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'champions', 'sparta prague'], 'result': True, 'ind': 0, 'tointer': 'for the champions records of all rows , most of them fuzzily match to sparta prague .', 'tostr': 'most_eq { all_rows ; champions ; sparta prague } = true'} | most_eq { all_rows ; champions ; sparta prague } = true | for the champions records of all rows , most of them fuzzily match to sparta prague . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'champions_3': 3, 'sparta prague_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'champions_3': 'champions', 'sparta prague_4': 'sparta prague'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'champions_3': [0], 'sparta prague_4': [0]} | ['season', 'champions', 'runner - up', 'third place', 'top goalscorer', 'club'] | [['1993 - 94', 'sparta prague ( 1 )', 'slavia prague', 'baník ostrava', 'horst siegl ( 20 )', 'sparta prague'], ['1994 - 95', 'sparta prague ( 2 )', 'slavia prague', 'fc brno', 'radek drulák ( 15 )', 'drnovice'], ['1995 - 96', 'slavia prague ( 1 )', 'sigma olomouc', 'baumit jablonec', 'radek drulák ( 22 )', 'drnovice']... |
1982 denver broncos season | https://en.wikipedia.org/wiki/1982_Denver_Broncos_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17928444-1.html.csv | majority | the majority of games in the 1982 denver broncos season ended in losses for the broncos . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; result ; l } = true'} | most_eq { all_rows ; result ; l } = true | for the result records of all rows , most of them fuzzily match to l . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'l_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'l_4': 'l'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'l_4': [0]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 12', 'san diego chargers', 'l 3 - 23', 'mile high stadium', '0 - 1', '73564'], ['2', 'september 19', 'san francisco 49ers', 'w 24 - 21', 'mile high stadium', '1 - 1', '73899'], ['10', 'november 21', 'seattle seahawks', 'l 10 - 17', 'mile high stadium', '1 - 2', '73996'], ['11', 'november 28', 'san die... |
list of montreal canadiens draft picks | https://en.wikipedia.org/wiki/List_of_Montreal_Canadiens_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18259953-8.html.csv | unique | the player selected in the 6th round is the only one whose name was omitted . | {'scope': 'all', 'row': '6', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '-', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'player', '-'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record is equal to - .', 'tostr': 'filter_eq { all_rows ; player ; - }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; pl... | and { only { filter_eq { all_rows ; player ; - } } ; eq { hop { filter_eq { all_rows ; player ; - } ; round } ; 6 } } = true | select the rows whose player record is equal to - . there is only one such row in the table . the round record of this unqiue row is 6 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, '-_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'round_9': 9, '6_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', '-_8': '-', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'round_9': 'round', '6_10': '6'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'player_7': [0], '-_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'round_9': [2], '6_10': [3]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'nathan beaulieu', 'defence', 'canada', 'saint john sea dogs ( qmjhl )'], ['4', 'josiah didier', 'defence', 'canada', 'cedar rapids roughriders ( ushl )'], ['4', 'olivier archambault', 'left wing', 'canada', "val d'or foreurs ( qmjhl )"], ['4', 'magnus nygren', 'defence', 'sweden', 'fã ¤ rjestads bk ( elitserien... |
newington college | https://en.wikipedia.org/wiki/Newington_College | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1839872-3.html.csv | majority | all of the newington college employees have won the medal of the order of australia honour . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'medal of the order of australia', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'honour', 'medal of the order of australia'], 'result': True, 'ind': 0, 'tointer': 'for the honour records of all rows , all of them fuzzily match to medal of the order of australia .', 'tostr': 'all_eq { all_rows ; honour ; medal of the order of australia } = true'} | all_eq { all_rows ; honour ; medal of the order of australia } = true | for the honour records of all rows , all of them fuzzily match to medal of the order of australia . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'honour_3': 3, 'medal of the order of australia_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'honour_3': 'honour', 'medal of the order of australia_4': 'medal of the order of australia'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'honour_3': [0], 'medal of the order of australia_4': [0]} | ['name', 'employed', 'position held', 'honour', 'citation'] | [['davis , phillip harris ( phil )', '1951 - 2000', 'mathematics & prefect master', 'medal of the order of australia', "it 's an honour"], ['morgan , michael dennis', '1981 - 2001', 'physical education ist viii coach', 'medal of the order of australia', "it 's an honour"], ['swain , elizabeth anne ( liz )', '1973 - 199... |
primera división de fútbol profesional apertura 2008 | https://en.wikipedia.org/wiki/Primera_Divisi%C3%B3n_de_F%C3%BAtbol_Profesional_Apertura_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18522916-5.html.csv | superlative | mauricio cienfuegos had the earliest date of vacancy in the primera division de futbol . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date of vacancy'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date of vacancy }'}, 'outgoing manager'], 'result': 'mauricio cienfuegos', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date of vacancy } ; outgoi... | eq { hop { argmin { all_rows ; date of vacancy } ; outgoing manager } ; mauricio cienfuegos } = true | select the row whose date of vacancy record of all rows is minimum . the outgoing manager record of this row is mauricio cienfuegos . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date of vacancy_5': 5, 'outgoing manager_6': 6, 'mauricio cienfuegos_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date of vacancy_5': 'date of vacancy', 'outgoing manager_6': 'outgoing manager', 'mauricio cienfuegos_7': 'mauricio cienfuegos'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date of vacancy_5': [0], 'outgoing manager_6': [1], 'mauricio cienfuegos_7': [2]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment', 'position in table'] | [['nejapa', 'mauricio cienfuegos', 'mutual consent', '14 august 2008', 'daniel uberti', '5 september 2008', '10th'], ['firpo', 'gerardo reinoso', 'sacked', '25 august 2008', 'oscar benitez', '2 september 2008', '7th'], ['balboa', 'gustavo de simone', 'sacked', '30 august 2008', 'roberto gamarra', '5 september 2008', '1... |
australian national bl class | https://en.wikipedia.org/wiki/Australian_National_BL_class | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11373937-1.html.csv | majority | the majority of australian national bl class locomotives have a pacific national blue & yellow livery . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'pacific national blue & yellow', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'livery', 'pacific national blue & yellow'], 'result': True, 'ind': 0, 'tointer': 'for the livery records of all rows , most of them fuzzily match to pacific national blue & yellow .', 'tostr': 'most_eq { all_rows ; livery ; pacific national blue & yellow } = true'} | most_eq { all_rows ; livery ; pacific national blue & yellow } = true | for the livery records of all rows , most of them fuzzily match to pacific national blue & yellow . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'livery_3': 3, 'pacific national blue & yellow_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'livery_3': 'livery', 'pacific national blue & yellow_4': 'pacific national blue & yellow'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'livery_3': [0], 'pacific national blue & yellow_4': [0]} | ['locomotive', 'serial no', 'entered service', 'gauge', 'livery'] | [['bl26', '83 - 1010', 'march 1983', 'standard', 'pacific national blue & yellow'], ['bl27', '83 - 1011', 'august 1983', 'standard', 'pacific national blue & yellow'], ['bl28', '83 - 1012', 'september 1983', 'standard', 'pacific national blue & yellow'], ['bl29', '83 - 1013', 'october 1983', 'broad', 'pacific national ... |
history of test cricket from 1901 to 1914 | https://en.wikipedia.org/wiki/History_of_Test_cricket_from_1901_to_1914 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1598207-2.html.csv | count | on two different sets of dates , the result was a draw . | {'scope': 'all', 'criterion': 'equal', 'value': 'draw', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'draw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to draw .', 'tostr': 'filter_eq { all_rows ; result ; draw }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filte... | eq { count { filter_eq { all_rows ; result ; draw } } ; 2 } = true | select the rows whose result record fuzzily matches to draw . 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, 'result_5': 5, 'draw_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', 'result_5': 'result', 'draw_6': 'draw', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'draw_6': [0], '2_7': [2]} | ['date', 'home captain', 'away captain', 'venue', 'result'] | [['29 , 3031 may 1902', 'archie maclaren', 'joe darling', 'edgbaston', 'draw'], ['12 , 13 , 14 jun 1902', 'archie maclaren', 'joe darling', "lord 's", 'draw'], ['3 , 4 , 5 jul 1902', 'archie maclaren', 'joe darling', 'bramall lane', 'aus by 143 runs'], ['24 , 25 , 26 jul 1902', 'archie maclaren', 'joe darling', 'old tr... |
1907 michigan wolverines football team | https://en.wikipedia.org/wiki/1907_Michigan_Wolverines_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25724294-2.html.csv | aggregation | the players on the 1907 michigan wolverines football team averaged 2.29 touchdowns each . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '2.29', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'touchdowns'], 'result': '2.29', 'ind': 0, 'tostr': 'avg { all_rows ; touchdowns }'}, '2.29'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; touchdowns } ; 2.29 } = true', 'tointer': 'the average of the touchdowns record of all rows is... | round_eq { avg { all_rows ; touchdowns } ; 2.29 } = true | the average of the touchdowns record of all rows is 2.29 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'touchdowns_4': 4, '2.29_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'touchdowns_4': 'touchdowns', '2.29_5': '2.29'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'touchdowns_4': [0], '2.29_5': [1]} | ['player', 'touchdowns', 'extra points', 'field goals', 'points'] | [['paul magoffin', '7', '0', '0', '35'], ['walter rheinschild', '5', '0', '0', '25'], ['octy graham', '0', '7', '4', '24'], ['jack loell', '3', '0', '0', '15'], ['prentiss douglass', '1', '0', '0', '5'], ['dave allerdice', '0', '3', '0', '3'], ['harry s hammond', '0', '1', '0', '1']] |
ucla bruins gymnastics | https://en.wikipedia.org/wiki/UCLA_Bruins_gymnastics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17617256-1.html.csv | unique | the only person on the ucla bruins gymnastics team from orlando metro is olivia courtney . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'orlando metro', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'orlando metro'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to orlando metro .', 'tostr': 'filter_eq { all_rows ; club ; orlando metro }'}], 'result': True, 'ind': 1, '... | and { only { filter_eq { all_rows ; club ; orlando metro } } ; eq { hop { filter_eq { all_rows ; club ; orlando metro } ; name } ; olivia courtney } } = true | select the rows whose club record fuzzily matches to orlando metro . there is only one such row in the table . the name record of this unqiue row is olivia courtney . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'club_7': 7, 'orlando metro_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'olivia courtney_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'club_7': 'club', 'orlando metro_8': 'orlando metro', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'olivia courtney_10': 'olivia courtney'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'club_7': [0], 'orlando metro_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'olivia courtney_10': [3]} | ['name', 'height', 'year', 'hometown', 'club'] | [['sadiqua bynum', '5 - 4', 'jr', 'berkeley , calif', 'head over heels athletic arts'], ['angi cipra', '5 - 2', 'fr', 'mesa , ariz', 'desert devils gymnastics'], ['olivia courtney', '5 - 2', 'jr', 'fairfax , va', 'orlando metro'], ['ellette craddock', '5 - 5', 'so', 'san francisco , calif', 'san mateo gymnastics center... |
list of intel pentium dual - core microprocessors | https://en.wikipedia.org/wiki/List_of_Intel_Pentium_Dual-Core_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11602313-4.html.csv | majority | the majority of the processors had a frequency greater than 1.5 ghz . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1.5 ghz', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'frequency', '1.5 ghz'], 'result': True, 'ind': 0, 'tointer': 'for the frequency records of all rows , most of them are greater than 1.5 ghz .', 'tostr': 'most_greater { all_rows ; frequency ; 1.5 ghz } = true'} | most_greater { all_rows ; frequency ; 1.5 ghz } = true | for the frequency records of all rows , most of them are greater than 1.5 ghz . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'frequency_3': 3, '1.5 ghz_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'frequency_3': 'frequency', '1.5 ghz_4': '1.5 ghz'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'frequency_3': [0], '1.5 ghz_4': [0]} | ['model number', 'sspec number', 'frequency', 'l2 cache', 'fsb', 'mult', 'voltage', 'tdp', 'socket', 'release date', 'part number ( s )', 'release price ( usd )'] | [['pentium dual - core t2310', 'slaec ( m0 )', '1.47 ghz', '1 mb', '533 mt / s', '11', '1.075 - 1.175 v', '35 w', 'socket p', 'q4 2007', 'lf80537 ge0201 m', '90'], ['pentium dual - core t2330', 'sla4k ( m0 )', '1.6 ghz', '1 mb', '533 mt / s', '12', '1.075 - 1.175 v', '35 w', 'socket p', 'q4 2007', 'lf80537 ge0251 mn', ... |
marc girardelli | https://en.wikipedia.org/wiki/Marc_Girardelli | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1376129-1.html.csv | count | marc giradielli finished 1st in overall season rankings 5 times . | {'scope': 'all', 'criterion': 'equal', 'value': '1', 'result': '5', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'overall', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose overall record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; overall ; 1 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ;... | eq { count { filter_eq { all_rows ; overall ; 1 } } ; 5 } = true | select the rows whose overall record is equal to 1 . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'overall_5': 5, '1_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'overall_5': 'overall', '1_6': '1', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'overall_5': [0], '1_6': [0], '5_7': [2]} | ['season', 'overall', 'slalom', 'giant slalom', 'super g', 'downhill', 'combined'] | [['1980', '84', '-', '32', 'not run', '-', '-'], ['1981', '26', '15', '23', 'not run', '-', '-'], ['1982', '6', '8', '3', 'not run', '-', '-'], ['1983', '4', '7', '6', 'not awarded', '-', '3'], ['1984', '3', '1', '4', 'not awarded', '-', '34'], ['1985', '1', '1', '1', 'not awarded', '19', '-'], ['1986', '1', '11', '5',... |
list of schools in the auckland region | https://en.wikipedia.org/wiki/List_of_schools_in_the_Auckland_Region | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12017602-20.html.csv | majority | most of the listed schools in the auckland region are in the area of papakura . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'papakura', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'area', 'papakura'], 'result': True, 'ind': 0, 'tointer': 'for the area records of all rows , most of them fuzzily match to papakura .', 'tostr': 'most_eq { all_rows ; area ; papakura } = true'} | most_eq { all_rows ; area ; papakura } = true | for the area records of all rows , most of them fuzzily match to papakura . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'area_3': 3, 'papakura_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'area_3': 'area', 'papakura_4': 'papakura'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'area_3': [0], 'papakura_4': [0]} | ['name', 'years', 'gender', 'area', 'authority', 'decile', 'roll'] | [['conifer grove school', '1 - 8', 'coed', 'takanini', 'state', '7', '526'], ['cosgrove school', '1 - 6', 'coed', 'papakura', 'state', '2', '606'], ['drury school', '1 - 8', 'coed', 'drury', 'state', '8', '423'], ['edmund hillary school', '1 - 8', 'coed', 'papakura', 'state', '1', '146'], ['hingaia peninsula school', '... |
henry cejudo | https://en.wikipedia.org/wiki/Henry_Cejudo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18931507-2.html.csv | majority | in four out of five of henry cejudo 's fights , the method he used to finish the fight was punches . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'punches', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'method', 'punches'], 'result': True, 'ind': 0, 'tointer': 'for the method records of all rows , most of them fuzzily match to punches .', 'tostr': 'most_eq { all_rows ; method ; punches } = true'} | most_eq { all_rows ; method ; punches } = true | for the method records of all rows , most of them fuzzily match to punches . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'method_3': 3, 'punches_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'method_3': 'method', 'punches_4': 'punches'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'method_3': [0], 'punches_4': [0]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '5 - 0', 'ryan hollis', 'decision ( unanimous )', 'lfc 24 - legacy fighting championship 24', '3', '5:00', 'dallas , texas , united states'], ['win', '4 - 0', 'miguelito marti', 'tko ( punches )', 'gladiator challenge : american dream', '1', '1:43', 'lincoln , california , united states'], ['win', '3 - 0', 'an... |
1996 ansett australia cup | https://en.wikipedia.org/wiki/1996_Ansett_Australia_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16388091-1.html.csv | majority | most games of the 1996 ansett australia cup competition were played in the month of february . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'february', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'date', 'february'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , most of them fuzzily match to february .', 'tostr': 'most_eq { all_rows ; date ; february } = true'} | most_eq { all_rows ; date ; february } = true | for the date records of all rows , most of them fuzzily match to february . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'february_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'february_4': 'february'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'february_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date', 'time'] | [['adelaide', '18.16 ( 124 )', 'melbourne', '10.5 ( 65 )', 'football park', '24143', 'friday 23 february 1996', '8:00 pm'], ['hawthorn', '9.19 ( 73 )', 'st kilda', '19.13 ( 127 )', 'waverley park', '16061', 'saturday , 23 february 1996', '8:00 pm'], ['fremantle', '7.15 ( 57 )', 'west coast', '10.11 ( 71 )', 'marrara st... |
salvatore bettiol | https://en.wikipedia.org/wiki/Salvatore_Bettiol | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15671752-1.html.csv | aggregation | salvatore bettiol 's total time in the year of 1987 was over 4:00:00 . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '4:27:46', 'subset': {'col': '1', 'criterion': 'equal', 'value': '1987'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '1987'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; 1987 }', 'tointer': 'select the rows whose year record is equal to 1987 .'}, 'notes'], 'result': '4:27:46', 'ind': 1, 'tostr': 'sum { filte... | round_eq { sum { filter_eq { all_rows ; year ; 1987 } ; notes } ; 4:27:46 } = true | select the rows whose year record is equal to 1987 . the sum of the notes record of these rows is 4:27:46 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, '1987_6': 6, 'notes_7': 7, '4:27:46_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '1987_6': '1987', 'notes_7': 'notes', '4:27:46_8': '4:27:46'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '1987_6': [0], 'notes_7': [1], '4:27:46_8': [2]} | ['year', 'competition', 'venue', 'position', 'event', 'notes'] | [['1986', 'venice marathon', 'venice , italy', '1st', 'marathon', '2:18:44'], ['1987', 'world championships', 'rome , italy', '13th', 'marathon', '2:17:45'], ['1987', 'venice marathon', 'venice , italy', '1st', 'marathon', '2:10:01'], ['1990', 'european championships', 'split , fr yugoslavia', '4th', 'marathon', '2:17:... |
lexus ls ( xf40 ) | https://en.wikipedia.org/wiki/Lexus_LS_%28XF40%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21530474-1.html.csv | unique | the l110f cvt drivetrain was only used 1 time in the hybrid model . | {'scope': 'all', 'row': '7', 'col': '5', 'col_other': '6', 'criterion': 'equal', 'value': 'l110f cvt', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'transmission', 'l110f cvt'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose transmission record fuzzily matches to l110f cvt .', 'tostr': 'filter_eq { all_rows ; transmission ; l110f cvt }'}], 'result': True,... | and { only { filter_eq { all_rows ; transmission ; l110f cvt } } ; eq { hop { filter_eq { all_rows ; transmission ; l110f cvt } ; engine type } ; 5.0 l hybrid v8 } } = true | select the rows whose transmission record fuzzily matches to l110f cvt . there is only one such row in the table . the engine type record of this unqiue row is 5.0 l hybrid v8 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'transmission_7': 7, 'l110f cvt_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'engine type_9': 9, '5.0 l hybrid v8_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'transmission_7': 'transmission', 'l110f cvt_8': 'l110f cvt', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'engine type_9': 'engine type', '5.0 l hybrid v8_10': '5.0 l hybrid v8'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'transmission_7': [0], 'l110f cvt_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'engine type_9': [2], '5.0 l hybrid v8_10': [3]} | ['chassis code', 'model no', 'production years', 'drivetrain', 'transmission', 'engine type', 'engine code', 'region ( s )'] | [['usf40 ( japanese )', 'ls 460', '2006 -', 'rwd', '8 - speed aa80e at', '4.6 l petrol v8', '1ur - fse', 'n america , asia , europe , oceania'], ['usf40 ( japanese )', 'ls 460', '2006 -', 'rwd', '8 - speed aa80e at', '4.6 l petrol v8', '1ur - fe', 'middle east'], ['usf41', 'ls 460 l', '2006 -', 'rwd', '8 - speed aa80e ... |
royal canadian mint numismatic coins ( 2000s ) | https://en.wikipedia.org/wiki/Royal_Canadian_Mint_numismatic_coins_%282000s%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11916083-14.html.csv | aggregation | the average mintage for royal canadian mint numismatic coins ( 2000s ) was 22800 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '22800', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'mintage'], 'result': '22800', 'ind': 0, 'tostr': 'avg { all_rows ; mintage }'}, '22800'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; mintage } ; 22800 } = true', 'tointer': 'the average of the mintage record of all rows is 22800 .'... | round_eq { avg { all_rows ; mintage } ; 22800 } = true | the average of the mintage record of all rows is 22800 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'mintage_4': 4, '22800_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'mintage_4': 'mintage', '22800_5': '22800'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'mintage_4': [0], '22800_5': [1]} | ['year', 'animal', 'artist', 'finish', 'mintage', 'issue price'] | [['2007', 'ruby - throated hummingbird', 'arnold nogy', 'specimen ( with selective colouring )', '25000', '24.95'], ['2007', 'red breasted nuthatch', 'arnold nogy', 'specimen ( with selective colouring )', '25000', '24.95'], ['2008', 'downy woodpecker', 'arnold nogy', 'specimen ( with selective colouring )', '25000', '... |
chad little | https://en.wikipedia.org/wiki/Chad_Little | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1875157-2.html.csv | superlative | 1995 was the most succesful in terms of wins for chad little . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'wins'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; wins }'}, 'year'], 'result': '1995', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; wins } ; year }'}, '1995'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argm... | eq { hop { argmax { all_rows ; wins } ; year } ; 1995 } = true | select the row whose wins record of all rows is maximum . the year record of this row is 1995 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'wins_5': 5, 'year_6': 6, '1995_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'wins_5': 'wins', 'year_6': 'year', '1995_7': '1995'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'wins_5': [0], 'year_6': [1], '1995_7': [2]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1992', '1', '0', '0', '0', '0', '29.0', '29.0', '1400', '120th', '37 little racing'], ['1993', '12', '0', '2', '3', '0', '22.1', '22.6', '56508', '32nd', '23 mark rypien motorsports'], ['1994', '28', '0', '10', '14', '0', '21.0', '11.9', '234022', '3rd', '23 mark rypien motorsports'], ['1995', '26', '6', '11', '13',... |
2004 belarusian premier league | https://en.wikipedia.org/wiki/2004_Belarusian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14749151-1.html.csv | comparative | of the venues for the 2004 belarusian premier league , neman has a higher capacity than darida . | {'row_1': '7', 'row_2': '13', 'col': '4', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'neman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to neman .', 'tostr': 'filter_eq { all_rows ; venue ; neman }'}, 'capacity'], 'result': None, 'ind': 2, 'to... | greater { hop { filter_eq { all_rows ; venue ; neman } ; capacity } ; hop { filter_eq { all_rows ; venue ; darida } ; capacity } } = true | select the rows whose venue record fuzzily matches to neman . take the capacity record of this row . select the rows whose venue record fuzzily matches to darida . take the capacity record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'neman_8': 8, 'capacity_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'venue_11': 11, 'darida_12': 12, 'capacity_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'neman_8': 'neman', 'capacity_9': 'capacity', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'venue_11': 'venue', 'darida_12': 'd... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'venue_7': [0], 'neman_8': [0], 'capacity_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'venue_11': [1], 'darida_12': [1], 'capacity_13': [3]} | ['team', 'location', 'venue', 'capacity', 'position in 2003'] | [['gomel', 'gomel', 'central , gomel', '11800', '1'], ['bate', 'borisov', 'city stadium , borisov', '5500', '2'], ['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '3'], ['torpedo - ska', 'minsk', 'torpedo , minsk', '5200', '4'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '5'], ['torpedo', 'zhodino', 'torpedo , ... |
patty schnyder | https://en.wikipedia.org/wiki/Patty_Schnyder | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1547798-4.html.csv | unique | the only time that patty schyder played on a clay surface was in 1998 . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'clay', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to clay .', 'tostr': 'filter_eq { all_rows ; surface ; clay }'}], 'result': True, 'ind': 1, 'tostr': 'only { fi... | and { only { filter_eq { all_rows ; surface ; clay } } ; eq { hop { filter_eq { all_rows ; surface ; clay } ; date } ; 3 may 1998 } } = true | select the rows whose surface record fuzzily matches to clay . there is only one such row in the table . the date record of this unqiue row is 3 may 1998 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'clay_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '3 may 1998_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'clay_8': 'clay', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '3 may 1998_10': '3 may 1998'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'clay_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '3 may 1998_10': [3]} | ['date', 'tournament', 'surface', 'partner', 'opponent in the final', 'score'] | [['3 may 1998', 'hamburg , germany', 'clay', 'barbara schett', 'martina hingis jana novotná', '7 - 6 , 3 - 6 , 6 - 3'], ['17 february 2002', 'antwerp , belgium', 'carpet', 'magdalena maleeva', 'nathalie dechy meilen tu', '6 - 3 , 6 - 7 , 6 - 3'], ['9 february 2003', 'paris , france', 'carpet', 'barbara schett', 'marion... |
forest hill railway station | https://en.wikipedia.org/wiki/Forest_Hill_railway_station | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1569516-1.html.csv | comparative | the forest hill railway station train whose destination is highbury & islington is on platform 1 while the train whose destination is west croydon is on platform 2 . | {'row_1': '1', 'row_2': '5', 'col': '1', 'col_other': '3', 'relation': 'not_equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'not_eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'destination', 'highbury & islington'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose destination record fuzzily matches to highbury & islington .', 'tostr': 'filter_eq { all_ro... | and { not_eq { hop { filter_eq { all_rows ; destination ; highbury & islington } ; platform } ; hop { filter_eq { all_rows ; destination ; west croydon } ; platform } } ; and { eq { hop { filter_eq { all_rows ; destination ; highbury & islington } ; platform } ; 1 } ; eq { hop { filter_eq { all_rows ; destination ; wes... | select the rows whose destination record fuzzily matches to highbury & islington . take the platform record of this row . select the rows whose destination record fuzzily matches to west croydon . take the platform record of this row . the first record is not equal to the second record . the platform record of the firs... | 13 | 9 | {'and_8': 8, 'result_9': 9, 'not_eq_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'destination_11': 11, 'highbury & islington_12': 12, 'platform_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'destination_15': 15, 'west croydon_16': 16, 'platform_17': 17, 'and_7': 7, 'eq_5': 5, '1_1... | {'and_8': 'and', 'result_9': 'true', 'not_eq_4': 'not_eq', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'destination_11': 'destination', 'highbury & islington_12': 'highbury & islington', 'platform_13': 'platform', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'al... | {'and_8': [9], 'result_9': [], 'not_eq_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'destination_11': [0], 'highbury & islington_12': [0], 'platform_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'destination_15': [1], 'west croydon_16': [1], 'platform_17': [3], ... | ['platform', 'frequency ( per hour )', 'destination', 'service pattern', 'operator', 'line'] | [['1', '4', 'highbury & islington', 'all stations via shoreditch high street', 'london overground', 'east london'], ['1', '4', 'dalston junction', 'all stations via shoreditch high street', 'london overground', 'east london'], ['1', '4', 'london bridge', 'all stations', 'southern', 'metro'], ['2', '4', 'crystal palace'... |
2007 - 08 fis ski jumping world cup | https://en.wikipedia.org/wiki/2007%E2%80%9308_FIS_Ski_Jumping_World_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14407512-23.html.csv | unique | gregor schlierenzauer was the only participant in the 2007 - 08 fis ski jumping world cup with austrian nationality . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'aut', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'aut'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to aut .', 'tostr': 'filter_eq { all_rows ; nationality ; aut }'}], 'result': True, 'ind': 1, 'tostr': '... | and { only { filter_eq { all_rows ; nationality ; aut } } ; eq { hop { filter_eq { all_rows ; nationality ; aut } ; name } ; gregor schlierenzauer } } = true | select the rows whose nationality record fuzzily matches to aut . there is only one such row in the table . the name record of this unqiue row is gregor schlierenzauer . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'aut_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'gregor schlierenzauer_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'aut_8': 'aut', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'gregor schlierenzauer_10': 'gregor schlierenzauer'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'aut_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'gregor schlierenzauer_10': [3]} | ['rank', 'name', 'nationality', '1st ( m )', '2nd ( m )', 'points', 'overall nt points', 'overall wc points ( rank )'] | [['1', 'janne ahonen', 'fin', '122.5', '126.0', '248.3', '378.7 ( 2 )', '1098 ( 3 )'], ['2', 'anders bardal', 'nor', '117.5', '128.0', '240.4', '373.0 ( 5 )', '788 ( 5 )'], ['3', 'tom hilde', 'nor', '121.5', '122.5', '237.2', '373.2 ( 4 )', '1027 ( 4 )'], ['4', 'gregor schlierenzauer', 'aut', '114.5', '129.0', '236.8',... |
2011 cfl draft | https://en.wikipedia.org/wiki/2011_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30108930-6.html.csv | count | two of the players drafted played the rb position . | {'scope': 'all', 'criterion': 'equal', 'value': 'rb', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'rb'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to rb .', 'tostr': 'filter_eq { all_rows ; position ; rb }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filte... | eq { count { filter_eq { all_rows ; position ; rb } } ; 2 } = true | select the rows whose position record fuzzily matches to rb . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, 'rb_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', 'rb_6': 'rb', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'rb_6': [0], '2_7': [2]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['32', 'winnipeg blue bombers ( via edmonton via winnipeg )', 'carl volny', 'rb', 'central michigan'], ['33', 'hamilton tiger - cats ( via edmonton )', 'patrick jean - mary', 'lb', 'howard'], ['34', 'calgary stampeders ( via bc )', 'matt walter', 'rb', 'calgary'], ['35', 'toronto argonauts', 'gregory alexandre', 'dl',... |
gartell light railway | https://en.wikipedia.org/wiki/Gartell_Light_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1160735-1.html.csv | comparative | andrew was incorporated into the gartell light railway before amanda was . | {'row_1': '2', 'row_2': '1', 'col': '5', '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', 'name', 'andrew'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to andrew .', 'tostr': 'filter_eq { all_rows ; name ; andrew }'}, 'date'], 'result': None, 'ind': 2, 'tostr': '... | less { hop { filter_eq { all_rows ; name ; andrew } ; date } ; hop { filter_eq { all_rows ; name ; amanda } ; date } } = true | select the rows whose name record fuzzily matches to andrew . take the date record of this row . select the rows whose name record fuzzily matches to amanda . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'andrew_8': 8, 'date_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'amanda_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'andrew_8': 'andrew', 'date_9': 'date', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'amanda_12': 'amanda', 'date_13... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'andrew_8': [0], 'date_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'amanda_12': [1], 'date_13': [3]} | ['number', 'name', 'builder', 'type', 'date'] | [['1', 'amanda', 'gartell light railway', 'bo - bodh', '2000'], ['2', 'andrew', 'baguley - drewry', '4wdh', '1973'], ['5', 'alison', 'alan keef', '4wdh', '1993'], ['6', 'mr g', 'north dorset locomotive works', '0 - 4 - 2t', '1998'], ['9', 'jean', 'north dorset locomotive works', '0 - 4 - 0', '2008']] |
miss usa 1980 | https://en.wikipedia.org/wiki/Miss_USA_1980 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15532342-2.html.csv | aggregation | the average swimsuit score of contestants in miss usa 1980 was 8.255 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '8.255', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'swimsuit'], 'result': '8.255', 'ind': 0, 'tostr': 'avg { all_rows ; swimsuit }'}, '8.255'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; swimsuit } ; 8.255 } = true', 'tointer': 'the average of the swimsuit record of all rows is 8.25... | round_eq { avg { all_rows ; swimsuit } ; 8.255 } = true | the average of the swimsuit record of all rows is 8.255 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'swimsuit_4': 4, '8.255_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'swimsuit_4': 'swimsuit', '8.255_5': '8.255'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'swimsuit_4': [0], '8.255_5': [1]} | ['state', 'preliminary average', 'interview', 'swimsuit', 'evening gown', 'semifinal average'] | [['nebraska', '8.450 ( 5 )', '7.938 ( 10 )', '7.489 ( 11 )', '7.832 ( 8 )', '7.753 ( 10 )'], ['arizona', '8.317 ( 8 )', '8.950 ( 4 )', '8.670 ( 4 )', '8.701 ( 2 )', '8.774 ( 2 )'], ['south carolina', '9.086 ( 1 )', '9.082 ( 1 )', '9.097 ( 1 )', '9.567 ( 1 )', '9.249 ( 1 )'], ['minnesota', '8.083 ( 12 )', '7.858 ( 11 )'... |
volleyball at the 2004 summer olympics - men 's team rosters | https://en.wikipedia.org/wiki/Volleyball_at_the_2004_Summer_Olympics_%E2%80%93_Men%27s_team_rosters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15859432-12.html.csv | comparative | on the men 's volleyball team at the 2004 summer olympics , kevin barnett weighed 9 less than gabriel gardner . | {'row_1': '11', 'row_2': '12', 'col': '4', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '9', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'kevin barnett'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to kevin barnett .', 'tostr': 'filter_eq { all_rows ; name ; kevin barnett }'}, ... | eq { diff { hop { filter_eq { all_rows ; name ; kevin barnett } ; weight } ; hop { filter_eq { all_rows ; name ; gabriel gardner } ; weight } } ; -9 } = true | select the rows whose name record fuzzily matches to kevin barnett . take the weight record of this row . select the rows whose name record fuzzily matches to gabriel gardner . take the weight record of this row . the second record is 9 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, 'name_8': 8, 'kevin barnett_9': 9, 'weight_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'name_12': 12, 'gabriel gardner_13': 13, 'weight_14': 14, '-9_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', 'name_8': 'name', 'kevin barnett_9': 'kevin barnett', 'weight_10': 'weight', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'name_12': 'name'... | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'name_8': [0], 'kevin barnett_9': [0], 'weight_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'name_12': [1], 'gabriel gardner_13': [1], 'weight_14': [3], '-9_15': [5]} | ['name', 'date of birth', 'height', 'weight', 'spike', 'block'] | [['lloy ball', '17.02.1972', '203', '95', '351', '316'], ['erik sullivan', '09.08.1972', '193', '86', '340', '320'], ['phillip eatherton', '02.01.1974', '206', '101', '356', '335'], ['donald suxho', '21.02.1976', '196', '98', '337', '319'], ['william priddy', '01.10.1977', '196', '89', '353', '330'], ['ryan millar', '2... |
1995 - 96 winnipeg jets season | https://en.wikipedia.org/wiki/1995%E2%80%9396_Winnipeg_Jets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14052745-12.html.csv | comparative | jason diog was picked in an earlier round in the 1995-96 winnipeg jets season than robert deciantis . | {'row_1': '3', 'row_2': '11', 'col': '1', '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', 'player', 'jason doig'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to jason doig .', 'tostr': 'filter_eq { all_rows ; player ; jason doig }'}, 'round'], 'result': None, '... | less { hop { filter_eq { all_rows ; player ; jason doig } ; round } ; hop { filter_eq { all_rows ; player ; robert deciantis } ; round } } = true | select the rows whose player record fuzzily matches to jason doig . take the round record of this row . select the rows whose player record fuzzily matches to robert deciantis . take the round record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'jason doig_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'robert deciantis_12': 12, 'round_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'jason doig_8': 'jason doig', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'robert decia... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'jason doig_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'robert deciantis_12': [1], 'round_13': [3]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team'] | [['1', 'shane doan', 'centre', 'canada', 'kamloops blazers ( whl )'], ['2', 'marc chouinard', 'centre', 'canada', 'beauport harfangs ( qmjhl )'], ['2', 'jason doig', 'defence', 'canada', 'laval titan collège français ( qmjhl )'], ['3', 'brad isbister', 'defence', 'canada', 'portland winter hawks ( whl )'], ['4', 'justi... |
2004 brazilian grand prix | https://en.wikipedia.org/wiki/2004_Brazilian_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1099518-2.html.csv | unique | in the 2004 brazilian grand prix , of the drivers that completed 71 laps , the only one that had a renault as a constructor was fernando alonso . | {'scope': 'subset', 'row': '4', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'renault', 'subset': {'col': '3', 'criterion': 'equal', 'value': '71'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '71'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; laps ; 71 }', 'tointer': 'select the rows whose laps record is equal to 71 .'}, 'constructor', 'renault'], 'result': ... | and { only { filter_eq { filter_eq { all_rows ; laps ; 71 } ; constructor ; renault } } ; eq { hop { filter_eq { filter_eq { all_rows ; laps ; 71 } ; constructor ; renault } ; driver } ; fernando alonso } } = true | select the rows whose laps record is equal to 71 . among these rows , select the rows whose constructor record fuzzily matches to renault . there is only one such row in the table . the driver record of this unqiue row is fernando alonso . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_eq_0': 0, 'all_rows_7': 7, 'laps_8': 8, '71_9': 9, 'constructor_10': 10, 'renault_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'driver_12': 12, 'fernando alonso_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_eq_0': 'filter_eq', 'all_rows_7': 'all_rows', 'laps_8': 'laps', '71_9': '71', 'constructor_10': 'constructor', 'renault_11': 'renault', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'driver_12': 'driver', 'fernando alonso... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_eq_0': [1], 'all_rows_7': [0], 'laps_8': [0], '71_9': [0], 'constructor_10': [1], 'renault_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'driver_12': [3], 'fernando alonso_13': [4]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['juan pablo montoya', 'williams - bmw', '71', '1:28:01.451', '2'], ['kimi räikkönen', 'mclaren - mercedes', '71', '+ 1.022', '3'], ['rubens barrichello', 'ferrari', '71', '+ 24.099', '1'], ['fernando alonso', 'renault', '71', '+ 48.508', '8'], ['ralf schumacher', 'williams - bmw', '71', '+ 49.740', '7'], ['takuma sat... |
madawaska county , new brunswick | https://en.wikipedia.org/wiki/Madawaska_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-171250-2.html.csv | aggregation | the parishes of madawaska county , new brunswick , have a total population of 9617 . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '9617', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'population'], 'result': '9617', 'ind': 0, 'tostr': 'sum { all_rows ; population }'}, '9617'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; population } ; 9617 } = true', 'tointer': 'the sum of the population record of all rows is 961... | round_eq { sum { all_rows ; population } ; 9617 } = true | the sum of the population record of all rows is 9617 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'population_4': 4, '9617_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'population_4': 'population', '9617_5': '9617'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'population_4': [0], '9617_5': [1]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['saint - joseph', 'parish', '321.87', '1696', '1472 of 5008'], ['saint - jacques', 'parish', '298.82', '1607', '1531 of 5008'], ['sainte - anne', 'parish', '369.25', '1081', '1942 of 5008'], ['saint - léonard', 'parish', '343.95', '1039', '2011 of 5008'], ['saint - basile', 'parish', '129.73', '799', '2364 of 5008'],... |
ect mainline rail | https://en.wikipedia.org/wiki/ECT_Mainline_Rail | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15805928-1.html.csv | count | three of the rails have fragonset black as their livery . | {'scope': 'all', 'criterion': 'equal', 'value': 'fragonset black', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'livery', 'fragonset black'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose livery record fuzzily matches to fragonset black .', 'tostr': 'filter_eq { all_rows ; livery ; fragonset black }'}], 'result': '3', ... | eq { count { filter_eq { all_rows ; livery ; fragonset black } } ; 3 } = true | select the rows whose livery record fuzzily matches to fragonset black . 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, 'livery_5': 5, 'fragonset black_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', 'livery_5': 'livery', 'fragonset black_6': 'fragonset black', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'livery_5': [0], 'fragonset black_6': [0], '3_7': [2]} | ['number', 'class', 'name', 'livery', 'notes'] | [['31128', '31', 'charybdis', 'fragonset black', 'now operated by nemesis rail'], ['31452', '31', 'minotaur', 'fragonset black', 'now operated by network rail'], ['31454', '31', 'the heart of wessex', 'intercity swallow', 'now operated by network rail'], ['31468', '31', 'hydra', 'fragonset black', 'now operated by netw... |
list of csi : ny characters | https://en.wikipedia.org/wiki/List_of_CSI%3A_NY_characters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11240028-1.html.csv | majority | most of the characters on csi : ny had a last appearance on today is life . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'today is life', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'last appearance', 'today is life'], 'result': True, 'ind': 0, 'tointer': 'for the last appearance records of all rows , most of them fuzzily match to today is life .', 'tostr': 'most_eq { all_rows ; last appearance ; today is life } = true'} | most_eq { all_rows ; last appearance ; today is life } = true | for the last appearance records of all rows , most of them fuzzily match to today is life . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'last appearance_3': 3, 'today is life_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'last appearance_3': 'last appearance', 'today is life_4': 'today is life'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'last appearance_3': [0], 'today is life_4': [0]} | ['character', 'portrayed by', 'first appearance', 'last appearance', 'duration', 'episodes'] | [['mac taylor csi detective', 'gary sinise', 'blink 1 , 2 , 3', 'today is life', '1.01 - 9.17', '197'], ['jo danville csi detective', 'sela ward', 'the 34th floor', 'today is life', '7.01 - 9.17', '57'], ['danny messer csi detective', 'carmine giovinazzo', 'blink 1', 'today is life', '1.01 - 9.17', '197'], ['lindsay mo... |
international cricket in 2008 - 09 | https://en.wikipedia.org/wiki/International_cricket_in_2008%E2%80%9309 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17324788-32.html.csv | superlative | the earliest game in international cricket in 2008-09 was on january 27th . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'min', 'args': ['all_rows', 'date'], 'result': '27 january', 'ind': 0, 'tostr': 'min { all_rows ; date }', 'tointer': 'the minimum date record of all rows is 27 january .'}, '27 january'], 'result': True, 'ind': 1, 'tostr': 'eq { min { all_rows ; date } ; 27 january } = true', 'tointer'... | eq { min { all_rows ; date } ; 27 january } = true | the minimum date record of all rows is 27 january . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'min_0': 0, 'all_rows_3': 3, 'date_4': 4, '27 january_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'min_0': 'min', 'all_rows_3': 'all_rows', 'date_4': 'date', '27 january_5': '27 january'} | {'eq_1': [2], 'result_2': [], 'min_0': [1], 'all_rows_3': [0], 'date_4': [0], '27 january_5': [1]} | ['date', 'home captain', 'away captain', 'venue', 'result'] | [['27 january', 'steve tikolo', 'prosper utseya', 'mombasa sports club , mombasa', 'by 109 runs'], ['29 january', 'steve tikolo', 'prosper utseya', 'mombasa sports club , mombasa', 'by 151 runs'], ['31 january', 'steve tikolo', 'prosper utseya', 'nairobi gymkhana club , nairobi', 'by 4 wickets'], ['1 february', 'steve ... |
david sigachev | https://en.wikipedia.org/wiki/David_Sigachev | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25421463-1.html.csv | aggregation | the average number of races per series for david sagachev is 7.6 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '7.6', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'races'], 'result': '7.6', 'ind': 0, 'tostr': 'avg { all_rows ; races }'}, '7.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; races } ; 7.6 } = true', 'tointer': 'the average of the races record of all rows is 7.6 .'} | round_eq { avg { all_rows ; races } ; 7.6 } = true | the average of the races record of all rows is 7.6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'races_4': 4, '7.6_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'races_4': 'races', '7.6_5': '7.6'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'races_4': [0], '7.6_5': [1]} | ['season', 'series', 'team name', 'races', 'wins', 'points', 'final placing'] | [['2007', 'formula renault 2.0 nec', 'sl formula racing', '16', '0', '67', '21st'], ['2007', 'eurocup formula renault 2.0', 'sl formula racing', '2', '0', 'n / a', 'nc'], ['2009', 'porsche carrera cup germany', 'tolimit seyffarth motorsport', '9', '0', '38', '13th'], ['2009', 'porsche supercup', 'tolimit seyffarth moto... |
comparison of cad , cam and cae file viewers | https://en.wikipedia.org/wiki/Comparison_of_CAD%2C_CAM_and_CAE_file_viewers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18913138-1.html.csv | count | there are two file viewers that do not support 3d . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'no', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '3d support', 'no'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 3d support record fuzzily matches to no .', 'tostr': 'filter_eq { all_rows ; 3d support ; no }'}], 'result': '2', 'ind': 1, 'tostr': 'count {... | eq { count { filter_eq { all_rows ; 3d support ; no } } ; 2 } = true | select the rows whose 3d support record fuzzily matches to no . 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, '3d support_5': 5, 'no_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', '3d support_5': '3d support', 'no_6': 'no', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], '3d support_5': [0], 'no_6': [0], '2_7': [2]} | ['latest stable release', 'developer', '3d support', 'runs on posix style systems', 'runs on windows', 'user interface language ( s )'] | [['1.0', 'eethal inc', 'yes', 'no', 'yes', 'en'], ['6.5', 'data design system asa', 'yes', 'no', 'yes', 'en'], ['v 2.13.15 ( 04 / 2013 )', 'dxf viewer', 'yes', 'yes ( java )', 'yes ( java )', 'en , de'], ['3.46', 'autodwg', 'yes', 'no', 'yes', 'en'], ['14', 'advanced computer solutions', 'yes', 'no', 'yes', 'en'], ['1.... |
1994 - 95 cleveland cavaliers season | https://en.wikipedia.org/wiki/1994%E2%80%9395_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16188254-7.html.csv | count | chris mills had five leading scorer performances in the 1994 - 95 cleveland cavaliers season . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'chris mills', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'leading scorer', 'chris mills'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose leading scorer record fuzzily matches to chris mills .', 'tostr': 'filter_eq { all_rows ; leading scorer ; chris mills }'}], 're... | eq { count { filter_eq { all_rows ; leading scorer ; chris mills } } ; 5 } = true | select the rows whose leading scorer record fuzzily matches to chris mills . 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, 'leading scorer_5': 5, 'chris mills_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', 'leading scorer_5': 'leading scorer', 'chris mills_6': 'chris mills', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'leading scorer_5': [0], 'chris mills_6': [0], '5_7': [2]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['march 2', 'cleveland', '84 - 90', 'dallas', 'chris mills , 16 points', 'reunion arena 12194', '33 - 23'], ['march 4', 'new york', '89 - 76', 'cleveland', 'hot rod williams , 20 points', 'gund arena 20562', '33 - 24'], ['march 7', 'detroit', '81 - 89', 'cleveland', 'chris mills , 24 points', 'gund arena 20562', '34 -... |
2003 u.s. bank cleveland grand prix | https://en.wikipedia.org/wiki/2003_U.S._Bank_Cleveland_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18943126-1.html.csv | superlative | paul tracy had the fastest time for the 1st qualifier at the 2003 u.s. bank cleveland grand prix . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '2', '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', 'qual 1'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; qual 1 }'}, 'name'], 'result': 'paul tracy', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; qual 1 } ; name }'}, 'paul tracy'], 'result': True, 'ind': 2, 'to... | eq { hop { argmin { all_rows ; qual 1 } ; name } ; paul tracy } = true | select the row whose qual 1 record of all rows is minimum . the name record of this row is paul tracy . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'qual 1_5': 5, 'name_6': 6, 'paul tracy_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'qual 1_5': 'qual 1', 'name_6': 'name', 'paul tracy_7': 'paul tracy'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'qual 1_5': [0], 'name_6': [1], 'paul tracy_7': [2]} | ['name', 'team', 'qual 1', 'qual 2', 'best'] | [['sébastien bourdais', 'newman / haas racing', '59.163', '58.014', '58.014'], ['paul tracy', "team player 's", '58.405', '1:01.294', '58.405'], ['patrick carpentier', "team player 's", '58.868', '58.449', '58.449'], ['oriol servià', 'patrick racing', '59.186', '58.502', '58.502'], ['bruno junqueira', 'newman / haas ra... |
united states house of representatives elections , 1864 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1864 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1434834-3.html.csv | ordinal | in the us house of representatives at the time of the 1864 election , george h pendleton was the first representative from ohio to have been originally elected to the house . | {'row': '1', 'col': '4', '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', 'first elected', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 1 }'}, 'incumbent'], 'result': 'george h pendleton', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 1... | eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; george h pendleton } = true | select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is george h pendleton . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '1_6': 6, 'incumbent_7': 7, 'george h pendleton_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', 'first elected_5': 'first elected', '1_6': '1', 'incumbent_7': 'incumbent', 'george h pendleton_8': 'george h pendleton'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1_6': [0], 'incumbent_7': [1], 'george h pendleton_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result'] | [['ohio 1', 'george h pendleton', 'democratic', '1856', 'retired republican gain'], ['ohio 2', 'alexander long', 'democratic', '1862', 'lost re - nomination republican gain'], ['ohio 3', 'robert c schenck', 'republican', '1862', 're - elected'], ['ohio 4', 'john f mckinney', 'democratic', '1862', 'lost re - election re... |
the whole thing 's started | https://en.wikipedia.org/wiki/The_Whole_Thing%27s_Started | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17071146-1.html.csv | aggregation | the median length of the 7 " single releases of the album the whole thing 's started , rounded to the nearest second , is 3:43 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '3:43', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'length'], 'result': '3:43', 'ind': 0, 'tostr': 'avg { all_rows ; length }'}, '3:43'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; length } ; 3:43 } = true', 'tointer': 'the average of the length record of all rows is 3:43 .'} | round_eq { avg { all_rows ; length } ; 3:43 } = true | the average of the length record of all rows is 3:43 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'length_4': 4, '3:43_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'length_4': 'length', '3:43_5': '3:43'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'length_4': [0], '3:43_5': [1]} | ['date', 'tracks', 'length', 'label', 'catalog'] | [['1977', 'do what you do', '3:47', 'cbs', 'ba 222304'], ['1977', "it 's automatic", '2:57', 'cbs', 'ba 222304'], ['1977', "that 's how the whole thing started", '4:03', 'cbs', 'ba 222325'], ['1977', "there 's nothing i can do", '3:38', 'cbs', 'ba 222325'], ['1978', 'do it again', '3:35', 'columbia', 'c4 - 8217'], ['19... |
russia women 's national rugby union team | https://en.wikipedia.org/wiki/Russia_women%27s_national_rugby_union_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13106281-1.html.csv | count | the russia women 's national rugby union team did n't lose a game in 5 different years . | {'scope': 'all', 'criterion': 'equal', 'value': '0', 'result': '5', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'lost', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lost record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; lost ; 0 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; lost ; 0... | eq { count { filter_eq { all_rows ; lost ; 0 } } ; 5 } = true | select the rows whose lost record is equal to 0 . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'lost_5': 5, '0_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'lost_5': 'lost', '0_6': '0', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'lost_5': [0], '0_6': [0], '5_7': [2]} | ['first game', 'played', 'drawn', 'lost', 'percentage'] | [['2006', '3', '0', '0', '100.00 %'], ['2005', '2', '0', '0', '100.00 %'], ['1994', '2', '0', '2', '0.00 %'], ['2008', '3', '0', '0', '100.00 %'], ['2010', '1', '0', '0', '100.00 %'], ['1998', '4', '0', '4', '0.00 %'], ['1997', '4', '0', '1', '75.00 %'], ['1998', '4', '0', '3', '25.00 %'], ['2005', '3', '0', '0', '100.... |
katarina srebotnik | https://en.wikipedia.org/wiki/Katarina_Srebotnik | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1729366-4.html.csv | majority | most of the tournaments took place in the first decade of the 2000 's . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '2000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'date', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , most of them are greater than 2000 .', 'tostr': 'most_greater { all_rows ; date ; 2000 } = true'} | most_greater { all_rows ; date ; 2000 } = true | for the date records of all rows , most of them are greater than 2000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '2000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '2000_4': '2000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '2000_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'opponent in final', 'score in final'] | [['winner', 'april 11 , 1999', 'estoril , portugal', 'clay', 'rita kuti - kis', '6 - 3 , 6 - 1'], ['runner - up', 'february 24 , 2002', 'bogotá , colombia', 'clay', 'fabiola zuluaga', '1 - 6 , 4 - 6'], ['winner', 'march 3 , 2002', 'acapulco , mexico', 'clay', 'paola suárez', '6 - 7 ( 1 - 7 ) , 6 - 4 , 6 - 2'], ['runner... |
television in thailand | https://en.wikipedia.org/wiki/Television_in_Thailand | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18987481-3.html.csv | superlative | bbtv ch7 had the highest market share of television in thailand in 2011 1h . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', '2011 1h'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; 2011 1h }'}, 'tv station ( operator )'], 'result': 'bbtv ch7', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; 2011 1h } ; tv station ( operator ) }'}, 'bbtv... | eq { hop { argmax { all_rows ; 2011 1h } ; tv station ( operator ) } ; bbtv ch7 } = true | select the row whose 2011 1h record of all rows is maximum . the tv station ( operator ) record of this row is bbtv ch7 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, '2011 1h_5': 5, 'tv station (operator)_6': 6, 'bbtv ch7_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', '2011 1h_5': '2011 1h', 'tv station (operator)_6': 'tv station ( operator )', 'bbtv ch7_7': 'bbtv ch7'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], '2011 1h_5': [0], 'tv station (operator)_6': [1], 'bbtv ch7_7': [2]} | ['tv station ( operator )', '2005', '2006', '2007', '2008', '2009', '2010', '2011 1h'] | [['bbtv ch7', '42.4', '41.3', '42.0', '44.7', '45.4', '43.8', '47.5'], ['tv3', '24.5', '25.6', '29.5', '26.8', '27.7', '29.5', '29.0'], ['tv5', '8.1', '7.3', '6.7', '7.6', '8.6', '8.0', '6.9'], ['modernine tv', '10.3', '10.2', '9.2', '9.6', '9.9', '9.7', '9.2'], ['nbt', '2.9', '3.0', '2.4', '4.9', '3.4', '3.4', '2.4'],... |
1985 pga tour | https://en.wikipedia.org/wiki/1985_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14640372-3.html.csv | aggregation | in the 1985 pga tour , the average winnings of the top five finishers was $ 426,356.60 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '$ 426,356.60', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'earnings'], 'result': '$ 426,356.60', 'ind': 0, 'tostr': 'avg { all_rows ; earnings }'}, '$ 426,356.60'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; earnings } ; $ 426,356.60 } = true', 'tointer': 'the average of the earnings recor... | round_eq { avg { all_rows ; earnings } ; $ 426,356.60 } = true | the average of the earnings record of all rows is $ 426,356.60 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'earnings_4': 4, '$426,356.60_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'earnings_4': 'earnings', '$426,356.60_5': '$ 426,356.60'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'earnings_4': [0], '$426,356.60_5': [1]} | ['rank', 'player', 'country', 'earnings', 'events', 'wins'] | [['1', 'curtis strange', 'united states', '542321', '25', '3'], ['2', 'lanny wadkins', 'united states', '446893', '24', '3'], ['3', 'calvin peete', 'united states', '384489', '22', '2'], ['4', 'jim thorpe', 'united states', '379091', '28', '2'], ['5', 'raymond floyd', 'united states', '378989', '22', '1']] |
1949 - 50 new york rangers season | https://en.wikipedia.org/wiki/1949%E2%80%9350_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17311417-7.html.csv | ordinal | in the 1949-50 new york rangers season , the 2nd to last game had a score of 8-7 . | {'row': '12', 'col': '2', 'order': '12', 'col_other': '4', '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', 'march', '12'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; march ; 12 }'}, 'score'], 'result': '8 - 7', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; march ; 12 } ; score }'}, '8 - 7'], 'result': Tr... | eq { hop { nth_argmin { all_rows ; march ; 12 } ; score } ; 8 - 7 } = true | select the row whose march record of all rows is 12th minimum . the score record of this row is 8 - 7 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'march_5': 5, '12_6': 6, 'score_7': 7, '8 - 7_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', 'march_5': 'march', '12_6': '12', 'score_7': 'score', '8 - 7_8': '8 - 7'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'march_5': [0], '12_6': [0], 'score_7': [1], '8 - 7_8': [2]} | ['game', 'march', 'opponent', 'score', 'record'] | [['58', '1', 'detroit red wings', '5 - 2', '24 - 23 - 11'], ['59', '4', 'boston bruins', '5 - 1', '24 - 24 - 11'], ['60', '5', 'toronto maple leafs', '5 - 2', '25 - 24 - 11'], ['61', '8', 'chicago black hawks', '4 - 2', '26 - 24 - 11'], ['62', '9', 'detroit red wings', '3 - 1', '27 - 24 - 11'], ['63', '11', 'toronto ma... |
three rivers conference ( indiana ) | https://en.wikipedia.org/wiki/Three_Rivers_Conference_%28Indiana%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15176211-1.html.csv | count | 3 schools in the three rivers conference are located in wabash . | {'scope': 'all', 'criterion': 'equal', 'value': 'wabash', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'wabash'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to wabash .', 'tostr': 'filter_eq { all_rows ; location ; wabash }'}], 'result': '3', 'ind': 1, 'tostr': 'c... | eq { count { filter_eq { all_rows ; location ; wabash } } ; 3 } = true | select the rows whose location record fuzzily matches to wabash . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location_5': 5, 'wabash_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location_5': 'location', 'wabash_6': 'wabash', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'wabash_6': [0], '3_7': [2]} | ['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'county', 'year joined', 'previous conference'] | [['manchester', 'north manchester', 'squires', '434', 'aa', '85 wabash', '1976', 'northern lakes'], ['northfield', 'wabash', 'norsemen', '380', 'aa', '85 wabash', '1971', 'none ( new school )'], ['north miami', 'denver', 'warriors', '348', 'a', '52 miami', '1971', 'mid - indiana'], ['rochester community', 'rochester', ... |
princess royal | https://en.wikipedia.org/wiki/Princess_Royal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-172426-1.html.csv | comparative | of the princess royals , anne , princess royal 1709 - 1759 , was married 63 years before charlotte , princess royal 1766 - 1828 . | {'row_1': '2', 'row_2': '3', 'col': '5', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '63', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name dates', 'anne , princess royal 1709 - 1759'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name dates record fuzzily matches to anne , princess royal 1709 - 1759 .', 'tostr'... | eq { diff { hop { filter_eq { all_rows ; name dates ; anne , princess royal 1709 - 1759 } ; date married } ; hop { filter_eq { all_rows ; name dates ; charlotte , princess royal 1766 - 1828 } ; date married } } ; -63 } = true | select the rows whose name dates record fuzzily matches to anne , princess royal 1709 - 1759 . take the date married record of this row . select the rows whose name dates record fuzzily matches to charlotte , princess royal 1766 - 1828 . take the date married record of this row . the second record is 63 larger than the... | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'name dates_8': 8, 'anne , princess royal 1709 - 1759_9': 9, 'date married_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'name dates_12': 12, 'charlotte , princess royal 1766 - 1828_13': 13, 'date married_... | {'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', 'name dates_8': 'name dates', 'anne , princess royal 1709 - 1759_9': 'anne , princess royal 1709 - 1759', 'date married_10': 'date married', 'num_hop_3': 'num_hop', 'filter_str_eq_1... | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'name dates_8': [0], 'anne , princess royal 1709 - 1759_9': [0], 'date married_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'name dates_12': [1], 'charlotte , princess royal 1766 - 1828_1... | ['order', 'name dates', 'princess royal from ( date ) to ( date )', 'parent', 'date married', 'husband dates'] | [['1', 'mary , princess royal 1631 - 1660', '1642 - 1660', 'charles i 1600 - 1649', '1641', 'william ii , prince of orange 1626 - 1650'], ['2', 'anne , princess royal 1709 - 1759', '1727 - 1759', 'george ii 1683 - 1760', '1734', 'william iv , prince of orange 1711 - 1751'], ['3', 'charlotte , princess royal 1766 - 1828... |
north state conference | https://en.wikipedia.org/wiki/North_State_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16168849-1.html.csv | superlative | in the north state conference , the highest enrollment is at east carolina university . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'enrollment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment }'}, 'institution'], 'result': 'east carolina university', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; institution }'}, 'eas... | eq { hop { argmax { all_rows ; enrollment } ; institution } ; east carolina university } = true | select the row whose enrollment record of all rows is maximum . the institution record of this row is east carolina university . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'institution_6': 6, 'east carolina university_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', 'institution_6': 'institution', 'east carolina university_7': 'east carolina university'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'institution_6': [1], 'east carolina university_7': [2]} | ['institution', 'location', 'founded', 'type', 'enrollment', 'nickname', 'joined', 'left', 'current conference'] | [['anderson university', 'anderson , south carolina', '1911', 'private', '2907', 'trojans', '1998', '2010', 'sac'], ['appalachian state university', 'boone , north carolina', '1899', 'public', '17589', 'mountaineers', '1930', '1967', 'socon ( sun belt in 2014 ) ( ncaa division i )'], ['catawba college', 'salisbury , no... |
nevada gaming area | https://en.wikipedia.org/wiki/Nevada_gaming_area | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25438110-5.html.csv | aggregation | there is a total of 217 casinos in the nevada gaming area . | {'scope': 'all', 'col': '1', 'type': 'sum', 'result': '217', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'casinos'], 'result': '217', 'ind': 0, 'tostr': 'sum { all_rows ; casinos }'}, '217'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; casinos } ; 217 } = true', 'tointer': 'the sum of the casinos record of all rows is 217 .'} | round_eq { sum { all_rows ; casinos } ; 217 } = true | the sum of the casinos record of all rows is 217 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'casinos_4': 4, '217_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'casinos_4': 'casinos', '217_5': '217'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'casinos_4': [0], '217_5': [1]} | ['casinos', 'county', 'road', '1 - jul - 08', 'fy07 millions', 'fy08 millions', 'fy09 millions'] | [['149', 'clark', 'i - 15', '1865746', '10538', '10172', '9081'], ['32', 'washoe', 'i - 80', '410443', '1045', '977', '856'], ['17', 'elko', 'i - 80', '47071', '324', '303', '279'], ['5', 'south lake tahoe', 'route 50', '45180', '283', '307', '264'], ['14', 'carson valley', 'route 395', '54867', '120', '114', '102']] |
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