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list of schools in the bay of plenty region | https://en.wikipedia.org/wiki/List_of_schools_in_the_Bay_of_Plenty_Region | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12174210-5.html.csv | count | two of the schools are for years one through eight . | {'scope': 'all', 'criterion': 'equal', 'value': '1 - 8', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'years', '1 - 8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose years record fuzzily matches to 1 - 8 .', 'tostr': 'filter_eq { all_rows ; years ; 1 - 8 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filte... | eq { count { filter_eq { all_rows ; years ; 1 - 8 } } ; 2 } = true | select the rows whose years record fuzzily matches to 1 - 8 . 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, 'years_5': 5, '1 - 8_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', 'years_5': 'years', '1 - 8_6': '1 - 8', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'years_5': [0], '1 - 8_6': [0], '2_7': [2]} | ['name', 'years', 'gender', 'area', 'authority', 'decile'] | [['kawerau putauaki school', '1 - 8', 'coed', 'kawerau', 'state', '1'], ['kawerau south school', '1 - 6', 'coed', 'kawerau', 'state', '1'], ['kawerau teen parent unit', '-', '-', 'kawerau', 'state', '1'], ['tarawera high school', '7 - 13', 'coed', 'kawerau', 'state', '1'], ['te whata tau o putauaki', '1 - 8', 'coed', '... |
comparison of e - book readers | https://en.wikipedia.org/wiki/Comparison_of_e-book_readers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1149661-3.html.csv | ordinal | notion ink makes the model that has the biggest screen size on the market . | {'row': '12', 'col': '4', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'screen size ( inch )', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; screen size ( inch ) ; 1 }'}, 'maker'], 'result': 'notion ink', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; screen size ( i... | eq { hop { nth_argmax { all_rows ; screen size ( inch ) ; 1 } ; maker } ; notion ink } = true | select the row whose screen size ( inch ) record of all rows is 1st maximum . the maker record of this row is notion ink . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'screen size (inch)_5': 5, '1_6': 6, 'maker_7': 7, 'notion ink_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', 'screen size (inch)_5': 'screen size ( inch )', '1_6': '1', 'maker_7': 'maker', 'notion ink_8': 'notion ink'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'screen size (inch)_5': [0], '1_6': [0], 'maker_7': [1], 'notion ink_8': [2]} | ['maker', 'model', 'intro year', 'screen size ( inch )', 'screen type', 'weight', 'screen pixels', 'hours reading', 'touch screen', 'wireless network', 'internal storage', 'card reader slot'] | [['aluratek', 'libre touch ebook reader', '2011', '7', 'lcd', 'g ( oz )', '480 800', '8', 'yes', 'yes , wi - fi', '4 gb', 'microsd'], ['aluratek', 'libre air ebook reader', '2011', '5', 'lcd', 'g ( oz )', '480 640', '20', 'no', 'yes , wi - fi', '512 mb', 'microsd'], ['aluratek', 'libre color ebook reader', '2010', '7',... |
winter garden region | https://en.wikipedia.org/wiki/Winter_Garden_Region | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10998425-1.html.csv | count | according to the winter garden region population statistics , 3 counties that had population above 1000 in 1900 had estimated population above 10,000 in 2006 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '10000', 'result': '2', 'col': '6', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '1000'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', '1900', '1000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; 1900 ; 1000 }', 'tointer': 'select the rows whose 1900 record is greater than 1000 .'}, '2006 est', '100... | eq { count { filter_greater { filter_greater { all_rows ; 1900 ; 1000 } ; 2006 est ; 10000 } } ; 2 } = true | select the rows whose 1900 record is greater than 1000 . among these rows , select the rows whose 2006 est record is greater than 10000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, '1900_6': 6, '1000_7': 7, '2006 est_8': 8, '10000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', '1900_6': '1900', '1000_7': '1000', '2006 est_8': '2006 est', '10000_9': '10000', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], '1900_6': [0], '1000_7': [0], '2006 est_8': [1], '10000_9': [1], '2_10': [3]} | ['county', '1900', '1930', '1950', '2000', '2006 est'] | [['dimmit', '1106', '8828', '10654', '10248', '10385'], ['frio', '4200', '9411', '10357', '16252', '16336'], ['la salle', '2303', '8228', '7485', '5866', '5969'], ['zavala', '792', '10349', '11201', '11600', '12036'], ['total', '8401', '36816', '39697', '43966', '44726']] |
list of television stations in hong kong | https://en.wikipedia.org/wiki/List_of_television_stations_in_Hong_Kong | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22274142-1.html.csv | comparative | atv world was launched earlier than tvb pearl in hong kong . | {'row_1': '4', 'row_2': '3', 'col': '6', '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', 'channel', 'atv world'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose channel record fuzzily matches to atv world .', 'tostr': 'filter_eq { all_rows ; channel ; atv world }'}, 'launch date'], 'result': N... | less { hop { filter_eq { all_rows ; channel ; atv world } ; launch date } ; hop { filter_eq { all_rows ; channel ; tvb pearl } ; launch date } } = true | select the rows whose channel record fuzzily matches to atv world . take the launch date record of this row . select the rows whose channel record fuzzily matches to tvb pearl . take the launch date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'channel_7': 7, 'atv world_8': 8, 'launch date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'channel_11': 11, 'tvb pearl_12': 12, 'launch date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'channel_7': 'channel', 'atv world_8': 'atv world', 'launch date_9': 'launch date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'channel_11': 'channel',... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'channel_7': [0], 'atv world_8': [0], 'launch date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'channel_11': [1], 'tvb pearl_12': [1], 'launch date_13': [3]} | ['ch -', 'channel', 'channel content', 'transmission', 'format', 'launch date', 'licence'] | [['1 ( a ) , 81 ( d )', 'tvb jade', "tvb 's main chinese ( cantonese ) channel", 'analog & digital', 'sdtv', '19 november 1967', 'tvb'], ['2 ( a ) , 11 ( d )', 'atv home', "atv 's main chinese ( cantonese ) channel", 'analog & digital', 'sdtv', '29 may 1957', 'atv'], ['3 ( a ) , 84 ( d )', 'tvb pearl', "tvb 's main eng... |
list of intel core i7 microprocessors | https://en.wikipedia.org/wiki/List_of_Intel_Core_i7_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18823880-10.html.csv | count | a total of three of the intel core i7 microprocessors have 8 mb of l3 cache . | {'scope': 'all', 'criterion': 'equal', 'value': '8 mb', 'result': '3', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'l3 cache', '8 mb'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose l3 cache record fuzzily matches to 8 mb .', 'tostr': 'filter_eq { all_rows ; l3 cache ; 8 mb }'}], 'result': '3', 'ind': 1, 'tostr': 'count {... | eq { count { filter_eq { all_rows ; l3 cache ; 8 mb } } ; 3 } = true | select the rows whose l3 cache record fuzzily matches to 8 mb . 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, 'l3 cache_5': 5, '8 mb_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', 'l3 cache_5': 'l3 cache', '8 mb_6': '8 mb', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'l3 cache_5': [0], '8 mb_6': [0], '3_7': [2]} | ['model number', 'sspec number', 'frequency', 'turbo', 'cores', 'l2 cache', 'l3 cache', 'i / o bus', 'mult', 'memory', 'voltage', 'tdp', 'socket', 'release date', 'part number ( s )', 'release price ( usd )'] | [['core i7 - 720qm', 'slbly ( b1 )', '1.6 ghz', '1 / 1 / 6 / 9', '4', '4 256 kb', '6 mb', 'dmi', '12', '2 ddr3 - 1333', '0.65 - 1.4 v', '45 w', 'socketg1', 'september 2009', 'by80607002907ahbx80607i7720qm', '364'], ['core i7 - 740qm', 'slbqg ( b1 )', '1.73 ghz', '1 / 1 / 6 / 9', '4', '4 256 kb', '6 mb', 'dmi', '13', '2... |
1970 - 71 california golden seals season | https://en.wikipedia.org/wiki/1970%E2%80%9371_California_Golden_Seals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18706961-1.html.csv | count | for the 1970 - 71 california golden seals season , of the players that came from the wchl , two of them were picked after round 2 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '2', 'result': '2', 'col': '1', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': 'wchl'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college / junior / club team', 'wchl'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; college / junior / club team ; wchl }', 'tointer': 'select the rows whose college / ju... | eq { count { filter_greater { filter_eq { all_rows ; college / junior / club team ; wchl } ; round ; 2 } } ; 2 } = true | select the rows whose college / junior / club team record fuzzily matches to wchl . among these rows , select the rows whose round record is greater than 2 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'college / junior / club team_6': 6, 'wchl_7': 7, 'round_8': 8, '2_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'college / junior / club team_6': 'college / junior / club team', 'wchl_7': 'wchl', 'round_8': 'round', '2_9': '2', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'college / junior / club team_6': [0], 'wchl_7': [0], 'round_8': [1], '2_9': [1], '2_10': [3]} | ['round', 'pick', 'player', 'nationality', 'college / junior / club team'] | [['1', '10', 'chris oddleifson', 'canada', 'winnipeg jets ( wchl )'], ['2', '19', 'pete laframboise', 'canada', "ottawa 67 's ( oha )"], ['3', '33', 'randy rota', 'canada', 'calgary centennials ( wchl )'], ['4', '47', 'ted mcaneeley', 'canada', 'edmonton oil kings ( wchl )'], ['5', '61', 'ray gibbs', 'canada', 'charlot... |
american seafoods | https://en.wikipedia.org/wiki/American_Seafoods | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15230458-1.html.csv | superlative | of the american seafoods ' ships , the one with the highest tonnage was northern eagle . | {'scope': 'all', 'col_superlative': '3', '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', 'tonnage'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; tonnage }'}, 'name'], 'result': 'northern eagle', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; tonnage } ; name }'}, 'northern eagle'], 'result': True, 'i... | eq { hop { argmax { all_rows ; tonnage } ; name } ; northern eagle } = true | select the row whose tonnage record of all rows is maximum . the name record of this row is northern eagle . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'tonnage_5': 5, 'name_6': 6, 'northern eagle_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'tonnage_5': 'tonnage', 'name_6': 'name', 'northern eagle_7': 'northern eagle'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'tonnage_5': [0], 'name_6': [1], 'northern eagle_7': [2]} | ['name', 'length', 'tonnage', 'built by', 'year', 'engines', 'horsepowers', 'former names'] | [['american dynasty', '272.0 feet', '3471', 'mangone shipyard , houston , tx', '1974', '2 , bergen diesel , brm - 8', '8000', 'artabaze , bure , sea bure'], ['american triumph', '285.0 feet', '4294', 'ls baier & co , portland , or', '1961', '2 , w채rtsil채 , 8r32d', '7939', 'acona'], ['northern jaeger', '337 feet', '3732... |
bruno giacomelli | https://en.wikipedia.org/wiki/Bruno_Giacomelli | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1219697-2.html.csv | aggregation | on average , bruno giacomelli scored about 2 points per race from 1977 to 1990 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '2', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '2', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 2 } = true', 'tointer': 'the average of the points record of all rows is 2 .'} | round_eq { avg { all_rows ; points } ; 2 } = true | the average of the points record of all rows is 2 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '2_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '2_5': '2'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '2_5': [1]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1977', 'marlboro team mclaren', 'mclaren m23', 'ford v8', '0'], ['1978', 'marlboro team mclaren', 'mclaren m26', 'ford v8', '0'], ['1979', 'autodelta', 'alfa romeo 177', 'alfa romeo f12', '0'], ['1979', 'autodelta', 'alfa romeo 179', 'alfa romeo v12', '0'], ['1980', 'marlboro team alfa romeo', 'alfa romeo 179', 'alf... |
united states house of representatives elections , 2000 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341423-40.html.csv | majority | a majority of those elected to the house of representatives in south carolina were republicans . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'republican', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to republican .', 'tostr': 'most_eq { all_rows ; party ; republican } = true'} | most_eq { all_rows ; party ; republican } = true | for the party records of all rows , most of them fuzzily match to republican . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'republican_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'republican_4': 'republican'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'republican_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['south carolina 1', 'mark sanford', 'republican', '1994', 'retired republican hold', 'henry brown ( r ) 60 % andy brack ( d ) 36 %'], ['south carolina 2', 'floyd spence', 'republican', '1970', 're - elected', 'floyd spence ( r ) 58 % jane frederick ( d ) 41 %'], ['south carolina 3', 'lindsey graham', 'republican', '1... |
seattle supersonics all - time roster | https://en.wikipedia.org/wiki/Seattle_SuperSonics_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16772687-7.html.csv | superlative | jake ford is the first player to join the seattle supersonics team among those listed in the all - time roster . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', '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', 'years'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; years }'}, 'player'], 'result': 'jake ford', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; years } ; player }'}, 'jake ford'], 'result': True, 'ind': 2, 'tos... | eq { hop { argmin { all_rows ; years } ; player } ; jake ford } = true | select the row whose years record of all rows is minimum . the player record of this row is jake ford . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'years_5': 5, 'player_6': 6, 'jake ford_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'years_5': 'years', 'player_6': 'player', 'jake ford_7': 'jake ford'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'years_5': [0], 'player_6': [1], 'jake ford_7': [2]} | ['player', 'nationality', 'jersey number ( s )', 'position', 'years', 'from'] | [['jim farmer', 'united states', '21', 'pg / sg', '1990', 'alabama'], ['noel felix', 'united states', '16', 'pf', '2006', 'fresno state'], ['al fleming', 'united states', '30', 'f', '1978', 'arizona'], ['alphonso ford', 'united states', '3', 'sg', '1994', 'mississippi valley state'], ['jake ford', 'united states', '33'... |
list of true jackson , vp episodes | https://en.wikipedia.org/wiki/List_of_True_Jackson%2C_VP_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20046379-3.html.csv | unique | the episode titled ' my boss ate my homework ' of true jackson , vp was the only episode written by diana sproveri . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'diana sproveri', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'diana sproveri'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to diana sproveri .', 'tostr': 'filter_eq { all_rows ; written by ; diana sproveri }'}], 'resul... | and { only { filter_eq { all_rows ; written by ; diana sproveri } } ; eq { hop { filter_eq { all_rows ; written by ; diana sproveri } ; title } ; my boss ate my homework } } = true | select the rows whose written by record fuzzily matches to diana sproveri . there is only one such row in the table . the title record of this unqiue row is my boss ate my homework . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'written by_7': 7, 'diana sproveri_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'my boss ate my homework_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'written by_7': 'written by', 'diana sproveri_8': 'diana sproveri', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'my boss ate my homework_10': 'my boss ate my homework'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'written by_7': [0], 'diana sproveri_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'my boss ate my homework_10': [3]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( millions )'] | [['27', '1', 'true concert', 'gary halvorson', 'dan kopelman', 'november 14 , 2009', '204', '3.8'], ['30', '4', 'true parade', 'gary halvorson', 'andy gordon', 'december 12 , 2009', '210', 'n / a'], ['31', '5', 'true drama', 'roger christiansen', 'steve joe', 'january 9 , 2010', '211', '3.3'], ['32', '6', 'my boss ate ... |
dancing with the stars ( u.s. season 1 ) | https://en.wikipedia.org/wiki/Dancing_with_the_Stars_%28U.S._season_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10535354-10.html.csv | aggregation | the total score of the couple who placed safe in season 1 of dancing with the stars totaled a score of 54 . | {'scope': 'subset', 'col': '2', 'type': 'sum', 'result': '54', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'safe'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'safe'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; safe }', 'tointer': 'select the rows whose result record fuzzily matches to safe .'}, 'score'], 'result': '54', 'ind': 1, 'tostr': ... | round_eq { sum { filter_eq { all_rows ; result ; safe } ; score } ; 54 } = true | select the rows whose result record fuzzily matches to safe . the sum of the score record of these rows is 54 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'safe_6': 6, 'score_7': 7, '54_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'safe_6': 'safe', 'score_7': 'score', '54_8': '54'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'safe_6': [0], 'score_7': [1], '54_8': [2]} | ['couple', 'score', 'dance', 'music', 'result'] | [['john & charlotte', '27 ( 9 , 9 , 9 )', 'foxtrot', 'let there be love - nat king cole', 'safe'], ['john & charlotte', '27 ( 9 , 9 , 9 )', 'paso doble', 'españa cañí - mexicana aleque la - band', 'safe'], ['kelly & alec', '22 ( 8 , 7 , 7 )', 'foxtrot', "do n't know why - norah jones", 'bottom 2'], ['kelly & alec', '25... |
2008 - 09 denver nuggets season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Denver_Nuggets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17355408-5.html.csv | ordinal | the denver nuggets ' games against dallas recorded their 2nd highest attendance of the 2008 - 09 season . | {'row': '6', 'col': '8', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'location attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location attendance ; 2 }'}, 'team'], 'result': 'dallas', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendance ; ... | eq { hop { nth_argmax { all_rows ; location attendance ; 2 } ; team } ; dallas } = true | select the row whose location attendance record of all rows is 2nd maximum . the team record of this row is dallas . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, '2_6': 6, 'team_7': 7, 'dallas_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', '2_6': '2', 'team_7': 'team', 'dallas_8': 'dallas'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], '2_6': [0], 'team_7': [1], 'dallas_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['19', 'december 2', 'toronto', 'w 132 - 93 ( ot )', 'chauncey billups ( 24 )', 'nenê ( 11 )', 'chauncey billups ( 14 )', 'pepsi center 14243', '13 - 6'], ['20', 'december 4', 'san antonio', 'l 91 - 108 ( ot )', 'carmelo anthony ( 16 )', 'j r smith ( 10 )', 'j r smith , chauncey billups ( 4 )', 'pepsi center 15866', '... |
euroleague 2007 - 08 individual statistics | https://en.wikipedia.org/wiki/Euroleague_2007%E2%80%9308_Individual_Statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16050349-4.html.csv | comparative | among the top scoring players in euroleague 2007 - 08 , jeremiah massey scored more points than kenan bajramović . | {'row_1': '2', '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', 'name', 'jeremiah massey'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to jeremiah massey .', 'tostr': 'filter_eq { all_rows ; name ; jeremiah massey }'}, 'points'], 'res... | greater { hop { filter_eq { all_rows ; name ; jeremiah massey } ; points } ; hop { filter_eq { all_rows ; name ; kenan bajramović } ; points } } = true | select the rows whose name record fuzzily matches to jeremiah massey . take the points record of this row . select the rows whose name record fuzzily matches to kenan bajramović . take the points record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'jeremiah massey_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'kenan bajramović_12': 12, 'points_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'jeremiah massey_8': 'jeremiah massey', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'ke... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'jeremiah massey_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'kenan bajramović_12': [1], 'points_13': [3]} | ['rank', 'name', 'team', 'games', 'points'] | [['1', 'will solomon', 'fenerbahçe', '6', '123'], ['2', 'jeremiah massey', 'aris thessaloniki', '6', '120'], ['3', 'lynn greer', 'olympiacos', '6', '113'], ['4', 'hollis price', 'lietuvos rytas vilnius', '6', '101'], ['4', 'kenan bajramović', 'lietuvos rytas vilnius', '6', '101']] |
1972 denver broncos season | https://en.wikipedia.org/wiki/1972_Denver_Broncos_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17848578-1.html.csv | count | in the 1972 season the denver broncos played at mile high stadium 7 times . | {'scope': 'all', 'criterion': 'equal', 'value': 'mile high stadium', 'result': '7', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'mile high stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game site record fuzzily matches to mile high stadium .', 'tostr': 'filter_eq { all_rows ; game site ; mile high stadium }'}], ... | eq { count { filter_eq { all_rows ; game site ; mile high stadium } } ; 7 } = true | select the rows whose game site record fuzzily matches to mile high stadium . 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, 'game site_5': 5, 'mile high stadium_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', 'game site_5': 'game site', 'mile high stadium_6': 'mile high stadium', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'game site_5': [0], 'mile high stadium_6': [0], '7_7': [2]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 17', 'houston oilers', 'w 30 - 17', 'mile high stadium', '1 - 0', '51656'], ['2', 'september 24', 'san diego chargers', 'l 14 - 37', 'san diego stadium', '1 - 1', '49048'], ['3', 'october 1', 'kansas city chiefs', 'l 24 - 45', 'mile high stadium', '1 - 2', '51656'], ['4', 'october 8', 'cincinnati beng... |
philippe étancelin | https://en.wikipedia.org/wiki/Philippe_%C3%89tancelin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235932-2.html.csv | majority | the most chassis used by philippe étancelin was talbot - lago t26c da . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'talbot-lago t26c da', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'chassis', 'talbot-lago t26c da'], 'result': True, 'ind': 0, 'tointer': 'for the chassis records of all rows , most of them fuzzily match to talbot-lago t26c da .', 'tostr': 'most_eq { all_rows ; chassis ; talbot-lago t26c da } = true'} | most_eq { all_rows ; chassis ; talbot-lago t26c da } = true | for the chassis records of all rows , most of them fuzzily match to talbot-lago t26c da . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'chassis_3': 3, 'talbot-lago t26c da_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'chassis_3': 'chassis', 'talbot-lago t26c da_4': 'talbot-lago t26c da'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'chassis_3': [0], 'talbot-lago t26c da_4': [0]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1950', 'philippe étancelin', 'talbot - lago t26c', 'talbot straight - 6', '3'], ['1950', 'automobiles talbot - darracq', 'talbot - lago t26c da', 'talbot straight - 6', '3'], ['1950', 'philippe étancelin', 'talbot - lago t26c da', 'talbot straight - 6', '3'], ['1951', 'philippe étancelin', 'talbot - lago t26c da', '... |
fifa puskás award | https://en.wikipedia.org/wiki/FIFA_Pusk%C3%A1s_Award | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24765815-2.html.csv | majority | in the fifa puskás award voting shown the majority of players were unranked . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'unranked', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'rank', 'unranked'], 'result': True, 'ind': 0, 'tointer': 'for the rank records of all rows , most of them fuzzily match to unranked .', 'tostr': 'most_eq { all_rows ; rank ; unranked } = true'} | most_eq { all_rows ; rank ; unranked } = true | for the rank records of all rows , most of them fuzzily match to unranked . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'rank_3': 3, 'unranked_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'rank_3': 'rank', 'unranked_4': 'unranked'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'rank_3': [0], 'unranked_4': [0]} | ['rank', 'player', 'nationality', 'team', 'opponent', 'score', 'competition', 'vote percentage'] | [['1st', 'hamit altıntop', 'turkey', 'turkey', 'kazakhstan', '0 - 2', 'uefa euro 2012 qualifying group a', '40.55 %'], ['2nd', 'linus hallenius', 'sweden', 'hammarby if', 'syrianska fc', '2 - 0', '2010 superettan', '13.23 %'], ['3rd', 'matty burrows', 'northern ireland', 'glentoran', 'portadown', '1 - 0', '2010 - 11 if... |
hegang | https://en.wikipedia.org/wiki/Hegang | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1834138-2.html.csv | superlative | luobei county has the biggest population among districts and counties in hegang . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '8', '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', 'population'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; population }'}, 'english name'], 'result': 'luobei county', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; population } ; english name }'}, 'luobei count... | eq { hop { argmax { all_rows ; population } ; english name } ; luobei county } = true | select the row whose population record of all rows is maximum . the english name record of this row is luobei county . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'population_5': 5, 'english name_6': 6, 'luobei county_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'population_5': 'population', 'english name_6': 'english name', 'luobei county_7': 'luobei county'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'population_5': [0], 'english name_6': [1], 'luobei county_7': [2]} | ['english name', 'simplified', 'traditional', 'pinyin', 'area', 'population', 'density'] | [['english name', 'simplified', 'traditional', 'pinyin', 'area', 'population', 'density'], ['xingshan district', '兴山区', '興山區', 'xīngshān qū', '27', '44803', '1659'], ['xiangyang district', '向阳区', '向陽區', 'xiàngyáng qū', '9', '110916', '12324'], ['gongnong district', '工农区', '工農區', 'gōngnóng qū', '11', '140070', '12734'],... |
golf magazine | https://en.wikipedia.org/wiki/Golf_Magazine | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11063491-1.html.csv | count | alister mackenzie designed or co-designed two of the courses . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'alister mackenzie', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'designer , year', 'alister mackenzie'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose designer , year record fuzzily matches to alister mackenzie .', 'tostr': 'filter_eq { all_rows ; designer , year ; aliste... | eq { count { filter_eq { all_rows ; designer , year ; alister mackenzie } } ; 2 } = true | select the rows whose designer , year record fuzzily matches to alister mackenzie . 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, 'designer , year_5': 5, 'alister mackenzie_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', 'designer , year_5': 'designer , year', 'alister mackenzie_6': 'alister mackenzie', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'designer , year_5': [0], 'alister mackenzie_6': [0], '2_7': [2]} | ['rank', 'name', 'location', 'state', 'designer , year'] | [['1', 'pine valley', 'pine valley', 'new jersey', 'george crump / harry colt , 1918'], ['2', 'cypress point', 'pebble beach', 'california', 'alister mackenzie , 1918'], ['3', 'augusta national', 'augusta', 'georgia', 'alister mackenzie / bobby jones , 1933'], ['4', 'pebble beach', 'pebble beach', 'california', 'jack n... |
fibt world championships 2008 | https://en.wikipedia.org/wiki/FIBT_World_Championships_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13566976-7.html.csv | comparative | canada won more silver medals than the us in the 2008 fibt world championships . | {'row_1': '2', 'row_2': '3', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; nation ; canada }'}, 'silver'], 'result': None, 'ind': 2,... | greater { hop { filter_eq { all_rows ; nation ; canada } ; silver } ; hop { filter_eq { all_rows ; nation ; united states } ; silver } } = true | select the rows whose nation record fuzzily matches to canada . take the silver record of this row . select the rows whose nation record fuzzily matches to united states . take the silver record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nation_7': 7, 'canada_8': 8, 'silver_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'nation_11': 11, 'united states_12': 12, 'silver_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nation_7': 'nation', 'canada_8': 'canada', 'silver_9': 'silver', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nation_11': 'nation', 'united state... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'nation_7': [0], 'canada_8': [0], 'silver_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'nation_11': [1], 'united states_12': [1], 'silver_13': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'germany', '5', '2', '4', '11'], ['2', 'canada', '0', '2', '0', '2'], ['3', 'united states', '0', '1', '1', '2'], ['4', 'russia', '0', '1', '1', '2'], ['5', 'united kingdom', '1', '0', '0', '1']] |
2001 denver broncos season | https://en.wikipedia.org/wiki/2001_Denver_Broncos_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16729083-1.html.csv | unique | the denver broncos 's week 1 game was the only one which they played against the new york giants during the 2001 season . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'new york giants', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'new york giants'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to new york giants .', 'tostr': 'filter_eq { all_rows ; opponent ; new york giants }'}], 'result':... | and { only { filter_eq { all_rows ; opponent ; new york giants } } ; eq { hop { filter_eq { all_rows ; opponent ; new york giants } ; week } ; 1 } } = true | select the rows whose opponent record fuzzily matches to new york giants . there is only one such row in the table . the week record of this unqiue row is 1 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'new york giants_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'week_9': 9, '1_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'new york giants_8': 'new york giants', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'week_9': 'week', '1_10': '1'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'opponent_7': [0], 'new york giants_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'week_9': [2], '1_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 10 , 2001', 'new york giants', 'w 31 - 20', '75735'], ['2', 'september 23 , 2001', 'arizona cardinals', 'w 38 - 17', '50913'], ['3', 'september 30 , 2001', 'baltimore ravens', 'l 20 - 13', '75082'], ['4', 'october 7 , 2001', 'kansas city chiefs', 'w 20 - 6', '75037'], ['5', 'october 14 , 2001', 'seatt... |
wru division one east | https://en.wikipedia.org/wiki/WRU_Division_One_East | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12784856-3.html.csv | comparative | in the wru division one east tredegar rfc has lost more games than newbridge rfc . | {'row_1': '12', 'row_2': '6', 'col': '4', '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', 'club', 'tredegar rfc'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to tredegar rfc .', 'tostr': 'filter_eq { all_rows ; club ; tredegar rfc }'}, 'lost'], 'result': None,... | greater { hop { filter_eq { all_rows ; club ; tredegar rfc } ; lost } ; hop { filter_eq { all_rows ; club ; newbridge rfc } ; lost } } = true | select the rows whose club record fuzzily matches to tredegar rfc . take the lost record of this row . select the rows whose club record fuzzily matches to newbridge rfc . take the lost record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'club_7': 7, 'tredegar rfc_8': 8, 'lost_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'club_11': 11, 'newbridge rfc_12': 12, 'lost_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'club_7': 'club', 'tredegar rfc_8': 'tredegar rfc', 'lost_9': 'lost', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'club_11': 'club', 'newbridge rf... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'club_7': [0], 'tredegar rfc_8': [0], 'lost_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'club_11': [1], 'newbridge rfc_12': [1], 'lost_13': [3]} | ['club', 'played', 'drawn', 'lost', 'try bp', 'losing bp'] | [['club', 'played', 'drawn', 'lost', 'try bp', 'losing bp'], ['uwic rfc', '22', '0', '3', '10', '2'], ['llanharan rfc', '22', '0', '5', '13', '3'], ['blackwood rfc', '22', '0', '6', '9', '4'], ['bargoed rfc', '22', '0', '6', '10', '2'], ['newbridge rfc', '22', '0', '9', '7', '2'], ['rumney rfc', '22', '0', '12', '5', '... |
calgary united f.c | https://en.wikipedia.org/wiki/Calgary_United_F.C. | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12042534-3.html.csv | aggregation | fifty two total games were played by calgary united . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '52', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'games played'], 'result': '52', 'ind': 0, 'tostr': 'sum { all_rows ; games played }'}, '52'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; games played } ; 52 } = true', 'tointer': 'the sum of the games played record of all rows is 5... | round_eq { sum { all_rows ; games played } ; 52 } = true | the sum of the games played record of all rows is 52 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'games played_4': 4, '52_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'games played_4': 'games played', '52_5': '52'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'games played_4': [0], '52_5': [1]} | ['team', 'games played', 'wins', 'losses', 'winning percentage', 'points for', 'points against', 'point differential'] | [['2007', '4', '2', '2', '500', '9', '6', '+ 3'], ['2008', '10', '8', '2', '800', '72', '38', '+ 34'], ['2009', '16', '8', '8', '500', '109', '84', '+ 21'], ['2010', '10', '8', '2', '800', '79', '32', '+ 47'], ['2011', '12', '8', '4', '667', '68', '52', '+ 16']] |
umberto maglioli | https://en.wikipedia.org/wiki/Umberto_Maglioli | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235883-1.html.csv | comparative | umberto maglioli scored more points in 1954 than he did in 1957 . | {'row_1': '3', 'row_2': '8', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1954'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1954 .', 'tostr': 'filter_eq { all_rows ; year ; 1954 }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'h... | greater { hop { filter_eq { all_rows ; year ; 1954 } ; points } ; hop { filter_eq { all_rows ; year ; 1957 } ; points } } = true | select the rows whose year record fuzzily matches to 1954 . take the points record of this row . select the rows whose year record fuzzily matches to 1957 . take the points record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '1954_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '1957_12': 12, 'points_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '1954_8': '1954', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '1957_12': '1957', 'point... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '1954_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '1957_12': [1], 'points_13': [3]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1953', 'scuderia ferrari', 'ferrari 553', 'ferrari straight - 4', '0'], ['1954', 'scuderia ferrari', 'ferrari 625', 'ferrari straight - 4', '2'], ['1954', 'scuderia ferrari', 'ferrari 553', 'ferrari straight - 4', '2'], ['1955', 'scuderia ferrari', 'ferrari 625', 'ferrari straight - 4', '1\xa01⁄3'], ['1955', 'scuder... |
list of how it 's made episodes | https://en.wikipedia.org/wiki/List_of_How_It%27s_Made_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15187735-20.html.csv | unique | episode 259 of how it 's made series 20 is the only one of that series with a two part segment . | {'scope': 'all', 'row': '12', 'col': '5', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'part', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment c', 'part'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment c record fuzzily matches to part .', 'tostr': 'filter_eq { all_rows ; segment c ; part }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; segment c ; part } } ; eq { hop { filter_eq { all_rows ; segment c ; part } ; episode } ; 259 } } = true | select the rows whose segment c record fuzzily matches to part . there is only one such row in the table . the episode record of this unqiue row is 259 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'segment c_7': 7, 'part_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'episode_9': 9, '259_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'segment c_7': 'segment c', 'part_8': 'part', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'episode_9': 'episode', '259_10': '259'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'segment c_7': [0], 'part_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'episode_9': [2], '259_10': [3]} | ['series ep', 'episode', 'segment a', 'segment b', 'segment c', 'segment d'] | [['20 - 01', '248', 'native healing drums', 's raisin', 'stereoscopic viewers', 'ribbon microphones'], ['20 - 02', '249', 'horse bits', 'oat cereal', 'turquoise jewellery', 'electric scooters'], ['20 - 03', '250', 'nail nippers', 'jade putters', 'ice cider', 'water skis'], ['20 - 04', '251', 'es stagecoach', 'road refl... |
2007 saskatchewan roughriders season | https://en.wikipedia.org/wiki/2007_Saskatchewan_Roughriders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16945617-4.html.csv | aggregation | the average crowd attendance for games in the 2007 saskatchewan roughriders season was 30349 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '30349', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '30349', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '30349'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 30349 } = true', 'tointer': 'the average of the attendance record of all rows... | round_eq { avg { all_rows ; attendance } ; 30349 } = true | the average of the attendance record of all rows is 30349 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '30349_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '30349_5': '30349'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '30349_5': [1]} | ['week', 'date', 'opponent', 'score', 'result', 'attendance', 'record'] | [['1', 'fri , june 29', 'montreal alouettes', '16 - 7', 'win', '20202', '1 - 0'], ['2', 'sun , july 8', 'calgary stampeders', '49 - 8', 'win', '25862', '2 - 0'], ['3', 'fri , july 13', 'bc lions', '42 - 12', 'loss', '26981', '2 - 1'], ['4', 'fri , july 20', 'edmonton eskimos', '21 - 20', 'loss', '46704', '2 - 2'], ['5'... |
1959 vfl season | https://en.wikipedia.org/wiki/1959_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10775038-15.html.csv | aggregation | in the 1959 vfl season , melbourne teams averaged 15,750 spectators at home games . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '15750', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': 'melbourne'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'melbourne'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; home team ; melbourne }', 'tointer': 'select the rows whose home team record fuzzily matches to melbourne .'}, 'crowd'], 'result': '... | round_eq { avg { filter_eq { all_rows ; home team ; melbourne } ; crowd } ; 15750 } = true | select the rows whose home team record fuzzily matches to melbourne . the average of the crowd record of these rows is 15750 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'home team_5': 5, 'melbourne_6': 6, 'crowd_7': 7, '15750_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'home team_5': 'home team', 'melbourne_6': 'melbourne', 'crowd_7': 'crowd', '15750_8': '15750'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'home team_5': [0], 'melbourne_6': [0], 'crowd_7': [1], '15750_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '12.8 ( 80 )', 'melbourne', '10.11 ( 71 )', 'western oval', '12549', '8 august 1959'], ['fitzroy', '11.15 ( 81 )', 'geelong', '6.11 ( 47 )', 'brunswick street oval', '14488', '8 august 1959'], ['collingwood', '12.18 ( 90 )', 'st kilda', '9.11 ( 65 )', 'victoria park', '29178', '8 august 1959'], ['south m... |
memphis grizzlies all - time roster | https://en.wikipedia.org/wiki/Memphis_Grizzlies_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16494599-3.html.csv | unique | of these players , only pete chilcutt had the position " power forward . " . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'power forward', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'power forward'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to power forward .', 'tostr': 'filter_eq { all_rows ; position ; power forward }'}], 'result': True,... | and { only { filter_eq { all_rows ; position ; power forward } } ; eq { hop { filter_eq { all_rows ; position ; power forward } ; player } ; pete chilcutt } } = true | select the rows whose position record fuzzily matches to power forward . there is only one such row in the table . the player record of this unqiue row is pete chilcutt . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'power forward_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'pete chilcutt_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'power forward_8': 'power forward', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'pete chilcutt_10': 'pete chilcutt'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'power forward_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'pete chilcutt_10': [3]} | ['player', 'nationality', 'position', 'years for grizzlies', 'school / club team'] | [['brian cardinal', 'united states', 'forward', '2004 - 2008', 'purdue'], ['rodney carney', 'united states', 'forward', '2011', 'memphis'], ['antoine carr', 'united states', 'forward / center', '1999 - 2000', 'wichita state'], ['demarre carroll', 'united states', 'forward', '2009 - 2012', 'missouri'], ['pete chilcutt',... |
2009 russian professional rugby league season | https://en.wikipedia.org/wiki/2009_Russian_Professional_Rugby_League_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27536877-1.html.csv | count | in the 2009 russan professional rugby league , 2 teams won exactly 9 games . | {'scope': 'all', 'criterion': 'equal', 'value': '9', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'won', '9'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose won record is equal to 9 .', 'tostr': 'filter_eq { all_rows ; won ; 9 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; won ; 9 } }... | eq { count { filter_eq { all_rows ; won ; 9 } } ; 2 } = true | select the rows whose won record is equal to 9 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'won_5': 5, '9_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'won_5': 'won', '9_6': '9', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'won_5': [0], '9_6': [0], '2_7': [2]} | ['', 'nation', 'played', 'won', 'drawn', 'lost', 'for', 'against', 'difference', 'table points'] | [['1', 'vva - podmoskovye monino', '10', '9', '0', '1', '399', '128', '271', '37'], ['2', 'yenisey - stm krasnoyarsk', '10', '9', '0', '1', '331', '140', '191', '37'], ['3', 'krasny yar krasnoyarsk', '10', '6', '0', '4', '247', '198', '49', '28'], ['4', 'slava moscow', '10', '3', '0', '7', '126', '267', '- 141', '19'],... |
2008 tim hortons brier | https://en.wikipedia.org/wiki/2008_Tim_Hortons_Brier | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15597975-2.html.csv | aggregation | the participants in the 2008 tim hortons brier curling tournament had a total combined ends won of 516 . | {'scope': 'all', 'col': '7', 'type': 'sum', 'result': '516', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'ends won'], 'result': '516', 'ind': 0, 'tostr': 'sum { all_rows ; ends won }'}, '516'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; ends won } ; 516 } = true', 'tointer': 'the sum of the ends won record of all rows is 516 .'} | round_eq { sum { all_rows ; ends won } ; 516 } = true | the sum of the ends won record of all rows is 516 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'ends won_4': 4, '516_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'ends won_4': 'ends won', '516_5': '516'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'ends won_4': [0], '516_5': [1]} | ['locale', 'skip', 'w', 'l', 'pf', 'pa', 'ends won', 'ends lost', 'blank ends', 'stolen ends', 'shot pct'] | [['alberta', 'kevin martin', '11', '0', '86', '52', '50', '40', '11', '11', '89'], ['saskatchewan', 'pat simmons', '9', '2', '80', '58', '50', '45', '9', '12', '84'], ['ontario', 'glenn howard', '9', '2', '85', '50', '54', '33', '11', '22', '88'], ['british columbia', 'bob ursel', '7', '4', '72', '66', '45', '47', '15'... |
2008 manx grand prix | https://en.wikipedia.org/wiki/2008_Manx_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18649514-4.html.csv | comparative | wattie brown finished with a better time than chris swallow in the 2008 manx grand prix . | {'row_1': '4', 'row_2': '8', 'col': '5', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rider', 'wattie brown'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rider record fuzzily matches to wattie brown .', 'tostr': 'filter_eq { all_rows ; rider ; wattie brown }'}, 'time'], 'result': None,... | less { hop { filter_eq { all_rows ; rider ; wattie brown } ; time } ; hop { filter_eq { all_rows ; rider ; chris swallow } ; time } } = true | select the rows whose rider record fuzzily matches to wattie brown . take the time record of this row . select the rows whose rider record fuzzily matches to chris swallow . take the time record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'rider_7': 7, 'wattie brown_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'rider_11': 11, 'chris swallow_12': 12, 'time_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'rider_7': 'rider', 'wattie brown_8': 'wattie brown', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'rider_11': 'rider', 'chris swallow_... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'rider_7': [0], 'wattie brown_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'rider_11': [1], 'chris swallow_12': [1], 'time_13': [3]} | ['rank', 'rider', 'team', 'speed', 'time'] | [['1', 'ryan farquhar', '498cc bic paton', '102.385 mph', '1:06.19.90'], ['2', 'alan oversby', '500cc norton manx', '101.863 mph', '1:06.40.30'], ['3', 'alan brew', 'seeley g50 496cc', '99.367 mph', '1:08.20.78'], ['4', 'wattie brown', '500cc petty manx', '98.118 mph', '1:09.12.98'], ['5', 'andy reynolds', '499cc bic p... |
gulf coast athletic conference | https://en.wikipedia.org/wiki/Gulf_Coast_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10577579-2.html.csv | aggregation | the gulf course had a total 11100 enrollment between 1981 and 2011 . | {'scope': 'all', 'col': '7', 'type': 'sum', 'result': '11100', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'enrollment'], 'result': '11100', 'ind': 0, 'tostr': 'sum { all_rows ; enrollment }'}, '11100'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; enrollment } ; 11100 } = true', 'tointer': 'the sum of the enrollment record of all rows is ... | round_eq { sum { all_rows ; enrollment } ; 11100 } = true | the sum of the enrollment record of all rows is 11100 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '11100_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '11100_5': '11100'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '11100_5': [1]} | ['institution', 'location', "men 's nickname", "women 's nickname", 'founded', 'type', 'enrollment', 'joined'] | [['dillard university', 'new orleans , louisiana', 'bleu devils', 'lady bleu devils', '1869', 'private / ( methodist & church of christ )', '900', '1981'], ['edward waters college', 'jacksonville , florida', 'tigers', 'lady tigers', '1866', 'private / ( african methodist )', '800', '2010'], ['fisk university', 'nashvil... |
administrative divisions of lithuania | https://en.wikipedia.org/wiki/Administrative_divisions_of_Lithuania | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1784514-1.html.csv | aggregation | the average number of powiats for the administrative divisions of lithuania is 2.5 powiats . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '2.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'number of powiats'], 'result': '2.5', 'ind': 0, 'tostr': 'avg { all_rows ; number of powiats }'}, '2.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; number of powiats } ; 2.5 } = true', 'tointer': 'the average of the number of powi... | round_eq { avg { all_rows ; number of powiats } ; 2.5 } = true | the average of the number of powiats record of all rows is 2.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'number of powiats_4': 4, '2.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'number of powiats_4': 'number of powiats', '2.5_5': '2.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'number of powiats_4': [0], '2.5_5': [1]} | ['voivodeship after 1569', 'capital', 'year established', 'number of powiats', 'area ( km square ) in 1590 ( lithuanian ) category : articles with lithuanian - language external links'] | [['brest litovsk voivodeship', 'brest', '1566', '2 powiats', '40600'], ['minsk voivodeship', 'minsk', '1566', '3 powiats', '55500'], ['mstsislaw voivodeship', 'mstsislaw', '1566', '1 powiat', '22600'], ['nowogródek voivodeship', 'navahrudak', '1507', '3 powiats', '33200'], ['polotsk voivodeship', 'polotsk', '1504', '1 ... |
2004 cleveland browns season | https://en.wikipedia.org/wiki/2004_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10652530-2.html.csv | unique | during the 2004 season , the cleveland browns game in week 15 was the only one in which they failed to score any points . | {'scope': 'all', 'row': '15', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'result', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; result ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; re... | and { only { filter_eq { all_rows ; result ; 0 } } ; eq { hop { filter_eq { all_rows ; result ; 0 } ; week } ; 15 } } = true | select the rows whose result record is equal to 0 . there is only one such row in the table . the week record of this unqiue row is 15 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, '0_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'week_9': 9, '15_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', '0_8': '0', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'week_9': 'week', '15_10': '15'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], '0_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'week_9': [2], '15_10': [3]} | ['week', 'date', 'opponent', 'result', 'stadium', 'record', 'attendance'] | [['1', 'september 12 , 2004', 'baltimore ravens', 'w 20 - 3', 'cleveland browns stadium', '1 - 0', '73068'], ['2', 'september 19 , 2004', 'dallas cowboys', 'l 12 - 19', 'texas stadium', '1 - 1', '63119'], ['3', 'september 26 , 2004', 'new york giants', 'l 10 - 27', 'giants stadium', '1 - 2', '78521'], ['4', 'october 3 ... |
2008 - 09 golden state warriors season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Golden_State_Warriors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17080868-7.html.csv | majority | most of the players had high points of above 20 points in the golden state warriors of 2008-09 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '20', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'high points', '20'], 'result': True, 'ind': 0, 'tointer': 'for the high points records of all rows , most of them are greater than 20 .', 'tostr': 'most_greater { all_rows ; high points ; 20 } = true'} | most_greater { all_rows ; high points ; 20 } = true | for the high points records of all rows , most of them are greater than 20 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high points_3': 3, '20_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high points_3': 'high points', '20_4': '20'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'high points_3': [0], '20_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['35', 'january 2', 'minnesota', 'l 108 - 115 ( ot )', 'stephen jackson ( 25 )', 'andris biedriņš ( 13 )', 'stephen jackson ( 7 )', 'target center 11921', '10 - 25'], ['36', 'january 5', 'utah', 'l 114 - 119 ( ot )', 'jamal crawford ( 28 )', 'andris biedriņš ( 17 )', 'jamal crawford ( 6 )', 'energysolutions arena 1991... |
sidecarcross world championship | https://en.wikipedia.org/wiki/Sidecarcross_World_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16729457-16.html.csv | comparative | daniãl willemsen/sven verbrugge had more points than janis daiders/lauris daiders . | {'row_1': '1', 'row_2': '2', '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', 'driver / passenger', 'daniãl willemsen / sven verbrugge 1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose driver / passenger record fuzzily matches to daniãl willemsen / sven verbrugge 1 .', 'tostr':... | greater { hop { filter_eq { all_rows ; driver / passenger ; daniãl willemsen / sven verbrugge 1 } ; points } ; hop { filter_eq { all_rows ; driver / passenger ; janis daiders / lauris daiders } ; points } } = true | select the rows whose driver / passenger record fuzzily matches to daniãl willemsen / sven verbrugge 1 . take the points record of this row . select the rows whose driver / passenger record fuzzily matches to janis daiders / lauris daiders . take the points record of this row . the first record is greater than the seco... | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'driver / passenger_7': 7, 'daniãl willemsen / sven verbrugge 1_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'driver / passenger_11': 11, 'janis daiders / lauris daiders_12': 12, 'points_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'driver / passenger_7': 'driver / passenger', 'daniãl willemsen / sven verbrugge 1_8': 'daniãl willemsen / sven verbrugge 1', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1'... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'driver / passenger_7': [0], 'daniãl willemsen / sven verbrugge 1_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'driver / passenger_11': [1], 'janis daiders / lauris daiders_12': [1]... | ['position', 'driver / passenger', 'equipment', 'bike no', 'points'] | [['1', 'daniãl willemsen / sven verbrugge 1', 'zabel - wsp', '1', '487'], ['2', 'janis daiders / lauris daiders', 'zabel - vmc', '8', '478'], ['3', 'jan hendrickx / tim smeuninx', 'zabel - vmc', '3', '405'], ['4', 'maris rupeiks / kaspars stupelis 2', 'zabel - wsp', '5', '349'], ['5', 'etienne bax / ben van den bogaart... |
yugoslavia national football team results | https://en.wikipedia.org/wiki/Yugoslavia_national_football_team_results | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14305653-40.html.csv | count | the yugoslavia national football team played 5 friendly matches . | {'scope': 'all', 'criterion': 'equal', 'value': 'friendly', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type of game', 'friendly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose type of game record fuzzily matches to friendly .', 'tostr': 'filter_eq { all_rows ; type of game ; friendly }'}], 'result': '5', 'in... | eq { count { filter_eq { all_rows ; type of game ; friendly } } ; 5 } = true | select the rows whose type of game record fuzzily matches to friendly . 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, 'type of game_5': 5, 'friendly_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', 'type of game_5': 'type of game', 'friendly_6': 'friendly', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'type of game_5': [0], 'friendly_6': [0], '5_7': [2]} | ['date', 'city', 'opponent', 'results', 'type of game'] | [['may 16', 'belgrade', 'east germany', '3:1', 'friendly'], ['may 31', 'arica , chile', 'ussr', '0:2', 'wc round 1'], ['june 2', 'arica , chile', 'uruguay', '3:1', 'wc round 1'], ['june 7', 'arica , chile', 'colombia', '5:0', 'wc round 1'], ['june 10', 'santiago , chile', 'west germany', '1:0', 'wc round 2'], ['june 13... |
1979 buffalo bills season | https://en.wikipedia.org/wiki/1979_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17386076-3.html.csv | unique | the september 9th game against cincinnati was the only one in which the bills scored over 50 points . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '2,3', 'criterion': 'greater_than', 'value': '50', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'result', '50'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record is greater than 50 .', 'tostr': 'filter_greater { all_rows ; result ; 50 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_g... | and { only { filter_greater { all_rows ; result ; 50 } } ; and { eq { hop { filter_greater { all_rows ; result ; 50 } ; date } ; september 9 , 1979 } ; eq { hop { filter_greater { all_rows ; result ; 50 } ; opponent } ; cincinnati bengals } } } = true | select the rows whose result record is greater than 50 . there is only one such row in the table . the date record of this unqiue row is september 9 , 1979 . the opponent record of this unqiue row is cincinnati bengals . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_9': 9, 'result_10': 10, '50_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'date_12': 12, 'september 9 , 1979_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'opponent_14': 14, 'cincinnati bengals_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_9': 'all_rows', 'result_10': 'result', '50_11': '50', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_12': 'date', 'september 9 , 1979_13': 'september 9 , 1979', 'str_eq_5': 'str_eq', 'str_hop_4': ... | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_greater_0': [1, 2, 4], 'all_rows_9': [0], 'result_10': [0], '50_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'date_12': [2], 'september 9 , 1979_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'opponent_14': [4], 'cincinnati bengals_15': [5]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 2 , 1979', 'miami dolphins', 'l 9 - 7', '69441'], ['2', 'september 9 , 1979', 'cincinnati bengals', 'w 51 - 24', '43504'], ['3', 'september 16 , 1979', 'san diego chargers', 'l 27 - 19', '50709'], ['4', 'september 23 , 1979', 'new york jets', 'w 46 - 31', '68731'], ['5', 'september 30 , 1979', 'baltim... |
2006 kansas city brigade season | https://en.wikipedia.org/wiki/2006_Kansas_City_Brigade_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11974088-1.html.csv | majority | the majority of games in the 2006 kansas city brigade season ended in losses for the kansas city brigade . | {'scope': 'all', 'col': '5', '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', 'home / away game', 'result'] | [['1', 'january 29', 'dallas desperados', 'away', 'l 58 - 44'], ['2', 'february 3', 'orlando predators', 'away', 'l 48 - 41'], ['3', 'february 12', 'austin wranglers', 'home', 'l 37 - 33'], ['4', 'february 19', 'columbus destroyers', 'home', 'w 45 - 24'], ['5', 'february 24', 'georgia force', 'away', 'l 51 - 19'], ['6'... |
list of highest mountain peaks in washington | https://en.wikipedia.org/wiki/List_of_highest_mountain_peaks_in_Washington | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19716903-1.html.csv | ordinal | mount fernow has the 15th highest prominence of all the highest mountain peaks in washington . | {'row': '7', 'col': '5', 'order': '15', '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', 'prominence', '15'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; prominence ; 15 }'}, 'mountain peak'], 'result': 'mount fernow', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; prominence ; 15 } ; mou... | eq { hop { nth_argmax { all_rows ; prominence ; 15 } ; mountain peak } ; mount fernow } = true | select the row whose prominence record of all rows is 15th maximum . the mountain peak record of this row is mount fernow . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'prominence_5': 5, '15_6': 6, 'mountain peak_7': 7, 'mount fernow_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', 'prominence_5': 'prominence', '15_6': '15', 'mountain peak_7': 'mountain peak', 'mount fernow_8': 'mount fernow'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'prominence_5': [0], '15_6': [0], 'mountain peak_7': [1], 'mount fernow_8': [2]} | ['rank', 'mountain peak', 'mountain range', 'elevation', 'prominence', 'isolation'] | [['1', 'mount rainier', 'cascade range', '4393.293 = 14411feet 4392 m', '4027.439 = 13211feet 4027 m', '01175.46 = 730.4 miles 1175.5 km'], ['2', 'mount adams', 'cascade range', '3742.988 = 12277feet 3743 m', '2474.390 = 8116feet 2474 m', '00075.14 = 46.7 miles 75.1 km'], ['3', 'mount baker', 'cascade range', '3285.976... |
1928 army cadets football team | https://en.wikipedia.org/wiki/1928_Army_Cadets_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21091157-1.html.csv | superlative | the army cadets football team scored the most points in the game on october 13 . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '3', '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', 'black knights points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; black knights points }'}, 'date'], 'result': 'oct 13', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; black knights points } ; date }'}, 'oct 1... | eq { hop { argmax { all_rows ; black knights points } ; date } ; oct 13 } = true | select the row whose black knights points record of all rows is maximum . the date record of this row is oct 13 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'black knights points_5': 5, 'date_6': 6, 'oct 13_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'black knights points_5': 'black knights points', 'date_6': 'date', 'oct 13_7': 'oct 13'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'black knights points_5': [0], 'date_6': [1], 'oct 13_7': [2]} | ['game', 'date', 'opponent', 'result', 'black knights points', 'opponents', 'record'] | [['1', 'sept 29', 'boston university', 'win', '35', '0', '1 - 0'], ['2', 'oct 6', 'southern methodist', 'win', '14', '13', '2 - 0'], ['3', 'oct 13', 'providence college', 'win', '44', '0', '3 - 0'], ['4', 'oct 20', 'harvard', 'win', '15', '0', '4 - 0'], ['5', 'oct 27', 'yale', 'win', '18', '6', '5 - 0'], ['6', 'nov 3',... |
dominik meffert | https://en.wikipedia.org/wiki/Dominik_Meffert | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13141391-4.html.csv | unique | the kyoto tournament was the only one in which dominik meffert used a carpet ( i ) surface . | {'scope': 'all', 'row': '7', 'col': '2', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'carpet', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; tournament } ; kyoto } } = true | select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the tournament record of this unqiue row is kyoto . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'carpet_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'kyoto_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', 'carpet_8': 'carpet', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'kyoto_10': 'kyoto'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'carpet_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'kyoto_10': [3]} | ['tournament', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['freudenstadt', 'clay', 'tomas behrend', 'alexandre sidorenko mischa zverev', '7 - 5 , 7 - 6 5'], ['durban', 'hard', 'rik de voest', 'stéphane bohli noam okun', '6 - 4 , 6 - 2'], ['tanger', 'clay', 'steve darcis', 'uladzimir ignatik martin kližan', '5 - 7 , 7 - 5 ,'], ['pereira', 'clay', 'philipp oswald', 'gero krets... |
list of medal of honor recipients | https://en.wikipedia.org/wiki/List_of_Medal_of_Honor_recipients | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1202355-1.html.csv | count | for medal of honor recipients , when the service is the marine corps , there were 5 recipients that were privates . | {'scope': 'subset', 'criterion': 'equal', 'value': 'private', 'result': '5', 'col': '3', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'marine corps'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'service', 'marine corps'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; service ; marine corps }', 'tointer': 'select the rows whose service record fuzzily matches to marin... | eq { count { filter_eq { filter_eq { all_rows ; service ; marine corps } ; rank ; private } } ; 5 } = true | select the rows whose service record fuzzily matches to marine corps . among these rows , select the rows whose rank record fuzzily matches to private . the number of such rows is 5 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'service_6': 6, 'marine corps_7': 7, 'rank_8': 8, 'private_9': 9, '5_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'service_6': 'service', 'marine corps_7': 'marine corps', 'rank_8': 'rank', 'private_9': 'private', '5_10': '5'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'service_6': [0], 'marine corps_7': [0], 'rank_8': [1], 'private_9': [1], '5_10': [3]} | ['name', 'service', 'rank', 'place of action', 'unit'] | [['john andrews', 'navy', 'ordinary seaman', 'aboard the ussbenicia', 'ussbenicia'], ['charles brown', 'marine corps', 'corporal', 'aboard the usscolorado', 'usscolorado'], ['john coleman', 'marine corps', 'private', 'aboard the usscolorado', 'usscolorado'], ['james dougherty', 'marine corps', 'private', 'aboard the us... |
vitamin k deficiency | https://en.wikipedia.org/wiki/Vitamin_K_deficiency | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20592988-1.html.csv | majority | the majority of conditions leave prothrombin time unaffected by the condition . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'unaffected', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'prothrombin time', 'unaffected'], 'result': True, 'ind': 0, 'tointer': 'for the prothrombin time records of all rows , most of them fuzzily match to unaffected .', 'tostr': 'most_eq { all_rows ; prothrombin time ; unaffected } = true'} | most_eq { all_rows ; prothrombin time ; unaffected } = true | for the prothrombin time records of all rows , most of them fuzzily match to unaffected . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'prothrombin time_3': 3, 'unaffected_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'prothrombin time_3': 'prothrombin time', 'unaffected_4': 'unaffected'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'prothrombin time_3': [0], 'unaffected_4': [0]} | ['condition', 'prothrombin time', 'partial thromboplastin time', 'bleeding time', 'platelet count'] | [['vitamin k deficiency or warfarin', 'prolonged', 'normal or mildly prolonged', 'unaffected', 'unaffected'], ['disseminated intravascular coagulation', 'prolonged', 'prolonged', 'prolonged', 'decreased'], ['von willebrand disease', 'unaffected', 'prolonged or unaffected', 'prolonged', 'unaffected'], ['hemophilia', 'un... |
partnership ( cricket ) | https://en.wikipedia.org/wiki/Partnership_%28cricket%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1670921-1.html.csv | comparative | donald bradman and sid barnes scored more runs than pat symcox and mark boucher . | {'row_1': '5', 'row_2': '9', 'col': '2', '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', 'battling partners', 'donald bradman and sid barnes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose battling partners record fuzzily matches to donald bradman and sid barnes .', 'tostr': 'filter_eq { ... | greater { hop { filter_eq { all_rows ; battling partners ; donald bradman and sid barnes } ; runs } ; hop { filter_eq { all_rows ; battling partners ; pat symcox and mark boucher } ; runs } } = true | select the rows whose battling partners record fuzzily matches to donald bradman and sid barnes . take the runs record of this row . select the rows whose battling partners record fuzzily matches to pat symcox and mark boucher . take the runs 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, 'battling partners_7': 7, 'donald bradman and sid barnes_8': 8, 'runs_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'battling partners_11': 11, 'pat symcox and mark boucher_12': 12, 'runs_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', 'battling partners_7': 'battling partners', 'donald bradman and sid barnes_8': 'donald bradman and sid barnes', 'runs_9': 'runs', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq',... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'battling partners_7': [0], 'donald bradman and sid barnes_8': [0], 'runs_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'battling partners_11': [1], 'pat symcox and mark boucher_12': [1], 'runs_13': ... | ['wicket', 'runs', 'battling partners', 'battling team', 'fielding team', 'venue', 'season'] | [['1st', '415', 'gc smith and neil mckenzie', 'south africa', 'bangladesh', 'chittagong', '2008'], ['2nd', '576', 'roshan mahanama and sanath jayasuriya', 'sri lanka', 'india', 'colombo', '1997'], ['3rd', '624', 'mahela jayawardene and kumar sangakkara', 'sri lanka', 'south africa', 'colombo', '2006'], ['4th', '437', '... |
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/2-16729930-11.html.csv | majority | most of the intel atom microprocessors have a frequency of less than 2 ghz . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '2 ghz', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'frequency', '2 ghz'], 'result': True, 'ind': 0, 'tointer': 'for the frequency records of all rows , most of them are less than 2 ghz .', 'tostr': 'most_less { all_rows ; frequency ; 2 ghz } = true'} | most_less { all_rows ; frequency ; 2 ghz } = true | for the frequency records of all rows , most of them are less than 2 ghz . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'frequency_3': 3, '2 ghz_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'frequency_3': 'frequency', '2 ghz_4': '2 ghz'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'frequency_3': [0], '2 ghz_4': [0]} | ['model number', 'sspec number', 'frequency', 'l2 cache', 'mult', 'voltage', 'socket', 'release date', 'part number ( s )', 'release price ( usd )'] | [['atom z500', 'slb6q ( c0 )', '800 mhz', '512 kb', '8', '0.712 - 1.1 v', 'bga 441', 'april 2 , 2008', 'ac80566uc800de', '45'], ['atom z510', 'slb2c ( c0 )', '1.1 ghz', '512 kb', '11', '0.75 - 1.1 v', 'bga 441', 'april 2 , 2008', 'ac80566uc005de', '45'], ['atom z510p', 'slgpq ( c0 )', '1.1 ghz', '512 kb', '11', '0.8 - ... |
1988 - 89 segunda división | https://en.wikipedia.org/wiki/1988%E2%80%9389_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12107896-2.html.csv | count | 7 teams score 50 or more goals in the 1988 - 89 segunda división . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '50', 'result': '7', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'goals for', '50'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goals for record is greater than or equal to 50 .', 'tostr': 'filter_greater_eq { all_rows ; goals for ; 50 }'}], 'result': '7', 'ind': 1,... | eq { count { filter_greater_eq { all_rows ; goals for ; 50 } } ; 7 } = true | select the rows whose goals for record is greater than or equal to 50 . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'goals for_5': 5, '50_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'goals for_5': 'goals for', '50_6': '50', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'goals for_5': [0], '50_6': [0], '7_7': [2]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'cd castellón', '38', '51 + 13', '21', '9', '8', '49', '29', '+ 20'], ['2', 'rayo vallecano', '38', '49 + 11', '19', '11', '8', '61', '36', '+ 25'], ['3', 'cd tenerife', '38', '48 + 10', '20', '8', '10', '54', '36', '+ 18'], ['4', 'rcd mallorca', '38', '48 + 10', '21', '6', '11', '51', '26', '+ 25'], ['5', 'recr... |
sebastián gonzález | https://en.wikipedia.org/wiki/Sebasti%C3%A1n_Gonz%C3%A1lez | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1257826-1.html.csv | unique | only the july 14 , 2004 goal was scored in a non-friendly competition . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': '2004 copa américa', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '2004 copa américa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to 2004 copa américa .', 'tostr': 'filter_eq { all_rows ; competition ; 2004 copa américa ... | and { only { filter_eq { all_rows ; competition ; 2004 copa américa } } ; eq { hop { filter_eq { all_rows ; competition ; 2004 copa américa } ; date } ; 14 july 2004 } } = true | select the rows whose competition record fuzzily matches to 2004 copa américa . there is only one such row in the table . the date record of this unqiue row is 14 july 2004 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'competition_7': 7, '2004 copa américa_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '14 july 2004_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', '2004 copa américa_8': '2004 copa américa', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '14 july 2004_10': '14 july 2004'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'competition_7': [0], '2004 copa américa_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '14 july 2004_10': [3]} | ['goal', 'date', 'score', 'result', 'competition'] | [['1', '17 january 2001', '2 - 0', '2 - 0', 'friendly'], ['2', '20 january 2001', '1 - 0', '2 - 0', 'friendly'], ['3', '20 january 2001', '2 - 0', '2 - 0', 'friendly'], ['4', '15 march 2001', '3 - 1', '3 - 1', 'friendly'], ['5', '14 july 2004', '0 - 1', '1 - 1', '2004 copa américa'], ['6', '17 november 2004', '2 - 1', ... |
yen plus | https://en.wikipedia.org/wiki/Yen_Plus | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18685750-1.html.csv | majority | all of the titles serialized in yen plus have not been completed . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'no', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'completed', 'no'], 'result': True, 'ind': 0, 'tointer': 'for the completed records of all rows , all of them fuzzily match to no .', 'tostr': 'all_eq { all_rows ; completed ; no } = true'} | all_eq { all_rows ; completed ; no } = true | for the completed records of all rows , all of them fuzzily match to no . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'completed_3': 3, 'no_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'completed_3': 'completed', 'no_4': 'no'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'completed_3': [0], 'no_4': [0]} | ['title', 'author', 'first issue', 'last issue', 'completed'] | [['bamboo blade', 'masahiro totsuka ( author ) , aguri igarashi ( artist )', 'august 2008', 'may 2009', 'no'], ['black butler', 'yana toboso', 'august 2009', 'july 2010', 'no'], ['higurashi when they cry', 'ryukishi07 ( author ) , karin suzuragi ( artist )', 'august 2008', 'january 2009', 'no'], ['hero tales', 'huang j... |
2009 cfl draft | https://en.wikipedia.org/wiki/2009_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20170644-5.html.csv | count | in the 2009 cfl draft , 3 players at the rb position were drafted . | {'scope': 'all', 'criterion': 'equal', 'value': 'rb', 'result': '3', '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': '3', 'ind': 1, 'tostr': 'count { filte... | eq { count { filter_eq { all_rows ; position ; rb } } ; 3 } = true | select the rows whose position record fuzzily matches to rb . 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, 'position_5': 5, 'rb_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', 'position_5': 'position', 'rb_6': 'rb', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'rb_6': [0], '3_7': [2]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['33', 'hamilton tiger - cats', 'guillarme allard - cameus', 'rb', 'laval'], ['34', 'toronto argonauts', 'gordon sawler', 'dl', 'st francis xavier'], ['35', 'winnipeg blue bombers', 'peter quinney', 'fb', 'wilfrid laurier'], ['36', 'edmonton eskimos', 'eric lee', 'rb', 'weber state'], ['37', 'bc lions', 'jonathan pier... |
festivali i këngës 46 | https://en.wikipedia.org/wiki/Festivali_i_K%C3%ABng%C3%ABs_46 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11513819-1.html.csv | ordinal | juliana pasha was the artist that scored the third highest amount of points at the festivali i këngës 46 . | {'row': '13', 'col': '5', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'points', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points ; 3 }'}, 'artist'], 'result': 'juliana pasha', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points ; 3 } ; artist }'}, 'juliana pas... | eq { hop { nth_argmax { all_rows ; points ; 3 } ; artist } ; juliana pasha } = true | select the row whose points record of all rows is 3rd maximum . the artist record of this row is juliana pasha . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, '3_6': 6, 'artist_7': 7, 'juliana pasha_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', '3_6': '3', 'artist_7': 'artist', 'juliana pasha_8': 'juliana pasha'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], '3_6': [0], 'artist_7': [1], 'juliana pasha_8': [2]} | ['draw', 'artist', 'song', 'rank', 'points', 'a krajka', 'gj leka', 'b haxhia', 'd tukiqi', 'r magjistari', 'gj xhuvani', 'a skënderaj'] | [['1', 'manjola nallbani', 'kjo botë merr frymë nga dashuria', '7', '27', '3', '4', '4', '7', '8', '1', '0'], ['2', 'produkt 28', '30 sekonda', '15', '3', '0', '0', '0', '1', '1', '0', '1'], ['3', 'eneida tarifa', 'e para letër', '10', '11', '0', '1', '0', '0', '0', '7', '3'], ['4', 'mariza ikonomi', 'mall i tretur', '... |
grado labs | https://en.wikipedia.org/wiki/Grado_Labs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1601027-2.html.csv | aggregation | the average impedance for the grado labs headphones is around 33 ohms . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '33', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'impedance ( ohms )'], 'result': '33', 'ind': 0, 'tostr': 'avg { all_rows ; impedance ( ohms ) }'}, '33'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; impedance ( ohms ) } ; 33 } = true', 'tointer': 'the average of the impedance ( oh... | round_eq { avg { all_rows ; impedance ( ohms ) } ; 33 } = true | the average of the impedance ( ohms ) record of all rows is 33 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'impedance (ohms)_4': 4, '33_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'impedance (ohms)_4': 'impedance ( ohms )', '33_5': '33'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'impedance (ohms)_4': [0], '33_5': [1]} | ['headphone model', 'headphone class', 'sensitivity ( db )', 'impedance ( ohms )', 'driver - matched db', 'construction', 'earpads', 'termination', 'succeeded by'] | [['sr40', 'unknown', '100', '32', 'unknown', 'plastic', 'foam', '1 / 8 ( 3.5 mm ) plug with 1 / 4 adaptor', 'igrado'], ['sr325', 'prestige', '98', '32', '0.05', 'aluminum alloy', 'bowls', '1 / 4 ( 6.5 mm ) plug', 'sr325i'], ['hp1000', 'joseph grado signature', 'unknown', '40', 'unknown', 'aluminum alloy', 'flats', '1 /... |
2007 fedex cup playoffs | https://en.wikipedia.org/wiki/2007_FedEx_Cup_Playoffs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13282157-1.html.csv | aggregation | the average number of events these athletes competed in was approximately 19.8 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '19.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'events'], 'result': '19.8', 'ind': 0, 'tostr': 'avg { all_rows ; events }'}, '19.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; events } ; 19.8 } = true', 'tointer': 'the average of the events record of all rows is 19.8 .'} | round_eq { avg { all_rows ; events } ; 19.8 } = true | the average of the events record of all rows is 19.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'events_4': 4, '19.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'events_4': 'events', '19.8_5': '19.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'events_4': [0], '19.8_5': [1]} | ['', 'player', 'country', 'points', 'events', 'reset points'] | [['1', 'tiger woods', 'united states', '30574', '13', '100000'], ['2', 'vijay singh', 'fiji', '19129', '23', '99000'], ['3', 'jim furyk', 'united states', '16691', '19', '98500'], ['4', 'phil mickelson', 'united states', '16037', '18', '98000'], ['5', 'kj choi', 'south korea', '15485', '21', '97500'], ['6', 'rory sabba... |
great railway journeys | https://en.wikipedia.org/wiki/Great_Railway_Journeys | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15211468-5.html.csv | superlative | the earliest episode of great railway journeys to air was entitled the gold rush line . | {'scope': 'all', 'col_superlative': '3', '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', 'uk broadcast date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; uk broadcast date }'}, 'episode title'], 'result': 'the gold rush line', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; uk broadcast date } ; epis... | eq { hop { argmin { all_rows ; uk broadcast date } ; episode title } ; the gold rush line } = true | select the row whose uk broadcast date record of all rows is minimum . the episode title record of this row is the gold rush line . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'uk broadcast date_5': 5, 'episode title_6': 6, 'the gold rush line_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'uk broadcast date_5': 'uk broadcast date', 'episode title_6': 'episode title', 'the gold rush line_7': 'the gold rush line'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'uk broadcast date_5': [0], 'episode title_6': [1], 'the gold rush line_7': [2]} | ['episode no', 'episode title', 'uk broadcast date', 'narrator', 'writer', 'details of journey', 'countries visited'] | [['1', 'the gold rush line', '1983 - 02 - 15', 'simon hoggart', 'simon hoggart', 'white pass and yukon route', 'alaska , usa and yukon , canada'], ['2', 'the other poland', '1983 - 02 - 22', 'brian blessed', 'lyn webster', 'nasielsk to pułtusk & komańcza to cisna', 'poland'], ['3', 'slow train to olympia', '1983 - 03 -... |
h. f. stephens | https://en.wikipedia.org/wiki/H._F._Stephens | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1152298-2.html.csv | ordinal | the hecate model locomotive that was designed by h. f. stephens was the third earliest to be built . | {'row': '3', 'col': '3', 'order': '3', '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', 'build date', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; build date ; 3 }'}, 'loco name'], 'result': 'hecate', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; build date ; 3 } ; loco name }'}, '... | eq { hop { nth_argmin { all_rows ; build date ; 3 } ; loco name } ; hecate } = true | select the row whose build date record of all rows is 3rd minimum . the loco name record of this row is hecate . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'build date_5': 5, '3_6': 6, 'loco name_7': 7, 'hecate_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', 'build date_5': 'build date', '3_6': '3', 'loco name_7': 'loco name', 'hecate_8': 'hecate'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'build date_5': [0], '3_6': [0], 'loco name_7': [1], 'hecate_8': [2]} | ['railway', 'loco name', 'build date', 'wheels', 'disposal'] | [['kesr', 'tenterden', '1900', '2 - 4 - 0 t', 'scrapped 1941'], ['kesr', 'rolvenden', '1900', '2 - 4 - 0 t', 'scrapped 1941'], ['kesr', 'hecate', '1904', '0 - 8 - 0 t', 'to sr and br'], ['pdswjr', 'a s harris', '1907', '0 - 6 - 0 t', 'to sr and br'], ['pdswjr', 'earl of mount edgcumbe', '1907', '0 - 6 - 2 t', 'to sr an... |
list of indoor arenas in the philippines | https://en.wikipedia.org/wiki/List_of_indoor_arenas_in_the_Philippines | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12258195-2.html.csv | count | four of these arenas in the phillipines have an unknown seating capacity . | {'scope': 'all', 'criterion': 'equal', 'value': 'unknown', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'maximum seating capacity', 'unknown'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose maximum seating capacity record fuzzily matches to unknown .', 'tostr': 'filter_eq { all_rows ; maximum seating capacity ;... | eq { count { filter_eq { all_rows ; maximum seating capacity ; unknown } } ; 4 } = true | select the rows whose maximum seating capacity record fuzzily matches to unknown . 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, 'maximum seating capacity_5': 5, 'unknown_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', 'maximum seating capacity_5': 'maximum seating capacity', 'unknown_6': 'unknown', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'maximum seating capacity_5': [0], 'unknown_6': [0], '4_7': [2]} | ['arena / venue', 'home campus', 'location', 'province / region', 'maximum seating capacity', 'year opened'] | [['blue eagle gym', 'ateneo de manila university', 'quezon city', 'metro manila', '7500', '1949'], ['la salle coliseum', 'university of st la salle', 'bacolod city', 'negros occidental', '8000', '1998'], ['olivarez sports center', 'olivarez college', 'paraã ± aque city', 'metro manila', 'unknown', 'unknown'], ['quadric... |
united states house of representatives elections in georgia , 1998 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections_in_Georgia%2C_1998 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27021001-1.html.csv | comparative | john lewis was elected to his position before nathan deal was elected to his . | {'row_1': '5', 'row_2': '9', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'john lewis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to john lewis .', 'tostr': 'filter_eq { all_rows ; incumbent ; john lewis }'}, 'elected'], 'resul... | less { hop { filter_eq { all_rows ; incumbent ; john lewis } ; elected } ; hop { filter_eq { all_rows ; incumbent ; nathan deal } ; elected } } = true | select the rows whose incumbent record fuzzily matches to john lewis . take the elected record of this row . select the rows whose incumbent record fuzzily matches to nathan deal . take the elected record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'john lewis_8': 8, 'elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'nathan deal_12': 12, 'elected_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'john lewis_8': 'john lewis', 'elected_9': 'elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'john lewis_8': [0], 'elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'nathan deal_12': [1], 'elected_13': [3]} | ['district', 'incumbent', 'party', 'elected', 'status', 'result'] | [["georgia 's 1st", 'jack kingston', 'republican', '1992', 're - elected', 'jack kingston ( r ) unopposed'], ["georgia 's 2nd", 'sanford bishop', 'democratic', '1992', 're - elected', 'sanford bishop ( d ) 57 % joseph mccormick ( r ) 43 %'], ["georgia 's 3rd", 'mac collins', 'republican', '1992', 're - elected', 'mac c... |
list of townships in north dakota | https://en.wikipedia.org/wiki/List_of_townships_in_North_Dakota | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18600760-10.html.csv | comparative | james hill township has more square miles of water than jim river valley township . | {'row_1': '2', 'row_2': '6', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'township', 'james hill'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose township record fuzzily matches to james hill .', 'tostr': 'filter_eq { all_rows ; township ; james hill }'}, 'water ( sqmi )'],... | greater { hop { filter_eq { all_rows ; township ; james hill } ; water ( sqmi ) } ; hop { filter_eq { all_rows ; township ; jim river valley } ; water ( sqmi ) } } = true | select the rows whose township record fuzzily matches to james hill . take the water ( sqmi ) record of this row . select the rows whose township record fuzzily matches to jim river valley . take the water ( sqmi ) 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, 'township_7': 7, 'james hill_8': 8, 'water (sqmi)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'township_11': 11, 'jim river valley_12': 12, 'water (sqmi)_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', 'township_7': 'township', 'james hill_8': 'james hill', 'water (sqmi)_9': 'water ( sqmi )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'township_... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'township_7': [0], 'james hill_8': [0], 'water (sqmi)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'township_11': [1], 'jim river valley_12': [1], 'water (sqmi)_13': [3]} | ['township', 'county', 'pop ( 2010 )', 'land ( sqmi )', 'water ( sqmi )', 'latitude', 'longitude', 'geo id', 'ansi code'] | [['jackson', 'sargent', '33', '35.809', '0.000', '46.066276', '- 97.945530', '3808140460', '1036797'], ['james hill', 'mountrail', '32', '31.820', '4.243', '48.423125', '- 102.429934', '3806140500', '1037048'], ['james river valley', 'dickey', '40', '28.597', '0.000', '46.246641', '- 98.188329', '3802140540', '1036767'... |
looney tunes and merrie melodies filmography ( 1929 - 39 ) | https://en.wikipedia.org/wiki/Looney_Tunes_and_Merrie_Melodies_filmography_%281929%E2%80%9339%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18792938-2.html.csv | ordinal | the film titled ' red - headed baby ' had the third highest production number of the 1929-39 looney tunes and merrie melodies films . | {'row': '17', 'col': '4', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'production num', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; production num ; 3 }'}, 'title'], 'result': 'red - headed baby', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; production num ; 3 }... | eq { hop { nth_argmax { all_rows ; production num ; 3 } ; title } ; red - headed baby } = true | select the row whose production num record of all rows is 3rd maximum . the title record of this row is red - headed baby . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'production num_5': 5, '3_6': 6, 'title_7': 7, 'red - headed baby_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', 'production num_5': 'production num', '3_6': '3', 'title_7': 'title', 'red - headed baby_8': 'red - headed baby'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'production num_5': [0], '3_6': [0], 'title_7': [1], 'red - headed baby_8': [2]} | ['title', 'series', 'characters', 'production num', 'release date'] | [['big man from the north', 'lt', 'bosko , honey', '4500', '1931 - 01 - xx'], ["ai n't nature grand !", 'lt', 'bosko', '4626', '1931 - 03 - xx'], ["ups 'n downs", 'lt', 'bosko', '4640', '1931 - 03 - xx'], ['dumb patrol', 'lt', 'bosko , honey', '4664', '1931 - 05 - xx'], ['yodeling yokels', 'lt', 'bosko , honey', '4680'... |
2000 pga championship | https://en.wikipedia.org/wiki/2000_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18026889-4.html.csv | majority | most of the players at the 2000 pga championship to score 70 were from the united states . | {'scope': 'subset', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': {'col': '4', 'criterion': 'equal', 'value': '70'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'score', '70'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; score ; 70 }', 'tointer': 'select the rows whose score record is equal to 70 .'}, 'country', 'united states'], 'result': True, 'ind': 1, 'tointer': 'select the rows whos... | most_eq { filter_eq { all_rows ; score ; 70 } ; country ; united states } = true | select the rows whose score record is equal to 70 . for the country records of these rows , most of them fuzzily match to united states . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_eq_0': 0, 'all_rows_3': 3, 'score_4': 4, '70_5': 5, 'country_6': 6, 'united states_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_eq_0': 'filter_eq', 'all_rows_3': 'all_rows', 'score_4': 'score', '70_5': '70', 'country_6': 'country', 'united states_7': 'united states'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_eq_0': [1], 'all_rows_3': [0], 'score_4': [0], '70_5': [0], 'country_6': [1], 'united states_7': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'scott dunlap', 'united states', '66', '- 6'], ['t1', 'tiger woods', 'united states', '66', '- 6'], ['t3', 'darren clarke', 'northern ireland', '68', '- 4'], ['t3', 'davis love iii', 'united states', '68', '- 4'], ['t5', 'stephen ames', 'trinidad and tobago', '69', '- 3'], ['t5', 'ed fryatt', 'england', '69', '... |
simon shirley | https://en.wikipedia.org/wiki/Simon_Shirley | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15170292-1.html.csv | unique | the summer olympics was the only competition held in south korea . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'south korea', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'south korea'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to south korea .', 'tostr': 'filter_eq { all_rows ; venue ; south korea }'}], 'result': True, 'ind': 1, 'tos... | and { only { filter_eq { all_rows ; venue ; south korea } } ; eq { hop { filter_eq { all_rows ; venue ; south korea } ; tournament } ; summer olympics } } = true | select the rows whose venue record fuzzily matches to south korea . there is only one such row in the table . the tournament record of this unqiue row is summer olympics . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'south korea_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'summer olympics_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'south korea_8': 'south korea', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'summer olympics_10': 'summer olympics'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'south korea_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'summer olympics_10': [3]} | ['year', 'tournament', 'venue', 'result', 'event'] | [['1988', 'summer olympics', 'seoul , south korea', '15th', 'decathlon'], ['1994', 'hypo - meeting', 'götzis , austria', '11th', 'decathlon'], ['1994', 'commonwealth games', 'victoria , canada', '2nd', 'decathlon'], ['1995', 'hypo - meeting', 'götzis , austria', '20th', 'decathlon'], ['1996', 'hypo - meeting', 'götzis ... |
south asian canadian | https://en.wikipedia.org/wiki/South_Asian_Canadian | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1717824-1.html.csv | superlative | ontario had more south asians in 2011 than any other province in canada . | {'scope': 'all', 'col_superlative': '4', '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', 'south asians 2011'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; south asians 2011 }'}, 'province'], 'result': 'ontario', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; south asians 2011 } ; province }'}, 'ontar... | eq { hop { argmax { all_rows ; south asians 2011 } ; province } ; ontario } = true | select the row whose south asians 2011 record of all rows is maximum . the province record of this row is ontario . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'south asians 2011_5': 5, 'province_6': 6, 'ontario_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'south asians 2011_5': 'south asians 2011', 'province_6': 'province', 'ontario_7': 'ontario'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'south asians 2011_5': [0], 'province_6': [1], 'ontario_7': [2]} | ['province', 'south asians 2001', '% 2001', 'south asians 2011', '% 2011'] | [['ontario', '554870', '4.9 %', '1003180', '7.9 %'], ['british columbia', '210295', '5.4 %', '311265', '7.2 %'], ['alberta', '69580', '2.4 %', '159055', '4.4 %'], ['quebec', '59510', '0.8 %', '91400', '1.2 %'], ['manitoba', '12875', '1.2 %', '26220', '2.2 %'], ['saskatchewan', '4090', '0.4 %', '12620', '1.3 %'], ['nova... |
2005 - 06 liverpool f.c. season | https://en.wikipedia.org/wiki/2005%E2%80%9306_Liverpool_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19764939-1.html.csv | count | 2 players were ranked 6th in the 2005 - 06 liverpool f.c. season . | {'scope': 'all', 'criterion': 'equal', 'value': '6', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'rank', '6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rank record is equal to 6 .', 'tostr': 'filter_eq { all_rows ; rank ; 6 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; rank ; 6... | eq { count { filter_eq { all_rows ; rank ; 6 } } ; 2 } = true | select the rows whose rank record is equal to 6 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'rank_5': 5, '6_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'rank_5': 'rank', '6_6': '6', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'rank_5': [0], '6_6': [0], '2_7': [2]} | ['rank', 'no', 'pos', 'player', 'premier league', 'fa cup', 'league cup', 'champions league', 'club world cup', 'total'] | [['1', '8', 'mf', 'steven gerrard', '10', '4', '1', '7', '1', '23'], ['2', '9', 'fw', 'djibril cisse', '9', '2', '0', '6', '0', '19'], ['3', '15', 'fw', 'peter crouch', '8', '3', '0', '0', '2', '13'], ['4', '10', 'mf', 'luis garcã\xada', '7', '1', '0', '2', '0', '11'], ['5', '19', 'fw', 'fernando morientes', '5', '1', ... |
european poker tour | https://en.wikipedia.org/wiki/European_Poker_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1296513-4.html.csv | comparative | the barcelona open had a higher prize amount than the european poker championships . | {'row_1': '3', 'row_2': '2', 'col': '5', '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', 'event', 'ept baden classic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record fuzzily matches to ept baden classic .', 'tostr': 'filter_eq { all_rows ; event ; ept baden classic }'}, 'prize... | greater { hop { filter_eq { all_rows ; event ; ept baden classic } ; prize } ; hop { filter_eq { all_rows ; event ; the european poker championships } ; prize } } = true | select the rows whose event record fuzzily matches to ept baden classic . take the prize record of this row . select the rows whose event record fuzzily matches to the european poker championships . take the prize 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, 'event_7': 7, 'ept baden classic_8': 8, 'prize_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'event_11': 11, 'the european poker championships_12': 12, 'prize_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', 'event_7': 'event', 'ept baden classic_8': 'ept baden classic', 'prize_9': 'prize', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'event_11': 'event... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'event_7': [0], 'ept baden classic_8': [0], 'prize_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'event_11': [1], 'the european poker championships_12': [1], 'prize_13': [3]} | ['date', 'city', 'event', 'winner', 'prize'] | [['28 aug - 2 sep 2007', 'barcelona', 'barcelona open', 'sander lyloff', '1170700'], ['25 - 29 september 2007', 'london', 'the european poker championships', 'joseph mouawad', '611520'], ['7 - 10 october 2007', 'baden', 'ept baden classic', 'julian thew', '670800'], ['30 oct - 3 nov 2007', 'dublin', 'ept dublin', 'reub... |
hong kong first division league | https://en.wikipedia.org/wiki/Hong_Kong_First_Division_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1908877-2.html.csv | superlative | south china has the most top division titles by far , with 41 . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'top division titles'], 'result': '41', 'ind': 0, 'tostr': 'max { all_rows ; top division titles }', 'tointer': 'the maximum top division titles record of all rows is 41 .'}, '41'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_r... | and { eq { max { all_rows ; top division titles } ; 41 } ; eq { hop { argmax { all_rows ; top division titles } ; club } ; south china } } = true | the maximum top division titles record of all rows is 41 . the club record of the row with superlative top division titles record is south china . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'top division titles_8': 8, '41_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'top division titles_11': 11, 'club_12': 12, 'south china_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'top division titles_8': 'top division titles', '41_9': '41', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'top division titles_11': 'top division titles', 'club_12': 'club', 's... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'top division titles_8': [0], '41_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'top division titles_11': [2], 'club_12': [3], 'south china_13': [4]} | ['club', 'position in 2012 - 13', 'first season in top division', 'number of seasons in top division', 'first season of current spell in top division', 'top division titles', 'last top division title'] | [['biu chun rangers', '6th', '1965 - 66', '35', '2012 - 13', '1', '1970 - 71'], ['citizen', '8th', '2004 - 05', '9', '2004 - 05', '0', 'n / a'], ['eastern salon', '3rd , second division', '1936 - 37', '59', '2013 - 14', '4', '1994 - 95'], ['happy valley', '2nd , second division', '1959 - 60', '48', '2013 - 14', '6', '2... |
sriperumbudur ( lok sabha constituency ) | https://en.wikipedia.org/wiki/Sriperumbudur_%28Lok_Sabha_constituency%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18640543-1.html.csv | unique | in sriperumbudur , when the party affiliation is dravida munnetra kazhagam , the only time the mp was t r baalu , was from 2009-incumbent . | {'scope': 'subset', 'row': '12', 'col': '3', 'col_other': '2,4', 'criterion': 'equal', 'value': 't r baalu', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'dravida munnetra kazhagam'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party affiliation', 'dravida munnetra kazhagam'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; party affiliation ; dravida munnetra kazhagam }', 'tointer': 'select the rows... | and { only { filter_eq { filter_eq { all_rows ; party affiliation ; dravida munnetra kazhagam } ; name of mp ; t r baalu } } ; eq { hop { filter_eq { filter_eq { all_rows ; party affiliation ; dravida munnetra kazhagam } ; name of mp ; t r baalu } ; duration } ; 2009 - incumbent } } = true | select the rows whose party affiliation record fuzzily matches to dravida munnetra kazhagam . among these rows , select the rows whose name of mp record fuzzily matches to t r baalu . there is only one such row in the table . the duration record of this unqiue row is 2009 - incumbent . | 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, 'party affiliation_8': 8, 'dravida munnetra kazhagam_9': 9, 'name of mp_10': 10, 't r baalu_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'duration_12': 12, '2009 - incumbent_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', 'party affiliation_8': 'party affiliation', 'dravida munnetra kazhagam_9': 'dravida munnetra kazhagam', 'name of mp_10': 'name of mp', 't r baalu_11': 't r baalu', 'st... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'party affiliation_8': [0], 'dravida munnetra kazhagam_9': [0], 'name of mp_10': [1], 't r baalu_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'duration_12': [3], '2009 - incumbent_13': [4]} | ['lok sabha', 'duration', 'name of mp', 'party affiliation', 'election year'] | [['fourth', '1967 - 71', 'p sivasankaran', 'dravida munnetra kazhagam', '1967'], ['fifth', '1971 - 77', 'ts lakshmanan', 'dravida munnetra kazhagam', '1971'], ['sixth', '1977 - 80', 'seeralan jaganathan', 'all india anna dravida munnetra kazhagam', '1977'], ['seventh', '1980 - 84', 't nagaratnam', 'dravida munnetra kaz... |
1970 cfl draft | https://en.wikipedia.org/wiki/1970_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26996293-2.html.csv | ordinal | burns mcpherson was the second-highest pick in the second round of the 1970 cfl draft . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'pick', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; pick ; 2 }'}, 'player'], 'result': 'burns mcpherson', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; pick ; 2 } ; player }'}, 'burns mcpherson... | eq { hop { nth_argmin { all_rows ; pick ; 2 } ; player } ; burns mcpherson } = true | select the row whose pick record of all rows is 2nd minimum . the player record of this row is burns mcpherson . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'pick_5': 5, '2_6': 6, 'player_7': 7, 'burns mcpherson_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', 'pick_5': 'pick', '2_6': '2', 'player_7': 'player', 'burns mcpherson_8': 'burns mcpherson'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'pick_5': [0], '2_6': [0], 'player_7': [1], 'burns mcpherson_8': [2]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['10', 'winnipeg ( 2 )', 'john senst', 'fl', 'simon fraser'], ['11', 'montreal ( 1 )', 'burns mcpherson', 'hb', 'st francis xavier'], ['12', 'edmonton ( 2 )', 'jim henshall', 'hb', 'western'], ['13', 'bc lions ( 2 )', "tony d'aloisio", 'fb', 'windsor'], ['14', 'winnipeg ( 3 ) via hamilton', 'rick sugden', 'hb', 'simon... |
2005 houston astros season | https://en.wikipedia.org/wiki/2005_Houston_Astros_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13710464-1.html.csv | count | chris young was the winning pitcher twice when texas won against houston in the 2005 lone star series . | {'scope': 'subset', 'criterion': 'equal', 'value': 'chris young', 'result': '2', 'col': '4', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'texas'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winning team', 'texas'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; winning team ; texas }', 'tointer': 'select the rows whose winning team record fuzzily matches to texa... | eq { count { filter_eq { filter_eq { all_rows ; winning team ; texas } ; winning pitcher ; chris young } } ; 2 } = true | select the rows whose winning team record fuzzily matches to texas . among these rows , select the rows whose winning pitcher record fuzzily matches to chris young . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'winning team_6': 6, 'texas_7': 7, 'winning pitcher_8': 8, 'chris young_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'winning team_6': 'winning team', 'texas_7': 'texas', 'winning pitcher_8': 'winning pitcher', 'chris young_9': 'chris young', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'winning team_6': [0], 'texas_7': [0], 'winning pitcher_8': [1], 'chris young_9': [1], '2_10': [3]} | ['date', 'winning team', 'score', 'winning pitcher', 'losing pitcher', 'attendance', 'location'] | [['may 20', 'texas', '7 - 3', 'kenny rogers', 'brandon backe', '38109', 'arlington'], ['may 21', 'texas', '18 - 3', 'chris young', 'ezequiel astacio', '35781', 'arlington'], ['may 22', 'texas', '2 - 0', 'chan ho park', 'roy oswalt', '40583', 'arlington'], ['june 24', 'houston', '5 - 2', 'roy oswalt', 'ricardo rodriguez... |
sexuality of adolf hitler | https://en.wikipedia.org/wiki/Sexuality_of_Adolf_Hitler | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13941408-1.html.csv | unique | eva braun was the only wife of adolf hitler . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'wife', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'relationship', 'wife'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose relationship record fuzzily matches to wife .', 'tostr': 'filter_eq { all_rows ; relationship ; wife }'}], 'result': True, 'ind': 1, 'tos... | and { only { filter_eq { all_rows ; relationship ; wife } } ; eq { hop { filter_eq { all_rows ; relationship ; wife } ; name } ; eva braun } } = true | select the rows whose relationship record fuzzily matches to wife . there is only one such row in the table . the name record of this unqiue row is eva braun . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'relationship_7': 7, 'wife_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'eva braun_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'relationship_7': 'relationship', 'wife_8': 'wife', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'eva braun_10': 'eva braun'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'relationship_7': [0], 'wife_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'eva braun_10': [3]} | ['name', 'life', 'age at death', 'first contact with hitler', 'relationship'] | [['stefanie rabatsch', 'unknown', 'unknown', 'c 1905', 'teenage love interest'], ['charlotte lobjoie', '1898 - 1951', '53', 'allegedly met in 1917', 'poorly substantiated claim that she bore his child'], ['eva braun', 'february 6 , 1912 - april 30 , 1945', '33', 'met in autumn 1929', 'wife'], ['geli raubal', 'june 4 , ... |
indiana high school athletics conferences : allen county - metropolitan | https://en.wikipedia.org/wiki/Indiana_High_School_Athletics_Conferences%3A_Allen_County_%E2%80%93_Metropolitan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13986492-1.html.csv | majority | all of the schools in allen county , in indiana high school athletics conferences , have an enrollment that is under 1000 . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'less_than', 'value': '1000', 'subset': None} | {'func': 'all_less', 'args': ['all_rows', 'enrollment ( 2010 )', '1000'], 'result': True, 'ind': 0, 'tointer': 'for the enrollment ( 2010 ) records of all rows , all of them are less than 1000 .', 'tostr': 'all_less { all_rows ; enrollment ( 2010 ) ; 1000 } = true'} | all_less { all_rows ; enrollment ( 2010 ) ; 1000 } = true | for the enrollment ( 2010 ) records of all rows , all of them are less than 1000 . | 1 | 1 | {'all_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'enrollment (2010)_3': 3, '1000_4': 4} | {'all_less_0': 'all_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'enrollment (2010)_3': 'enrollment ( 2010 )', '1000_4': '1000'} | {'all_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'enrollment (2010)_3': [0], '1000_4': [0]} | ['school', 'location', 'mascot', 'enrollment ( 2010 )', 'ihsaa class', 'ihsaa football class', 'county'] | [['adams central', 'monroe', 'flying jets', '404', 'aa', 'a', '01 adams'], ['bluffton', 'bluffton', 'tigers', '467', 'aa', 'aa', '90 wells'], ['garrett', 'garrett', 'railroaders', '598', 'aaa', 'aaa', '17 de kalb'], ['heritage', 'monroeville', 'patriots', '734', 'aaa', 'aaa', '02 allen'], ['leo', 'leo - cedarville', 'l... |
1960 - 61 primeira divisão | https://en.wikipedia.org/wiki/1960%E2%80%9361_Primeira_Divis%C3%A3o | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17933459-2.html.csv | unique | in the 1960 - 61 primeira divisão , for clubs that have 27 seasons at this level , the only one with settlements as porto is the porto club . | {'scope': 'subset', 'row': '4', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'porto', 'subset': {'col': '2', 'criterion': 'equal', 'value': '27 seasons'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'seasons at this level', '27 seasons'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; seasons at this level ; 27 seasons }', 'tointer': 'select the rows whose seasons at this... | and { only { filter_eq { filter_eq { all_rows ; seasons at this level ; 27 seasons } ; settlements ; porto } } ; eq { hop { filter_eq { filter_eq { all_rows ; seasons at this level ; 27 seasons } ; settlements ; porto } ; clubs } ; porto } } = true | select the rows whose seasons at this level record fuzzily matches to 27 seasons . among these rows , select the rows whose settlements record fuzzily matches to porto . there is only one such row in the table . the clubs record of this unqiue row is porto . | 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, 'seasons at this level_8': 8, '27 seasons_9': 9, 'settlements_10': 10, 'porto_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'clubs_12': 12, 'porto_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', 'seasons at this level_8': 'seasons at this level', '27 seasons_9': '27 seasons', 'settlements_10': 'settlements', 'porto_11': 'porto', 'str_eq_4': 'str_eq', 'str_hop_... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'seasons at this level_8': [0], '27 seasons_9': [0], 'settlements_10': [1], 'porto_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'clubs_12': [3], 'porto_13': [4]} | ['clubs', 'seasons at this level', 'settlements', 'season joined league', 'position in 1959 - 1960'] | [['benfica', '27 seasons', 'lisbon', '1934 - 1935', '1'], ['sporting cp', '27 seasons', 'lisbon', '1934 - 1935', '2'], ['belenenses', '27 seasons', 'lisbon', '1934 - 1935', '3'], ['porto', '27 seasons', 'porto', '1934 - 1935', '4'], ['académica de coimbra', '26 seasons', 'coimbra', '1949 - 1950', '6'], ['vitória de gui... |
list of ireland cricket captains | https://en.wikipedia.org/wiki/List_of_Ireland_cricket_captains | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11783487-3.html.csv | unique | kyle mccallan is the only player to have a tie in the list of ireland cricket captains . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'tied', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tied record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; tied ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; tied ; 1... | and { only { filter_eq { all_rows ; tied ; 1 } } ; eq { hop { filter_eq { all_rows ; tied ; 1 } ; player } ; kyle mccallan } } = true | select the rows whose tied record is equal to 1 . there is only one such row in the table . the player record of this unqiue row is kyle mccallan . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'tied_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'kyle mccallan_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'tied_7': 'tied', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'kyle mccallan_10': 'kyle mccallan'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'tied_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'kyle mccallan_10': [3]} | ['player', 'dates of captaincy', 'lost', 'tied', 'no result', '% win'] | [['alan lewis', '1993 / 94', '4', '0', '0', '42.86'], ['justin benson', '1996 / 97', '3', '0', '1', '66.66'], ['kyle mccallan', '2001 - 2005', '5', '1', '0', '44.44'], ['dekker curry', '2005', '1', '0', '0', '0.00'], ['jason molins', '2005', '0', '0', '0', '100.00'], ['william porterfield', '2009', '2', '0', '0', '80.0... |
lindsay davenport career statistics | https://en.wikipedia.org/wiki/Lindsay_Davenport_career_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22858557-1.html.csv | majority | lindsay davenport has played most of her matches on hard surfaces . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['outcome', 'year', 'championship', 'surface', 'opponent in final', 'score in final'] | [['winner', '1998', 'us open', 'hard', 'martina hingis', '6 - 3 , 7 - 5'], ['winner', '1999', 'wimbledon', 'grass', 'steffi graf', '6 - 4 , 7 - 5'], ['winner', '2000', 'australian open', 'hard', 'martina hingis', '6 - 1 , 7 - 5'], ['runner - up', '2000', 'wimbledon', 'grass', 'venus williams', '6 - 3 , 7 - 6'], ['runne... |
hunt - class mine countermeasures vessel | https://en.wikipedia.org/wiki/Hunt-class_mine_countermeasures_vessel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1162013-1.html.csv | majority | the majority of hunt - class mine countermeasures vessels have a home port of portsmouth . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'portsmouth', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'home port', 'portsmouth'], 'result': True, 'ind': 0, 'tointer': 'for the home port records of all rows , most of them fuzzily match to portsmouth .', 'tostr': 'most_eq { all_rows ; home port ; portsmouth } = true'} | most_eq { all_rows ; home port ; portsmouth } = true | for the home port records of all rows , most of them fuzzily match to portsmouth . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'home port_3': 3, 'portsmouth_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'home port_3': 'home port', 'portsmouth_4': 'portsmouth'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'home port_3': [0], 'portsmouth_4': [0]} | ['navy', 'name', 'pennant', 'commissioned', 'home port'] | [['royal navy', 'brecon', 'm29', '1980', 'hms raleigh'], ['royal navy', 'ledbury', 'm30', '1981', 'portsmouth'], ['royal navy', 'cattistock', 'm31', '1982', 'portsmouth'], ['royal navy', 'cottesmore', 'm32', '1983', 'portsmouth'], ['royal navy', 'brocklesby', 'm33', '1982', 'portsmouth'], ['royal navy', 'middleton', 'm... |
euro convergence criteria | https://en.wikipedia.org/wiki/Euro_convergence_criteria | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1884378-1.html.csv | comparative | latvian lats has an earlier official target date than lithuanian litas . | {'row_1': '6', 'row_2': '7', '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', 'currency', 'latvian lats'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose currency record fuzzily matches to latvian lats .', 'tostr': 'filter_eq { all_rows ; currency ; latvian lats }'}, 'official targe... | less { hop { filter_eq { all_rows ; currency ; latvian lats } ; official target date } ; hop { filter_eq { all_rows ; currency ; lithuanian litas } ; official target date } } = true | select the rows whose currency record fuzzily matches to latvian lats . take the official target date record of this row . select the rows whose currency record fuzzily matches to lithuanian litas . take the official target date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'currency_7': 7, 'latvian lats_8': 8, 'official target date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'currency_11': 11, 'lithuanian litas_12': 12, 'official target date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'currency_7': 'currency', 'latvian lats_8': 'latvian lats', 'official target date_9': 'official target date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows'... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'currency_7': [0], 'latvian lats_8': [0], 'official target date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'currency_11': [1], 'lithuanian litas_12': [1], 'official target date_13': [3]} | ['currency', 'code', 'entry erm ii', 'central rate', 'official target date'] | [['bulgarian lev', 'bgn', '-', '1.95583', '-'], ['croatian kuna', 'hrk', '-', '-', '-'], ['czech koruna', 'czk', '-', '-', '-'], ['danish krone', 'dkk', '1 january 1999', '7.46038', 'formal opt - out'], ['hungarian forint', 'huf', '-', '-', '-'], ['latvian lats', 'lvl', '2 may 2005', '0.702804', '1 january 2014'], ['li... |
list of highest - grossing bollywood films | https://en.wikipedia.org/wiki/List_of_highest-grossing_Bollywood_films | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11872185-6.html.csv | majority | most of the top ten grossing films made over 25,00,000 in a single day . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '25 , 00 , 00000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'single day net gross', '25 , 00 , 00000'], 'result': True, 'ind': 0, 'tointer': 'for the single day net gross records of all rows , most of them are greater than 25 , 00 , 00000 .', 'tostr': 'most_greater { all_rows ; single day net gross ; 25 , 00 , 00000 } = true'} | most_greater { all_rows ; single day net gross ; 25 , 00 , 00000 } = true | for the single day net gross records of all rows , most of them are greater than 25 , 00 , 00000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'single day net gross_3': 3, '25 , 00 , 00000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'single day net gross_3': 'single day net gross', '25 , 00 , 00000_4': '25 , 00 , 00000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'single day net gross_3': [0], '25 , 00 , 00000_4': [0]} | ['rank', 'movie', 'year', 'studio ( s )', 'single day net gross', 'day in release', 'day of week'] | [['1', 'chennai express', '2013', 'red chillies entertainment', '33 , 12 , 00000', 'friday', '1'], ['2', 'ek tha tiger', '2012', 'yash raj films', '32 , 93 , 00000', 'wednesday', '1'], ['3', 'chennai express', '2013', 'red chillies entertainment', '32 , 50 , 00000', 'sunday', '3'], ['4', 'chennai express', '2013', 'red... |
nadia fanchini | https://en.wikipedia.org/wiki/Nadia_Fanchini | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15692953-1.html.csv | unique | nadia fanchini only placed first one time in lake louise , canada on december 7 , 2008 . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': '1st', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'place', '1st'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose place record fuzzily matches to 1st .', 'tostr': 'filter_eq { all_rows ; place ; 1st }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq {... | and { only { filter_eq { all_rows ; place ; 1st } } ; eq { hop { filter_eq { all_rows ; place ; 1st } ; date } ; 7 dec 2008 } } = true | select the rows whose place record fuzzily matches to 1st . there is only one such row in the table . the date record of this unqiue row is 7 dec 2008 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'place_7': 7, '1st_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '7 dec 2008_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'place_7': 'place', '1st_8': '1st', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '7 dec 2008_10': '7 dec 2008'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'place_7': [0], '1st_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '7 dec 2008_10': [3]} | ['season', 'date', 'location', 'discipline', 'place'] | [['2007', '1 dec 2006', 'lake louise , canada', 'downhill', '3rd'], ['2008', '9 feb 2008', 'sestriere , italy', 'downhill', '3rd'], ['2008', '8 mar 2008', 'crans montana , switzerland', 'downhill', '3rd'], ['2009', '5 dec 2008', 'lake louise , canada', 'downhill', '2nd'], ['2009', '7 dec 2008', 'lake louise , canada', ... |
art competitions at the 1928 summer olympics | https://en.wikipedia.org/wiki/Art_competitions_at_the_1928_Summer_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16574447-6.html.csv | aggregation | in art competitions at the 1928 summer olympics , the average number of gold medals won was .82 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '.82', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'gold'], 'result': '.82', 'ind': 0, 'tostr': 'avg { all_rows ; gold }'}, '.82'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; gold } ; .82 } = true', 'tointer': 'the average of the gold record of all rows is .82 .'} | round_eq { avg { all_rows ; gold } ; .82 } = true | the average of the gold record of all rows is .82 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'gold_4': 4, '.82_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '.82_5': '.82'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'gold_4': [0], '.82_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'netherlands ( ned )', '2', '1', '1', '4'], ['2', 'germany ( ger )', '1', '2', '5', '8'], ['3', 'france ( fra )', '1', '2', '1', '4'], ['4', 'great britain ( gbr )', '1', '1', '0', '2'], ['5', 'poland ( pol )', '1', '0', '1', '2'], ['6', 'austria ( aut )', '1', '0', '0', '1'], ['6', 'hungary ( hun )', '1', '0', ... |
camarines norte | https://en.wikipedia.org/wiki/Camarines_Norte | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-255885-1.html.csv | comparative | in camarines norte , jose panganiban has a larger area than daet . | {'row_1': '4', 'row_2': '3', 'col': '3', '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', 'municipality', 'jose panganiban'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose municipality record fuzzily matches to jose panganiban .', 'tostr': 'filter_eq { all_rows ; municipality ; jose pangani... | greater { hop { filter_eq { all_rows ; municipality ; jose panganiban } ; area ( km square ) } ; hop { filter_eq { all_rows ; municipality ; daet ( capital town ) } ; area ( km square ) } } = true | select the rows whose municipality record fuzzily matches to jose panganiban . take the area ( km square ) record of this row . select the rows whose municipality record fuzzily matches to daet ( capital town ) . take the area ( km square ) 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, 'municipality_7': 7, 'jose panganiban_8': 8, 'area (km square)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'municipality_11': 11, 'daet (capital town)_12': 12, 'area (km square)_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', 'municipality_7': 'municipality', 'jose panganiban_8': 'jose panganiban', 'area (km square)_9': 'area ( km square )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_1... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'municipality_7': [0], 'jose panganiban_8': [0], 'area (km square)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'municipality_11': [1], 'daet (capital town)_12': [1], 'area (km square)_13': [3]} | ['municipality', 'no of s barangay', 'area ( km square )', 'population ( 2007 )', 'population ( 2010 )'] | [['basud', '29', '260.28', '36763', '38176'], ['capalonga', '22', '290.00', '29683', '31299'], ['daet ( capital town )', '25', '46.00', '94184', '95572'], ['jose panganiban', '27', '214.44', '49028', '55557'], ['labo', '52', '589.36', '88087', '92041'], ['mercedes', '26', '173.69', '44375', '47674'], ['paracale', '27',... |
westinghouse broadcasting | https://en.wikipedia.org/wiki/Westinghouse_Broadcasting | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1553485-1.html.csv | unique | for westinghouse broadcasting , when the current affiliation is cbs owned and operated , the only time the city is pittsburgh is when the station is kdka-tv . | {'scope': 'subset', 'row': '7', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': 'pittsburgh', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'cbs owned - and - operated ( o & o )'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'current affiliation', 'cbs owned - and - operated ( o & o )'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; current affiliation ; cbs owned - and - operated ( o & o ) }', '... | and { only { filter_eq { filter_eq { all_rows ; current affiliation ; cbs owned - and - operated ( o & o ) } ; city of license / market ; pittsburgh } } ; eq { hop { filter_eq { filter_eq { all_rows ; current affiliation ; cbs owned - and - operated ( o & o ) } ; city of license / market ; pittsburgh } ; station } ; kd... | select the rows whose current affiliation record fuzzily matches to cbs owned - and - operated ( o & o ) . among these rows , select the rows whose city of license / market record fuzzily matches to pittsburgh . there is only one such row in the table . the station record of this unqiue row is kdka - tv . | 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, 'current affiliation_8': 8, 'cbs owned - and - operated (o&o)_9': 9, 'city of license / market_10': 10, 'pittsburgh_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'station_12': 12, 'kdka - tv_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', 'current affiliation_8': 'current affiliation', 'cbs owned - and - operated (o&o)_9': 'cbs owned - and - operated ( o & o )', 'city of license / market_10': 'city of l... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'current affiliation_8': [0], 'cbs owned - and - operated (o&o)_9': [0], 'city of license / market_10': [1], 'pittsburgh_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'station_12': [3], 'kdka - tv_13': [4]... | ['city of license / market', 'station', 'channel tv ( dt )', 'years owned', 'current affiliation'] | [['san francisco - oakland - san jose', 'kpix', '5 ( 29 )', '1954 - 1995', 'cbs owned - and - operated ( o & o )'], ['baltimore', 'wjz - tv', '13 ( 13 )', '1957 - 1995', 'cbs owned - and - operated ( o & o )'], ['boston', 'wbz - tv', '4 ( 30 )', '1948 - 1995', 'cbs owned - and - operated ( o & o )'], ['charlotte', 'wpc... |
richard crunkilton | https://en.wikipedia.org/wiki/Richard_Crunkilton | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17443070-2.html.csv | aggregation | the average number of rounds played by richard crunkilton during an event was 1.95 rounds . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '1.95', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'round'], 'result': '1.95', 'ind': 0, 'tostr': 'avg { all_rows ; round }'}, '1.95'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; round } ; 1.95 } = true', 'tointer': 'the average of the round record of all rows is 1.95 .'} | round_eq { avg { all_rows ; round } ; 1.95 } = true | the average of the round record of all rows is 1.95 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'round_4': 4, '1.95_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'round_4': 'round', '1.95_5': '1.95'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'round_4': [0], '1.95_5': [1]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time'] | [['win', '17 - 3', 'carlo prater', 'decision ( split )', 'shine : lightweight grand prix', '3', '5:00'], ['loss', '16 - 3', 'dave jansen', 'decision ( unanimous )', 'wec 43', '3', '5:00'], ['win', '16 - 2', 'sergio gomez', 'decision ( unanimous )', 'wec 33', '3', '5:00'], ['loss', '15 - 2', 'rob mccullough', 'tko ( pun... |
the apprentice australia | https://en.wikipedia.org/wiki/The_Apprentice_Australia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24501530-1.html.csv | aggregation | the average age of candidates on the apprentice australia was 30 years old . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '30', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'age'], 'result': '30', 'ind': 0, 'tostr': 'avg { all_rows ; age }'}, '30'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; age } ; 30 } = true', 'tointer': 'the average of the age record of all rows is 30 .'} | round_eq { avg { all_rows ; age } ; 30 } = true | the average of the age record of all rows is 30 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'age_4': 4, '30_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'age_4': 'age', '30_5': '30'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'age_4': [0], '30_5': [1]} | ['candidate', 'background', 'original team', 'age', 'hometown', 'result'] | [['andrew morello morello', 'auctioneer', 'pinnacle', '23', 'melbourne , victoria', 'hired by bouris'], ['heather williams', 'advertising sales consultant', 'eventus', '31', 'maylands , western australia', 'fired 2nd in finale'], ['gavin mcinnes', 'lawyer', 'pinnacle', '33', 'brisbane , queensland', 'fired 1st in final... |
2007 - 08 dallas stars season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Dallas_Stars_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11801912-4.html.csv | majority | all games of the dallas stars ' in the 2007 - 08 season were played in the month of november . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'november', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to november .', 'tostr': 'all_eq { all_rows ; date ; november } = true'} | all_eq { all_rows ; date ; november } = true | for the date records of all rows , all of them fuzzily match to november . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'november_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'november_4': 'november'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'november_4': [0]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['november 2', 'phoenix', '5 - 0', 'dallas', 'smith', '18203', '5 - 6 - 2'], ['november 5', 'dallas', '5 - 0', 'anaheim', 'turco', '17174', '6 - 6 - 2'], ['november 7', 'dallas', '3 - 1', 'san jose', 'turco', '17496', '7 - 6 - 2'], ['november 8', 'dallas', '2 - 5', 'phoenix', 'turco', '12027', '7 - 7 - 2'], ['november... |
kashmir | https://en.wikipedia.org/wiki/Kashmir | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17337-1.html.csv | unique | ladakh area , is the only area that has any practicing buddhist . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'not_equal', 'value': '-', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_not_eq', 'args': ['all_rows', '% buddhist', '-'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose % buddhist record is not equal to - .', 'tostr': 'filter_not_eq { all_rows ; % buddhist ; - }'}], 'result': True, 'ind': 1, 'tostr': 'only { f... | and { only { filter_not_eq { all_rows ; % buddhist ; - } } ; eq { hop { filter_not_eq { all_rows ; % buddhist ; - } ; area } ; ladakh } } = true | select the rows whose % buddhist record is not equal to - . there is only one such row in the table . the area record of this unqiue row is ladakh . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_not_eq_0': 0, 'all_rows_6': 6, '% buddhist_7': 7, '-_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'area_9': 9, 'ladakh_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_not_eq_0': 'filter_not_eq', 'all_rows_6': 'all_rows', '% buddhist_7': '% buddhist', '-_8': '-', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'area_9': 'area', 'ladakh_10': 'ladakh'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_not_eq_0': [1, 2], 'all_rows_6': [0], '% buddhist_7': [0], '-_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'area_9': [2], 'ladakh_10': [3]} | ['area', 'population', '% muslim', '% hindu', '% buddhist', '% other'] | [['kashmir valley', '~ 4 million ( 4 million )', '95 %', '4 %', '-', '-'], ['jammu', '~ 3 million ( 3 million )', '30 %', '66 %', '-', '4 %'], ['ladakh', '~ 0.25 million ( 250000 )', '46 %', '-', '50 %', '3 %'], ['azad kashmir', '~ 2.6 million ( 2.6 million )', '100 %', '-', '-', '-'], ['gilgit - baltistan', '~ 1 milli... |
50 metre rifle prone | https://en.wikipedia.org/wiki/50_metre_rifle_prone | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18656178-1.html.csv | count | in the 50 metre rifle prone , between year 1962 and 1974 it was once in cairo . | {'scope': 'subset', 'criterion': 'equal', 'value': 'cairo', 'result': '1', 'col': '2', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '1974'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'year', '1974'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; year ; 1974 }', 'tointer': 'select the rows whose year record is less than or equal to 1974 .'}, 'place',... | eq { count { filter_eq { filter_less_eq { all_rows ; year ; 1974 } ; place ; cairo } } ; 1 } = true | select the rows whose year record is less than or equal to 1974 . among these rows , select the rows whose place record fuzzily matches to cairo . the number of such rows is 1 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_less_eq_0': 0, 'all_rows_5': 5, 'year_6': 6, '1974_7': 7, 'place_8': 8, 'cairo_9': 9, '1_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_5': 'all_rows', 'year_6': 'year', '1974_7': '1974', 'place_8': 'place', 'cairo_9': 'cairo', '1_10': '1'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_less_eq_0': [1], 'all_rows_5': [0], 'year_6': [0], '1974_7': [0], 'place_8': [1], 'cairo_9': [1], '1_10': [3]} | ['year', 'place', 'gold', 'silver', 'bronze'] | [['1962', 'cairo', 'karl wenk ( frg )', 'vladimir chuian ( urs )', 'james enoch hill ( usa )'], ['1966', 'wiesbaden', 'david boyd ( usa )', 'jerzy nowicki ( pol )', 'bill krilling ( usa )'], ['1970', 'phoenix', 'manfred fiess ( rsa )', 'esa einari kervinen ( fin )', 'klaus zaehringer ( frg )'], ['1974', 'thun', 'karel ... |
mont ventoux | https://en.wikipedia.org/wiki/Mont_Ventoux | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-162439-2.html.csv | unique | 1974 was the only year that gonzalo aja was the leader at the summit of the mont ventoux race . | {'scope': 'all', 'row': '2', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'gonzalo aja', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'leader at the summit', 'gonzalo aja'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose leader at the summit record fuzzily matches to gonzalo aja .', 'tostr': 'filter_eq { all_rows ; leader at the summit ; gon... | and { only { filter_eq { all_rows ; leader at the summit ; gonzalo aja } } ; eq { hop { filter_eq { all_rows ; leader at the summit ; gonzalo aja } ; year } ; 1974 } } = true | select the rows whose leader at the summit record fuzzily matches to gonzalo aja . there is only one such row in the table . the year record of this unqiue row is 1974 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'leader at the summit_7': 7, 'gonzalo aja_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1974_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'leader at the summit_7': 'leader at the summit', 'gonzalo aja_8': 'gonzalo aja', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1974_10': '1974'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'leader at the summit_7': [0], 'gonzalo aja_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1974_10': [3]} | ['year', 'stage', 'category', 'start', 'finish', 'leader at the summit'] | [['1994', '15', 'hc', 'montpellier', 'carpentras', 'eros poli ( ita )'], ['1974', '12', '1', 'savines - le - lac', 'orange', 'gonzalo aja ( esp )'], ['1967', '13', '1', 'marseille', 'carpentras', 'julio jimãnez ( esp )'], ['1955', '11', '1', 'marseille', 'avignon', 'louison bobet ( fra )'], ['1952', '14', '1', 'aix - e... |
2008 in british television | https://en.wikipedia.org/wiki/2008_in_British_television | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13549921-18.html.csv | count | three of the programmes returned on the same channel as the original . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'same channel as original', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'new channel ( s )', 'same channel as original'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose new channel ( s ) record fuzzily matches to same channel as original .', 'tostr': 'filter_eq { all_rows ; new ch... | eq { count { filter_eq { all_rows ; new channel ( s ) ; same channel as original } } ; 3 } = true | select the rows whose new channel ( s ) record fuzzily matches to same channel as original . 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, 'new channel (s)_5': 5, 'same channel as original_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', 'new channel (s)_5': 'new channel ( s )', 'same channel as original_6': 'same channel as original', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'new channel (s)_5': [0], 'same channel as original_6': [0], '3_7': [2]} | ['programme', 'date ( s ) of original removal', 'original channel', 'date ( s ) of return', 'new channel ( s )'] | [['mr and mrs as all star mr & mrs', '1999', 'itv', '12 april 2008', 'n / a ( same channel as original )'], ['itv news at ten', '5 march 1999 30 january 2004', 'itv', '22 january 2001 14 january 2008', 'n / a ( same channel as original )'], ['gladiators', '1 january 2000', 'itv', '11 may 2008', 'sky1'], ['superstars', ... |
1948 vfl season | https://en.wikipedia.org/wiki/1948_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809529-8.html.csv | superlative | in the 1948 vfl season , the match that took place at punt road oval had the largest crowd . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '5', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'venue'], 'result': 'punt road oval', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; venue }'}, 'punt road oval'], 'result': True, 'ind':... | eq { hop { argmax { all_rows ; crowd } ; venue } ; punt road oval } = true | select the row whose crowd record of all rows is maximum . the venue record of this row is punt road oval . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'venue_6': 6, 'punt road oval_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', 'venue_6': 'venue', 'punt road oval_7': 'punt road oval'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'venue_6': [1], 'punt road oval_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '15.16 ( 106 )', 'south melbourne', '19.12 ( 126 )', 'kardinia park', '19500', '5 june 1948'], ['collingwood', '11.17 ( 83 )', 'melbourne', '11.10 ( 76 )', 'victoria park', '20000', '5 june 1948'], ['st kilda', '7.12 ( 54 )', 'hawthorn', '10.12 ( 72 )', 'junction oval', '7000', '5 june 1948'], ['north melb... |
sri lanka at the commonwealth games | https://en.wikipedia.org/wiki/Sri_Lanka_at_the_Commonwealth_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18916531-3.html.csv | count | a total of six sri lankan people won silver medals at the commonwealth games . | {'scope': 'all', 'criterion': 'equal', 'value': 'silver', 'result': '6', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'medal', 'silver'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose medal record fuzzily matches to silver .', 'tostr': 'filter_eq { all_rows ; medal ; silver }'}], 'result': '6', 'ind': 1, 'tostr': 'count { fi... | eq { count { filter_eq { all_rows ; medal ; silver } } ; 6 } = true | select the rows whose medal record fuzzily matches to silver . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'medal_5': 5, 'silver_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'medal_5': 'medal', 'silver_6': 'silver', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'medal_5': [0], 'silver_6': [0], '6_7': [2]} | ['medal', 'name', 'games', 'sport', 'event'] | [['gold', 'barney henricus', '1938 sydney', 'boxing', 'featherweight ( 57 kg )'], ['gold', 'duncan white', '1950 auckland', 'athletics', "men 's 440 yards hurdles"], ['gold', 'pushpamali ramanayake malee wickremasinghe', '1994 victoria', 'shooting', "women 's air rifle - pairs"], ['gold', 'chinthana vidanage', '2006 me... |
1986 dallas cowboys season | https://en.wikipedia.org/wiki/1986_Dallas_Cowboys_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11309481-2.html.csv | comparative | more people attended the first game of the dallas cowboys ' season in 1986 than the last game . | {'row_1': '1', 'row_2': '16', 'col': '6', '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', 'date', 'september 8 , 1986'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to september 8 , 1986 .', 'tostr': 'filter_eq { all_rows ; date ; september 8 , 1986 }'}, 'atten... | greater { hop { filter_eq { all_rows ; date ; september 8 , 1986 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 21 , 1986 } ; attendance } } = true | select the rows whose date record fuzzily matches to september 8 , 1986 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 21 , 1986 . take the attendance 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, 'date_7': 7, 'september 8 , 1986_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'december 21 , 1986_12': 12, 'attendance_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', 'date_7': 'date', 'september 8 , 1986_8': 'september 8 , 1986', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'september 8 , 1986_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'december 21 , 1986_12': [1], 'attendance_13': [3]} | ['week', 'date', 'opponent', 'result', 'game site', 'attendance'] | [['1', 'september 8 , 1986', 'new york giants', 'w 31 - 28', 'texas stadium', '59804'], ['2', 'september 14 , 1986', 'detroit lions', 'w 31 - 7', 'pontiac silverdome', '73812'], ['3', 'september 21 , 1986', 'atlanta falcons', 'l 35 - 37', 'texas stadium', '62880'], ['4', 'september 29 , 1986', 'st louis cardinals', 'w ... |
memphis grizzlies all - time roster | https://en.wikipedia.org/wiki/Memphis_Grizzlies_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16494599-13.html.csv | count | of the players on the memphis grizzlies all - time roster from the united states , two played center . | {'scope': 'subset', 'criterion': 'equal', 'value': 'center', 'result': '2', 'col': '3', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; nationality ; united states }', 'tointer': 'select the rows whose nationality record fuzzily ma... | eq { count { filter_eq { filter_eq { all_rows ; nationality ; united states } ; position ; center } } ; 2 } = true | select the rows whose nationality record fuzzily matches to united states . among these rows , select the rows whose position record fuzzily matches to center . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'nationality_6': 6, 'united states_7': 7, 'position_8': 8, 'center_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'nationality_6': 'nationality', 'united states_7': 'united states', 'position_8': 'position', 'center_9': 'center', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'nationality_6': [0], 'united states_7': [0], 'position_8': [1], 'center_9': [1], '2_10': [3]} | ['player', 'nationality', 'position', 'years for grizzlies', 'school / club team'] | [['sam mack', 'united states', 'guard - forward', '1997 - 1998', 'houston'], ['rich manning', 'united states', 'forward / center', '1995 - 1997', 'washington'], ['cuonzo martin', 'united states', 'guard - forward', '1995 - 1996', 'purdue'], ['darrick martin', 'united states', 'point guard', '1995 - 1996', 'ucla'], ['to... |
1998 icc knockout trophy | https://en.wikipedia.org/wiki/1998_ICC_KnockOut_Trophy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11950720-1.html.csv | count | five players in the 1998 icc knockout trophy were with the new south wales first class team . | {'scope': 'all', 'criterion': 'equal', 'value': 'new south wales', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first class team', 'new south wales'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first class team record fuzzily matches to new south wales .', 'tostr': 'filter_eq { all_rows ; first class team ; new sou... | eq { count { filter_eq { all_rows ; first class team ; new south wales } } ; 5 } = true | select the rows whose first class team record fuzzily matches to new south wales . 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, 'first class team_5': 5, 'new south wales_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', 'first class team_5': 'first class team', 'new south wales_6': 'new south wales', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'first class team_5': [0], 'new south wales_6': [0], '5_7': [2]} | ['player', 'date of birth', 'batting style', 'bowling style', 'first class team'] | [['steve waugh ( captain )', '2 june 1965', 'right hand bat', 'right arm medium', 'new south wales'], ['mark waugh ( vice - captain )', '2 june 1965', 'right hand bat', 'right arm medium right arm off break', 'new south wales'], ['michael bevan', '8 may 1970', 'left hand bat', 'left arm slow chinaman', 'new south wales... |
farsi1 | https://en.wikipedia.org/wiki/FARSI1 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28803803-1.html.csv | ordinal | the third-highest number of episodes in a show shown on farsi1 was 135 . | {'row': '5', 'col': '5', 'order': '3', 'col_other': 'n/a', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'no of episodes', '3'], 'result': '135', 'ind': 0, 'tostr': 'nth_max { all_rows ; no of episodes ; 3 }', 'tointer': 'the 3rd maximum no of episodes record of all rows is 135 .'}, '135'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; no of ... | eq { nth_max { all_rows ; no of episodes ; 3 } ; 135 } = true | the 3rd maximum no of episodes record of all rows is 135 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_max_0': 0, 'all_rows_3': 3, 'no of episodes_4': 4, '3_5': 5, '135_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_max_0': 'nth_max', 'all_rows_3': 'all_rows', 'no of episodes_4': 'no of episodes', '3_5': '3', '135_6': '135'} | {'eq_1': [2], 'result_2': [], 'nth_max_0': [1], 'all_rows_3': [0], 'no of episodes_4': [0], '3_5': [0], '135_6': [1]} | ['no', 'name', 'country', 'original channel', 'no of episodes', 'running time', 'launched', 'date', 'irst'] | [['1', "lara 's choice", 'croatia', 'nova tv ( 2011 )', '182', '45 minutes', '28 jul 2012', 'saturday to wednesday', '21:00 - 22:00'], ['2', 'falling angel', 'united states', 'telemundo ( 2009 )', '182', '45 minutes', '11 mar 2013', 'saturday to wednesday', '20:00 - 21:00'], ['3', 'elisa', 'italy', 'canale 5 ( 2003 )',... |
united states district court for the eastern district of california | https://en.wikipedia.org/wiki/United_States_District_Court_for_the_Eastern_District_of_California | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1065275-2.html.csv | superlative | of the judges in the united states district court for the eastern district of california , the oldest one currently living was born in 1928 . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '9', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': 'n/a', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'present'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'born / died', 'present'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; born / died ; present }', 'tointer': 'select the rows whose born / died record fuzzily matches to present .'}, 'born / died'], 'result': '... | eq { min { filter_eq { all_rows ; born / died ; present } ; born / died } ; 1928 - present } = true | select the rows whose born / died record fuzzily matches to present . the minimum born / died record of these rows is 1928 - present . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'born / died_5': 5, 'present_6': 6, 'born / died_7': 7, '1928 - present_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'born / died_5': 'born / died', 'present_6': 'present', 'born / died_7': 'born / died', '1928 - present_8': '1928 - present'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'born / died_5': [0], 'present_6': [0], 'born / died_7': [1], '1928 - present_8': [2]} | ['state', 'born / died', 'active service', 'chief judge', 'senior status', 'appointed by', 'reason for termination'] | [['ca', '1914 - 2010', '1966 - 1981', '1966 - 1967', '1981 - 2010', 'eisenhower', 'death'], ['ca', '1901 - 1991', '1966 - 1969', '-', '1969 - 1991', 'eisenhower', 'death'], ['ca', '1914 - 2000', '1966 - 1979', '1967 - 1979', '1979 - 2000', 'kennedy', 'death'], ['ca', '1913 - 1998', '1969 - 1983', '1979 - 1983', '1983 -... |
miguel zepeda | https://en.wikipedia.org/wiki/Miguel_Zepeda | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15316394-1.html.csv | majority | in the majority of the games shown miguel zepeda scored a single goal . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'score', '1'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them are equal to 1 .', 'tostr': 'most_eq { all_rows ; score ; 1 } = true'} | most_eq { all_rows ; score ; 1 } = true | for the score records of all rows , most of them are equal to 1 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, '1_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', '1_4': '1'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], '1_4': [0]} | ['goal', 'date', 'venue', 'score', 'result', 'competition'] | [['1', 'july 17 , 1999', 'estadio defensores del chaco , asunción , paraguay', '2 - 1', '2 - 1', '1999 copa américa'], ['2', 'august 4 , 1999', 'estadio azteca , mexico city , mexico', '1 - 0', '4 - 3', '1999 fifa confederations cup'], ['3', 'august 4 , 1999', 'estadio azteca , mexico city , mexico', '3 - 2', '4 - 3', ... |
wzxv | https://en.wikipedia.org/wiki/WZXV | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15493221-1.html.csv | superlative | w283au has the highesst frequency of all wzxv radio station call signs . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'frequency mhz'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; frequency mhz }'}, 'call sign'], 'result': 'w283au', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; frequency mhz } ; call sign }'}, 'w283au'], 'resul... | eq { hop { argmax { all_rows ; frequency mhz } ; call sign } ; w283au } = true | select the row whose frequency mhz record of all rows is maximum . the call sign record of this row is w283au . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'frequency mhz_5': 5, 'call sign_6': 6, 'w283au_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'frequency mhz_5': 'frequency mhz', 'call sign_6': 'call sign', 'w283au_7': 'w283au'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'frequency mhz_5': [0], 'call sign_6': [1], 'w283au_7': [2]} | ['call sign', 'frequency mhz', 'city of license', 'facility id', 'erp w', 'height m ( ft )', 'class', 'fcc info'] | [['w227bw', '93.3', 'cheektowaga', '151267', '99', '-', 'd', 'fcc'], ['w248at', '97.5', 'corfy', '150935', '10', '-', 'd', 'fcc'], ['w248bc', '97.5', 'dansville', '86505', '10', '-', 'd', 'fcc'], ['w266be', '101.1', 'auburn', '138601', '27', '-', 'd', 'fcc'], ['w273af', '102.5', 'penn yan', '86524', '3', '-', 'd', 'fcc... |
satoru nakajima | https://en.wikipedia.org/wiki/Satoru_Nakajima | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226566-2.html.csv | aggregation | the total number of points scored by satoru nakajima in his career is 19 . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '19', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '19', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '19'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 19 } = true', 'tointer': 'the sum of the points record of all rows is 19 .'} | round_eq { sum { all_rows ; points } ; 19 } = true | the sum of the points record of all rows is 19 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '19_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '19_5': '19'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '19_5': [1]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1987', 'camel team lotus honda', 'lotus 99t', 'honda v6', '7'], ['1988', 'camel team lotus honda', 'lotus 100t', 'honda v6', '1'], ['1989', 'camel team lotus', 'lotus 101', 'judd v8', '3'], ['1990', 'tyrrell racing organisation', 'tyrrell 018', 'cosworth v8', '3'], ['1990', 'tyrrell racing organisation', 'tyrrell 01... |
1975 world judo championships | https://en.wikipedia.org/wiki/1975_World_Judo_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15807850-2.html.csv | aggregation | the average number of bronze medals won per country at the 1975 world judo championships was 1.7 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '1.7', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'bronze'], 'result': '1.7', 'ind': 0, 'tostr': 'avg { all_rows ; bronze }'}, '1.7'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; bronze } ; 1.7 } = true', 'tointer': 'the average of the bronze record of all rows is 1.7 .'} | round_eq { avg { all_rows ; bronze } ; 1.7 } = true | the average of the bronze record of all rows is 1.7 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'bronze_4': 4, '1.7_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'bronze_4': 'bronze', '1.7_5': '1.7'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'bronze_4': [0], '1.7_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'japan', '4', '4', '3', '11'], ['2', 'soviet union', '1', '2', '3', '6'], ['3', 'france', '1', '0', '1', '2'], ['4', 'east germany', '0', '0', '2', '2'], ['5', 'italy', '0', '0', '1', '1'], ['5', 'poland', '0', '0', '1', '1'], ['5', 'north korea', '0', '0', '1', '1']] |
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/1-14934885-1.html.csv | unique | episode 5 is the only episode of whose line is it anyway ? uk in which john bird was a performer . | {'scope': 'all', 'row': '5', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': 'john bird', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'performer 4', 'john bird'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose performer 4 record fuzzily matches to john bird .', 'tostr': 'filter_eq { all_rows ; performer 4 ; john bird }'}], 'result': True, 'i... | and { only { filter_eq { all_rows ; performer 4 ; john bird } } ; eq { hop { filter_eq { all_rows ; performer 4 ; john bird } ; episode } ; 5 } } = true | select the rows whose performer 4 record fuzzily matches to john bird . there is only one such row in the table . the episode record of this unqiue row is 5 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'performer 4_7': 7, 'john bird_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'episode_9': 9, '5_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'performer 4_7': 'performer 4', 'john bird_8': 'john bird', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'episode_9': 'episode', '5_10': '5'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'performer 4_7': [0], 'john bird_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'episode_9': [2], '5_10': [3]} | ['date', 'episode', 'performer 1', 'performer 2', 'performer 3', 'performer 4'] | [['2 january 1988', '1', 'john sessions', 'stephen fry', 'dawn french', 'lenny henry'], ['9 january 1988', '2', 'john sessions', 'stephen fry', 'hugh laurie', 'enn reitel'], ['16 january 1988', '3', 'john sessions', 'stephen fry', 'nonny williams', 'jimmy mulville'], ['23 january 1988', '4', 'john sessions', 'stephen f... |
list of number - one singles of 2000 ( canada ) | https://en.wikipedia.org/wiki/List_of_number-one_singles_of_2000_%28Canada%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17507197-1.html.csv | superlative | the artist eiffel 65 's song is the first one on the number - one singles list of 2000 . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '5', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'issue date ( s )'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; issue date ( s ) }'}, 'artist'], 'result': 'eiffel 65', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; issue date ( s ) } ; artist }'}, 'eiffel 65'... | eq { hop { argmin { all_rows ; issue date ( s ) } ; artist } ; eiffel 65 } = true | select the row whose issue date ( s ) record of all rows is minimum . the artist record of this row is eiffel 65 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'issue date (s)_5': 5, 'artist_6': 6, 'eiffel 65_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'issue date (s)_5': 'issue date ( s )', 'artist_6': 'artist', 'eiffel 65_7': 'eiffel 65'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'issue date (s)_5': [0], 'artist_6': [1], 'eiffel 65_7': [2]} | ['volume : issue', 'issue date ( s )', 'weeks on top', 'song', 'artist'] | [['70:8 - 9', '13 december - 3 january 2000 ÷', '2 ÷', 'blue', 'eiffel 65'], ['70:10 - 11', '10 january - 17 january', '2', 'i knew i loved you', 'savage garden'], ['70:12', '24 january', '1', 'what a girl wants', 'christina aguilera'], ['70:13 - 14', '31 january - 7 february', '2', 'i knew i loved you', 'savage garden... |
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