niryuu/sni-each-converted huggingface dataset:
Command: round_eq { avg { filter_eq { all_rows ; location attendance ; at & t center } ; location attendance } ; 18581 }, interpretation: select the rows whose hdtv record fuzzily matches to yes . there is only one such row in the table . the television service record of this unqiue row is satisfaction hd .
Output: no
Command: and { only { filter_eq { all_rows ; hdtv ; yes } } ; eq { hop { filter_eq { all_rows ; hdtv ; yes } ; television service } ; satisfaction hd } }, interpretation: select the rows whose hdtv record fuzzily matches to yes . there is only one such row in the table . the television service record of this unqiue row is satisfaction hd .
Output: yes
Command: and { only { filter_eq { all_rows ; hdtv ; yes } } ; eq { hop { filter_eq { all_rows ; hdtv ; yes } ; television service } ; satisfaction hd } }, interpretation: select the rows whose crowd record is greater than 10000 . the number of such rows is 2 .
Output: no
Command: eq { count { filter_greater { all_rows ; crowd ; 10000 } } ; 2 }, interpretation: select the rows whose crowd record is greater than 10000 . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_greater { all_rows ; crowd ; 10000 } } ; 2 }, interpretation: select the rows whose location record fuzzily matches to poland . there is only one such row in the table .
Output: no
Command: only { filter_eq { all_rows ; location ; poland } }, interpretation: select the rows whose location record fuzzily matches to poland . there is only one such row in the table .
Output: yes
Command: only { filter_eq { all_rows ; location ; poland } }, interpretation: select the rows whose player record is arbitrary . the number of such rows is 12 .
Output: no
Command: eq { count { filter_all { all_rows ; player } } ; 12 }, interpretation: select the rows whose player record is arbitrary . the number of such rows is 12 .
Output: yes
Command: eq { count { filter_all { all_rows ; player } } ; 12 }, interpretation: select the row whose points record of all rows is maximum . the singer record of this row is olta boka .
Output: no
Command: eq { hop { argmax { all_rows ; points } ; singer } ; olta boka }, interpretation: select the row whose points record of all rows is maximum . the singer record of this row is olta boka .
Output: yes
Command: eq { hop { argmax { all_rows ; points } ; singer } ; olta boka }, interpretation: select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record fuzzily matches to 143 . the number of such rows is 2 .
Output: no
Command: eq { count { filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 143 } } ; 2 }, interpretation: select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record fuzzily matches to 143 . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 143 } } ; 2 }, interpretation: for the area ( km square ) records of all rows , most of them are greater than 40 .
Output: no
Command: most_greater { all_rows ; area ( km square ) ; 40 }, interpretation: for the area ( km square ) records of all rows , most of them are greater than 40 .
Output: yes
Command: most_greater { all_rows ; area ( km square ) ; 40 }, interpretation: select the row whose attendance record of all rows is maximum . the opponent record of this row is denver broncos .
Output: no
Command: eq { hop { argmax { all_rows ; attendance } ; opponent } ; denver broncos }, interpretation: select the row whose attendance record of all rows is maximum . the opponent record of this row is denver broncos .
Output: yes
Command: eq { hop { argmax { all_rows ; attendance } ; opponent } ; denver broncos }, interpretation: select the row whose events record of all rows is 2nd maximum . the tournament record of this row is pga championship .
Output: no
Command: eq { hop { nth_argmax { all_rows ; events ; 2 } ; tournament } ; pga championship }, interpretation: select the row whose events record of all rows is 2nd maximum . the tournament record of this row is pga championship .
Output: yes
Command: eq { hop { nth_argmax { all_rows ; events ; 2 } ; tournament } ; pga championship }, interpretation: for the result records of all rows , most of them fuzzily match to won .
Output: no
Command: most_eq { all_rows ; result ; won }, interpretation: for the draws records of all rows , all of them are equal to 0 .
Output: no
Command: all_eq { all_rows ; draws ; 0 }, interpretation: for the draws records of all rows , all of them are equal to 0 .
Output: yes
Command: all_eq { all_rows ; draws ; 0 }, interpretation: the average of the t c ( k ) record of all rows is 99.8 degrees .
Output: no
Command: round_eq { avg { all_rows ; t c ( k ) } ; 99.8 degrees }, interpretation: the average of the t c ( k ) record of all rows is 99.8 degrees .
Output: yes
Command: round_eq { avg { all_rows ; t c ( k ) } ; 99.8 degrees }, interpretation: select the rows whose outcome of election record fuzzily matches to ndc opposition . the number of such rows is 2 .
Output: no
Command: eq { count { filter_eq { all_rows ; outcome of election ; ndc opposition } } ; 2 }, interpretation: select the rows whose outcome of election record fuzzily matches to ndc opposition . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_eq { all_rows ; outcome of election ; ndc opposition } } ; 2 }, interpretation: select the row whose score record of all rows is 2nd maximum . the date record of this row is march 13 . the opponent record of this row is baltimore bullets .
Output: no
Command: and { eq { hop { nth_argmax { all_rows ; score ; 2 } ; date } ; march 13 } ; eq { hop { nth_argmax { all_rows ; score ; 2 } ; opponent } ; baltimore bullets } }, interpretation: select the row whose score record of all rows is 2nd maximum . the date record of this row is march 13 . the opponent record of this row is baltimore bullets .
Output: yes
Command: and { eq { hop { nth_argmax { all_rows ; score ; 2 } ; date } ; march 13 } ; eq { hop { nth_argmax { all_rows ; score ; 2 } ; opponent } ; baltimore bullets } }, interpretation: select the rows whose recorded record fuzzily matches to 1980 . there is only one such row in the table .
Output: no
Command: only { filter_eq { all_rows ; recorded ; 1980 } }, interpretation: select the rows whose recorded record fuzzily matches to 1980 . there is only one such row in the table .
Output: yes
Command: only { filter_eq { all_rows ; recorded ; 1980 } }, interpretation: the average of the frequency record of all rows is 2200 mhz .
Output: no
Command: round_eq { avg { all_rows ; frequency } ; 2200 mhz }, interpretation: the average of the frequency record of all rows is 2200 mhz .
Output: yes
Command: round_eq { avg { all_rows ; frequency } ; 2200 mhz }, interpretation: select the row whose commissioned record of all rows is 1st minimum . the name record of this row is cygnet .
Output: no
Command: eq { hop { nth_argmin { all_rows ; commissioned ; 1 } ; name } ; cygnet }, interpretation: select the row whose commissioned record of all rows is 1st minimum . the name record of this row is cygnet .
Output: yes
Command: eq { hop { nth_argmin { all_rows ; commissioned ; 1 } ; name } ; cygnet }, interpretation: select the rows whose area in 1000 km square ( 1930 ) record is greater than 30 . among these rows , select the rows whose population in 1000 ( 1931 ) record is greater than 2000 . the number of such rows is 2 .
Output: no
Command: eq { count { filter_greater { filter_greater { all_rows ; area in 1000 km square ( 1930 ) ; 30 } ; population in 1000 ( 1931 ) ; 2000 } } ; 2 }, interpretation: select the rows whose area in 1000 km square ( 1930 ) record is greater than 30 . among these rows , select the rows whose population in 1000 ( 1931 ) record is greater than 2000 . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_greater { filter_greater { all_rows ; area in 1000 km square ( 1930 ) ; 30 } ; population in 1000 ( 1931 ) ; 2000 } } ; 2 }, interpretation: select the row whose transfer fee record of all rows is maximum . the name record of this row is ferdinand .
Output: no
Command: eq { hop { argmax { all_rows ; transfer fee } ; name } ; ferdinand }, interpretation: select the row whose transfer fee record of all rows is maximum . the name record of this row is ferdinand .
Output: yes
Command: eq { hop { argmax { all_rows ; transfer fee } ; name } ; ferdinand }, interpretation: select the rows whose party record fuzzily matches to independent . there is only one such row in the table . the candidate record of this unqiue row is peter law .
Output: no
Command: and { only { filter_eq { all_rows ; party ; independent } } ; eq { hop { filter_eq { all_rows ; party ; independent } ; candidate } ; peter law } }, interpretation: select the rows whose party record fuzzily matches to independent . there is only one such row in the table . the candidate record of this unqiue row is peter law .
Output: yes
Command: and { only { filter_eq { all_rows ; party ; independent } } ; eq { hop { filter_eq { all_rows ; party ; independent } ; candidate } ; peter law } }, interpretation: select the rows whose country record fuzzily matches to united states . the average of the score record of these rows is 139.5 .
Output: no
Command: round_eq { avg { filter_eq { all_rows ; country ; united states } ; score } ; 139.5 }, interpretation: select the rows whose country record fuzzily matches to united states . the average of the score record of these rows is 139.5 .
Output: yes
Command: round_eq { avg { filter_eq { all_rows ; country ; united states } ; score } ; 139.5 }, interpretation: select the rows whose area record fuzzily matches to featherston . select the row whose roll record of these rows is maximum . the name record of this row is st teresa 's school .
Output: no
Command: eq { hop { argmax { filter_eq { all_rows ; area ; featherston } ; roll } ; name } ; st teresa 's school }, interpretation: select the rows whose area record fuzzily matches to featherston . select the row whose roll record of these rows is maximum . the name record of this row is st teresa 's school .
Output: yes
Command: eq { hop { argmax { filter_eq { all_rows ; area ; featherston } ; roll } ; name } ; st teresa 's school }, interpretation: select the rows whose type record fuzzily matches to embankment . for the height ( m ) records of these rows , most of them are less than 100 .
Output: no
Command: most_less { filter_eq { all_rows ; type ; embankment } ; height ( m ) ; 100 }, interpretation: select the rows whose type record fuzzily matches to embankment . for the height ( m ) records of these rows , most of them are less than 100 .
Output: yes
Command: most_less { filter_eq { all_rows ; type ; embankment } ; height ( m ) ; 100 }, interpretation: select the rows whose municipality record fuzzily matches to tecate . take the area ( km2 ) record of this row . select the rows whose municipality record fuzzily matches to tijuana . take the area ( km2 ) record of this row . the first record is greater than the second record .
Output: no
Command: greater { hop { filter_eq { all_rows ; municipality ; tecate } ; area ( km2 ) } ; hop { filter_eq { all_rows ; municipality ; tijuana } ; area ( km2 ) } }, interpretation: select the rows whose municipality record fuzzily matches to tecate . take the area ( km2 ) record of this row . select the rows whose municipality record fuzzily matches to tijuana . take the area ( km2 ) record of this row . the first record is greater than the second record .
Output: yes
Command: greater { hop { filter_eq { all_rows ; municipality ; tecate } ; area ( km2 ) } ; hop { filter_eq { all_rows ; municipality ; tijuana } ; area ( km2 ) } }, interpretation: select the rows whose opponent record fuzzily matches to denver broncos . take the date record of this row . select the rows whose opponent record fuzzily matches to new york titans . take the date record of this row . the first record is less than the second record .
Output: no
Command: less { hop { filter_eq { all_rows ; opponent ; denver broncos } ; date } ; hop { filter_eq { all_rows ; opponent ; new york titans } ; date } }, interpretation: select the rows whose opponent record fuzzily matches to denver broncos . take the date record of this row . select the rows whose opponent record fuzzily matches to new york titans . take the date record of this row . the first record is less than the second record .
Output: yes
Command: less { hop { filter_eq { all_rows ; opponent ; denver broncos } ; date } ; hop { filter_eq { all_rows ; opponent ; new york titans } ; date } }, interpretation: select the rows whose class record fuzzily matches to d . the average of the quantity record of these rows is 48 .
Output: no
Command: round_eq { avg { filter_eq { all_rows ; class ; d } ; quantity } ; 48 }, interpretation: select the rows whose class record fuzzily matches to d . the average of the quantity record of these rows is 48 .
Output: yes
Command: round_eq { avg { filter_eq { all_rows ; class ; d } ; quantity } ; 48 }, interpretation: select the rows whose year opened record is less than 1954 . there is only one such row in the table . the facility record of this unqiue row is monroe correctional complex ( mcc ) .
Output: no
Command: and { only { filter_less { all_rows ; year opened ; 1954 } } ; eq { hop { filter_less { all_rows ; year opened ; 1954 } ; facility } ; monroe correctional complex ( mcc ) } }, interpretation: select the rows whose year opened record is less than 1954 . there is only one such row in the table . the facility record of this unqiue row is monroe correctional complex ( mcc ) .
Output: yes
Command: and { only { filter_less { all_rows ; year opened ; 1954 } } ; eq { hop { filter_less { all_rows ; year opened ; 1954 } ; facility } ; monroe correctional complex ( mcc ) } }, interpretation: the sum of the total record of all rows is 48 .
Output: no
Command: round_eq { sum { all_rows ; total } ; 48 }, interpretation: the sum of the total record of all rows is 48 .
Output: yes
Command: round_eq { sum { all_rows ; total } ; 48 }, interpretation: select the rows whose series record fuzzily matches to gp2 series . the number of such rows is 2 .
Output: no
Command: eq { count { filter_eq { all_rows ; series ; gp2 series } } ; 2 }, interpretation: select the rows whose series record fuzzily matches to gp2 series . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_eq { all_rows ; series ; gp2 series } } ; 2 }, interpretation: the average of the points record of all rows is 14.56 .
Output: no
Command: round_eq { avg { all_rows ; points } ; 14.56 }, interpretation: the average of the points record of all rows is 14.56 .
Output: yes
Command: round_eq { avg { all_rows ; points } ; 14.56 }, interpretation: select the rows whose directed by record fuzzily matches to brent woods . the number of such rows is 2 .
Output: no
Command: eq { count { filter_eq { all_rows ; directed by ; brent woods } } ; 2 }, interpretation: select the rows whose directed by record fuzzily matches to brent woods . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_eq { all_rows ; directed by ; brent woods } } ; 2 }, interpretation: the sum of the assists record of all rows is 54 .
Output: no
Command: round_eq { sum { all_rows ; assists } ; 54 }, interpretation: the sum of the assists record of all rows is 54 .
Output: yes
Command: round_eq { sum { all_rows ; assists } ; 54 }, interpretation: select the row whose wins record of all rows is maximum . the constructor record of this row is citroën total world rally team .
Output: no
Command: eq { hop { argmax { all_rows ; wins } ; constructor } ; citroën total world rally team }, interpretation: select the row whose wins record of all rows is maximum . the constructor record of this row is citroën total world rally team .
Output: yes
Command: eq { hop { argmax { all_rows ; wins } ; constructor } ; citroën total world rally team }, interpretation: select the row whose pop ( 2010 ) record of all rows is 2nd maximum . the township record of this row is ypsilanti .
Output: no
Command: eq { hop { nth_argmax { all_rows ; pop ( 2010 ) ; 2 } ; township } ; ypsilanti }, interpretation: select the row whose pop ( 2010 ) record of all rows is 2nd maximum . the township record of this row is ypsilanti .
Output: yes
Command: eq { hop { nth_argmax { all_rows ; pop ( 2010 ) ; 2 } ; township } ; ypsilanti }, interpretation: for the vacator records of all rows , most of them fuzzily match to d .
Output: no
Command: most_eq { all_rows ; vacator ; d }, interpretation: for the vacator records of all rows , most of them fuzzily match to d .
Output: yes
Command: most_eq { all_rows ; vacator ; d }, interpretation: for the venue records of all rows , most of them fuzzily match to johannesburg .
Output: no
Command: most_eq { all_rows ; venue ; johannesburg }, interpretation: for the venue records of all rows , most of them fuzzily match to johannesburg .
Output: yes
Command: most_eq { all_rows ; venue ; johannesburg }, interpretation: for the result records of all rows , most of them fuzzily match to won .
Output: no
Command: most_eq { all_rows ; result ; won }, interpretation: select the rows whose round of 16 record does not match to did not advance . the number of such rows is 4 .
Output: no
Command: eq { count { filter_not_eq { all_rows ; round of 16 ; did not advance } } ; 4 }, interpretation: select the rows whose round of 16 record does not match to did not advance . the number of such rows is 4 .
Output: yes
Command: eq { count { filter_not_eq { all_rows ; round of 16 ; did not advance } } ; 4 }, interpretation: select the rows whose engine ( s ) record fuzzily matches to yamaha . there is only one such row in the table . the year record of this unqiue row is 1989 .
Output: no
Command: and { only { filter_eq { all_rows ; engine ( s ) ; yamaha } } ; eq { hop { filter_eq { all_rows ; engine ( s ) ; yamaha } ; year } ; 1989 } }, interpretation: select the rows whose engine ( s ) record fuzzily matches to yamaha . there is only one such row in the table . the year record of this unqiue row is 1989 .
Output: yes
Command: and { only { filter_eq { all_rows ; engine ( s ) ; yamaha } } ; eq { hop { filter_eq { all_rows ; engine ( s ) ; yamaha } ; year } ; 1989 } }, interpretation: for the gdp ( billion us ) records of all rows , most of them are greater than 100 .
Output: no
Command: most_greater { all_rows ; gdp ( billion us ) ; 100 }, interpretation: for the gdp ( billion us ) records of all rows , most of them are greater than 100 .
Output: yes
Command: most_greater { all_rows ; gdp ( billion us ) ; 100 }, interpretation: select the row whose enrollment record of all rows is 2nd maximum . the school record of this row is stony brook university .
Output: no
Command: eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; school } ; stony brook university }, interpretation: select the row whose enrollment record of all rows is 2nd maximum . the school record of this row is stony brook university .
Output: yes
Command: eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; school } ; stony brook university }, interpretation: select the row whose away team score record of all rows is 2nd maximum . the home team record of this row is collingwood .
Output: no
Command: eq { hop { nth_argmax { all_rows ; away team score ; 2 } ; home team } ; collingwood }, interpretation: select the row whose away team score record of all rows is 2nd maximum . the home team record of this row is collingwood .
Output: yes
Command: eq { hop { nth_argmax { all_rows ; away team score ; 2 } ; home team } ; collingwood }, interpretation: select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is ralph a gamble .
Output: no
Command: eq { hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent } ; ralph a gamble }, interpretation: select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is ralph a gamble .
Output: yes
Command: eq { hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent } ; ralph a gamble }, interpretation: select the rows whose transmitter record fuzzily matches to mullaghanish . take the 2fm ( mhz ) record of this row . select the rows whose transmitter record fuzzily matches to mount leinster . take the 2fm ( mhz ) record of this row . the first record is greater than the second record .
Output: no
Command: greater { hop { filter_eq { all_rows ; transmitter ; mullaghanish } ; 2fm ( mhz ) } ; hop { filter_eq { all_rows ; transmitter ; mount leinster } ; 2fm ( mhz ) } }, interpretation: select the rows whose transmitter record fuzzily matches to mullaghanish . take the 2fm ( mhz ) record of this row . select the rows whose transmitter record fuzzily matches to mount leinster . take the 2fm ( mhz ) record of this row . the first record is greater than the second record .
Output: yes
Command: greater { hop { filter_eq { all_rows ; transmitter ; mullaghanish } ; 2fm ( mhz ) } ; hop { filter_eq { all_rows ; transmitter ; mount leinster } ; 2fm ( mhz ) } }, interpretation: select the rows whose result record fuzzily matches to made january shortlist . there is only one such row in the table . the film title used in nomination record of this unqiue row is samson and delilah .
Output: no
Command: and { only { filter_eq { all_rows ; result ; made january shortlist } } ; eq { hop { filter_eq { all_rows ; result ; made january shortlist } ; film title used in nomination } ; samson and delilah } }, interpretation: select the rows whose result record fuzzily matches to made january shortlist . there is only one such row in the table . the film title used in nomination record of this unqiue row is samson and delilah .
Output: yes
Command: and { only { filter_eq { all_rows ; result ; made january shortlist } } ; eq { hop { filter_eq { all_rows ; result ; made january shortlist } ; film title used in nomination } ; samson and delilah } }, interpretation: select the rows whose year of release record is equal to 1979 . the number of such rows is 2 .
Output: no
Command: eq { count { filter_eq { all_rows ; year of release ; 1979 } } ; 2 }, interpretation: select the rows whose year of release record is equal to 1979 . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_eq { all_rows ; year of release ; 1979 } } ; 2 }, interpretation: select the rows whose co - singers record fuzzily matches to solo . the number of such rows is 6 .
Output: no
Command: eq { count { filter_eq { all_rows ; co - singers ; solo } } ; 6 }, interpretation: select the rows whose co - singers record fuzzily matches to solo . the number of such rows is 6 .
Output: yes
Command: eq { count { filter_eq { all_rows ; co - singers ; solo } } ; 6 }, interpretation: select the rows whose label record fuzzily matches to rock records . among these rows , select the rows whose release date record fuzzily matches to 2000 . there is only one such row in the table . the english title record of this unqiue row is courage .
Output: no
Command: and { only { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } } ; eq { hop { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } ; english title } ; courage } }, interpretation: select the rows whose label record fuzzily matches to rock records . among these rows , select the rows whose release date record fuzzily matches to 2000 . there is only one such row in the table . the english title record of this unqiue row is courage .
Output: yes
Command: and { only { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } } ; eq { hop { filter_eq { filter_eq { all_rows ; label ; rock records } ; release date ; 2000 } ; english title } ; courage } }, interpretation: select the rows whose year record is equal to 1967 . the sum of the points record of these rows is 2 .
Output: no
Command: round_eq { sum { filter_eq { all_rows ; year ; 1967 } ; points } ; 2 }, interpretation: select the rows whose year record is equal to 1967 . the sum of the points record of these rows is 2 .
Output: yes
Command: round_eq { sum { filter_eq { all_rows ; year ; 1967 } ; points } ; 2 }, interpretation: the average of the goals record of all rows is 63.78 .
Output: no
Command: round_eq { avg { all_rows ; goals } ; 63.78 }, interpretation: the average of the goals record of all rows is 63.78 .
Output: yes
Command: round_eq { avg { all_rows ; goals } ; 63.78 }, interpretation: select the rows whose headquarters record fuzzily matches to united kingdom . the number of such rows is 2 .
Output: no
Command: eq { count { filter_eq { all_rows ; headquarters ; united kingdom } } ; 2 }, interpretation: select the rows whose headquarters record fuzzily matches to united kingdom . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_eq { all_rows ; headquarters ; united kingdom } } ; 2 }, interpretation: select the rows whose player record fuzzily matches to linden rowat ( g ) . take the round record of this row . select the rows whose player record fuzzily matches to dwight king ( c ) . take the round record of this row . the first record is 1 larger than the second record . the round record of the first row is 5 . the round record of the second row is 4 .
Output: no
Command: and { eq { diff { hop { filter_eq { all_rows ; player ; linden rowat ( g ) } ; round } ; hop { filter_eq { all_rows ; player ; dwight king ( c ) } ; round } } ; 1 } ; and { eq { hop { filter_eq { all_rows ; player ; linden rowat ( g ) } ; round } ; 5 } ; eq { hop { filter_eq { all_rows ; player ; dwight king ( c ) } ; round } ; 4 } } }, interpretation: select the rows whose player record fuzzily matches to linden rowat ( g ) . take the round record of this row . select the rows whose player record fuzzily matches to dwight king ( c ) . take the round record of this row . the first record is 1 larger than the second record . the round record of the first row is 5 . the round record of the second row is 4 .
Output: yes
Command: and { eq { diff { hop { filter_eq { all_rows ; player ; linden rowat ( g ) } ; round } ; hop { filter_eq { all_rows ; player ; dwight king ( c ) } ; round } } ; 1 } ; and { eq { hop { filter_eq { all_rows ; player ; linden rowat ( g ) } ; round } ; 5 } ; eq { hop { filter_eq { all_rows ; player ; dwight king ( c ) } ; round } ; 4 } } }, interpretation: select the row whose originalairdate record of all rows is 2nd minimum . the title record of this row is a bright and shiny future .
Output: no
Command: eq { hop { nth_argmin { all_rows ; originalairdate ; 2 } ; title } ; a bright and shiny future }, interpretation: select the row whose originalairdate record of all rows is 2nd minimum . the title record of this row is a bright and shiny future .
Output: yes
Command: eq { hop { nth_argmin { all_rows ; originalairdate ; 2 } ; title } ; a bright and shiny future }, interpretation: the average of the attendance record of all rows is 58252 .
Output: no
Command: round_eq { avg { all_rows ; attendance } ; 58252 }, interpretation: the average of the attendance record of all rows is 58252 .
Output: yes
Command: round_eq { avg { all_rows ; attendance } ; 58252 }, interpretation: select the row whose 1910 census record of all rows is 3rd maximum . the city record of this row is fuzan .
Output: no
Command: eq { hop { nth_argmax { all_rows ; 1910 census ; 3 } ; city } ; fuzan }, interpretation: select the row whose 1910 census record of all rows is 3rd maximum . the city record of this row is fuzan .
Output: yes
Command: eq { hop { nth_argmax { all_rows ; 1910 census ; 3 } ; city } ; fuzan }, interpretation: select the rows whose directed by record fuzzily matches to guy bee . there is only one such row in the table . the title record of this unqiue row is family matters .
Output: no
Command: and { only { filter_eq { all_rows ; directed by ; guy bee } } ; eq { hop { filter_eq { all_rows ; directed by ; guy bee } ; title } ; family matters } }, interpretation: select the rows whose directed by record fuzzily matches to guy bee . there is only one such row in the table . the title record of this unqiue row is family matters .
Output: yes
Command: and { only { filter_eq { all_rows ; directed by ; guy bee } } ; eq { hop { filter_eq { all_rows ; directed by ; guy bee } ; title } ; family matters } }, interpretation: select the rows whose location record fuzzily matches to japan . among these rows , select the rows whose res record fuzzily matches to win . the number of such rows is 3 .
Output: no
Command: eq { count { filter_eq { filter_eq { all_rows ; location ; japan } ; res ; win } } ; 3 }, interpretation: select the rows whose location record fuzzily matches to japan . among these rows , select the rows whose res record fuzzily matches to win . the number of such rows is 3 .
Output: yes
Command: eq { count { filter_eq { filter_eq { all_rows ; location ; japan } ; res ; win } } ; 3 }, interpretation: for the released records of all rows , most of them fuzzily match to 2012 .
Output: no
Command: most_eq { all_rows ; released ; 2012 }, interpretation: for the released records of all rows , most of them fuzzily match to 2012 .
Output: yes
Command: most_eq { all_rows ; released ; 2012 }, interpretation: select the rows whose player record fuzzily matches to fedor dmitriev . take the year born record of this row . select the rows whose player record fuzzily matches to anton ponkrashov . take the year born record of this row . the first record is less than the second record .
Output: no
Command: less { hop { filter_eq { all_rows ; player ; fedor dmitriev } ; year born } ; hop { filter_eq { all_rows ; player ; anton ponkrashov } ; year born } }, interpretation: select the rows whose player record fuzzily matches to fedor dmitriev . take the year born record of this row . select the rows whose player record fuzzily matches to anton ponkrashov . take the year born record of this row . the first record is less than the second record .
Output: yes
Command: less { hop { filter_eq { all_rows ; player ; fedor dmitriev } ; year born } ; hop { filter_eq { all_rows ; player ; anton ponkrashov } ; year born } }, interpretation: select the rows whose sport record fuzzily matches to soccer . take the 1st tournament record of this row . select the rows whose sport record fuzzily matches to bowling . take the 1st tournament record of this row . the first record is less than the second record .
Output: no
Command: less { hop { filter_eq { all_rows ; sport ; soccer } ; 1st tournament } ; hop { filter_eq { all_rows ; sport ; bowling } ; 1st tournament } }, interpretation: select the rows whose sport record fuzzily matches to soccer . take the 1st tournament record of this row . select the rows whose sport record fuzzily matches to bowling . take the 1st tournament record of this row . the first record is less than the second record .
Output: yes
Command: less { hop { filter_eq { all_rows ; sport ; soccer } ; 1st tournament } ; hop { filter_eq { all_rows ; sport ; bowling } ; 1st tournament } }, interpretation: select the rows whose season record fuzzily matches to 2005 . take the races record of this row . select the rows whose season record fuzzily matches to 2012 . take the races record of this row . the first record is greater than the second record .
Output: no
Command: greater { hop { filter_eq { all_rows ; season ; 2005 } ; races } ; hop { filter_eq { all_rows ; season ; 2012 } ; races } }, interpretation: select the rows whose season record fuzzily matches to 2005 . take the races record of this row . select the rows whose season record fuzzily matches to 2012 . take the races record of this row . the first record is greater than the second record .
Output: yes
Command: greater { hop { filter_eq { all_rows ; season ; 2005 } ; races } ; hop { filter_eq { all_rows ; season ; 2012 } ; races } }, interpretation: select the rows whose gold record is equal to - . the number of such rows is 2 .
Output: no
Command: eq { count { filter_eq { all_rows ; gold ; - } } ; 2 }, interpretation: select the rows whose gold record is equal to - . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_eq { all_rows ; gold ; - } } ; 2 }, interpretation: select the rows whose incumbent record fuzzily matches to edward everett eslick . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to gordon browning . take the first elected record of this row . the first record is greater than the second record .
Output: no
Command: greater { hop { filter_eq { all_rows ; incumbent ; edward everett eslick } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; gordon browning } ; first elected } }, interpretation: select the rows whose incumbent record fuzzily matches to edward everett eslick . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to gordon browning . take the first elected record of this row . the first record is greater than the second record .
Output: yes
Command: greater { hop { filter_eq { all_rows ; incumbent ; edward everett eslick } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; gordon browning } ; first elected } }, interpretation: select the rows whose host record fuzzily matches to jack arute . take the year record of this row . select the rows whose host record fuzzily matches to allen bestwick . take the year record of this row . the first record is less than the second record .
Output: no
Command: less { hop { filter_eq { all_rows ; host ; jack arute } ; year } ; hop { filter_eq { all_rows ; host ; allen bestwick } ; year } }, interpretation: select the rows whose host record fuzzily matches to jack arute . take the year record of this row . select the rows whose host record fuzzily matches to allen bestwick . take the year record of this row . the first record is less than the second record .
Output: yes
Command: less { hop { filter_eq { all_rows ; host ; jack arute } ; year } ; hop { filter_eq { all_rows ; host ; allen bestwick } ; year } }, interpretation: select the rows whose position record fuzzily matches to centre - left . the number of such rows is 2 .
Output: no
Command: eq { count { filter_eq { all_rows ; position ; centre - left } } ; 2 }, interpretation: select the rows whose position record fuzzily matches to centre - left . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_eq { all_rows ; position ; centre - left } } ; 2 }, interpretation: select the rows whose date record fuzzily matches to november . the number of such rows is 16 .
Output: no
Command: eq { count { filter_eq { all_rows ; date ; november } } ; 16 }, interpretation: select the rows whose date record fuzzily matches to november . the number of such rows is 16 .
Output: yes
Command: eq { count { filter_eq { all_rows ; date ; november } } ; 16 }, interpretation: select the rows whose matches record is greater than 200 . among these rows , select the rows whose innings record is greater than 250 . the number of such rows is 3 .
Output: no
Command: eq { count { filter_greater { filter_greater { all_rows ; matches ; 200 } ; innings ; 250 } } ; 3 }, interpretation: select the rows whose matches record is greater than 200 . among these rows , select the rows whose innings record is greater than 250 . the number of such rows is 3 .
Output: yes
Command: eq { count { filter_greater { filter_greater { all_rows ; matches ; 200 } ; innings ; 250 } } ; 3 }, interpretation: select the row whose uk viewers ( million ) record of all rows is 5th maximum . the title record of this row is episode 4 .
Output: no
Command: eq { hop { nth_argmax { all_rows ; uk viewers ( million ) ; 5 } ; title } ; episode 4 }, interpretation: select the row whose uk viewers ( million ) record of all rows is 5th maximum . the title record of this row is episode 4 .
Output: yes
Command: eq { hop { nth_argmax { all_rows ; uk viewers ( million ) ; 5 } ; title } ; episode 4 }, interpretation: select the rows whose name record fuzzily matches to robert childress . take the round record of this row . select the rows whose name record fuzzily matches to ivey armstrong . take the round record of this row . the first record is greater than the second record .
Output: no
Command: greater { hop { filter_eq { all_rows ; name ; robert childress } ; round } ; hop { filter_eq { all_rows ; name ; ivey armstrong } ; round } }, interpretation: select the rows whose name record fuzzily matches to robert childress . take the round record of this row . select the rows whose name record fuzzily matches to ivey armstrong . take the round record of this row . the first record is greater than the second record .
Output: yes
Command: greater { hop { filter_eq { all_rows ; name ; robert childress } ; round } ; hop { filter_eq { all_rows ; name ; ivey armstrong } ; round } }, interpretation: select the row whose crowd record of all rows is 1st maximum . the venue record of this row is lake oval .
Output: no
Command: eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; lake oval }, interpretation: select the row whose crowd record of all rows is 1st maximum . the venue record of this row is lake oval .
Output: yes
Command: eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; lake oval }, interpretation: select the row whose place record of all rows is minimum . the player record of this row is gary hallberg .
Output: no
Command: eq { hop { argmin { all_rows ; place } ; player } ; gary hallberg }, interpretation: select the row whose place record of all rows is minimum . the player record of this row is gary hallberg .
Output: yes
Command: eq { hop { argmin { all_rows ; place } ; player } ; gary hallberg }, interpretation: select the rows whose club record fuzzily matches to sporting de gijón . take the points record of this row . select the rows whose club record fuzzily matches to cádiz cf . take the points record of this row . the first record is greater than the second record .
Output: no
Command: greater { hop { filter_eq { all_rows ; club ; sporting de gijón } ; points } ; hop { filter_eq { all_rows ; club ; cádiz cf } ; points } }, interpretation: select the rows whose club record fuzzily matches to sporting de gijón . take the points record of this row . select the rows whose club record fuzzily matches to cádiz cf . take the points record of this row . the first record is greater than the second record .
Output: yes
Command: greater { hop { filter_eq { all_rows ; club ; sporting de gijón } ; points } ; hop { filter_eq { all_rows ; club ; cádiz cf } ; points } }, interpretation: for the party leader records of all rows , all of them fuzzily match to habib bourguiba .
Output: no
Command: all_eq { all_rows ; party leader ; habib bourguiba }, interpretation: for the party leader records of all rows , all of them fuzzily match to habib bourguiba .
Output: yes
Command: all_eq { all_rows ; party leader ; habib bourguiba }, interpretation: for the location records of all rows , most of them fuzzily match to busch stadium .
Output: no
Command: most_eq { all_rows ; location ; busch stadium }, interpretation: for the location records of all rows , most of them fuzzily match to busch stadium .
Output: yes
Command: most_eq { all_rows ; location ; busch stadium }, interpretation: select the rows whose club record fuzzily matches to ca osasuna . take the wins record of this row . select the rows whose club record fuzzily matches to real oviedo . take the wins record of this row . the first record is greater than the second record .
Output: no
Command: greater { hop { filter_eq { all_rows ; club ; ca osasuna } ; wins } ; hop { filter_eq { all_rows ; club ; real oviedo } ; wins } }, interpretation: select the rows whose club record fuzzily matches to ca osasuna . take the wins record of this row . select the rows whose club record fuzzily matches to real oviedo . take the wins record of this row . the first record is greater than the second record .
Output: yes
Command: greater { hop { filter_eq { all_rows ; club ; ca osasuna } ; wins } ; hop { filter_eq { all_rows ; club ; real oviedo } ; wins } }, interpretation: for the jockey records of all rows , most of them fuzzily match to c newitt .
Output: no
Command: most_eq { all_rows ; jockey ; c newitt }, interpretation: for the jockey records of all rows , most of them fuzzily match to c newitt .
Output: yes
Command: most_eq { all_rows ; jockey ; c newitt }, interpretation: select the rows whose opponent record fuzzily matches to dallas cowboys . the number of such rows is 2 .
Output: no
Command: eq { count { filter_eq { all_rows ; opponent ; dallas cowboys } } ; 2 }, interpretation: select the rows whose opponent record fuzzily matches to dallas cowboys . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_eq { all_rows ; opponent ; dallas cowboys } } ; 2 }, interpretation: select the rows whose position record fuzzily matches to wide receiver . the number of such rows is 2 .
Output: no
Command: eq { count { filter_eq { all_rows ; position ; wide receiver } } ; 2 }, interpretation: select the rows whose position record fuzzily matches to wide receiver . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_eq { all_rows ; position ; wide receiver } } ; 2 }, interpretation: for the laps records of all rows , most of them are equal to 47 .
Output: no
Command: most_eq { all_rows ; laps ; 47 }, interpretation: for the laps records of all rows , most of them are equal to 47 .
Output: yes
Command: most_eq { all_rows ; laps ; 47 }, interpretation: select the rows whose result record fuzzily matches to re - elected . the number of such rows is 6 .
Output: no
Command: eq { count { filter_eq { all_rows ; result ; re - elected } } ; 6 }, interpretation: select the rows whose result record fuzzily matches to re - elected . the number of such rows is 6 .
Output: yes
Command: eq { count { filter_eq { all_rows ; result ; re - elected } } ; 6 }, interpretation: select the rows whose lost record is equal to 3 . the number of such rows is 2 .
Output: no
Command: eq { count { filter_eq { all_rows ; lost ; 3 } } ; 2 }, interpretation: select the rows whose lost record is equal to 3 . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_eq { all_rows ; lost ; 3 } } ; 2 }, interpretation: select the rows whose power ( kw ) record fuzzily matches to 10 kw . among these rows , select the rows whose frequency record is greater than 100.0 . the number of such rows is 2 .
Output: no
Command: eq { count { filter_greater { filter_eq { all_rows ; power ( kw ) ; 10 kw } ; frequency ; 100.0 } } ; 2 }, interpretation: select the rows whose power ( kw ) record fuzzily matches to 10 kw . among these rows , select the rows whose frequency record is greater than 100.0 . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_greater { filter_eq { all_rows ; power ( kw ) ; 10 kw } ; frequency ; 100.0 } } ; 2 }, interpretation: select the rows whose player record fuzzily matches to chi chi rodriguez . take the wins record of this row . select the rows whose player record fuzzily matches to dave stockton . take the wins record of this row . the first record is greater than the second record .
Output: no
Command: greater { hop { filter_eq { all_rows ; player ; chi chi rodriguez } ; wins } ; hop { filter_eq { all_rows ; player ; dave stockton } ; wins } }, interpretation: select the rows whose player record fuzzily matches to chi chi rodriguez . take the wins record of this row . select the rows whose player record fuzzily matches to dave stockton . take the wins record of this row . the first record is greater than the second record .
Output: yes
Command: greater { hop { filter_eq { all_rows ; player ; chi chi rodriguez } ; wins } ; hop { filter_eq { all_rows ; player ; dave stockton } ; wins } }, interpretation: select the row whose attendance record of all rows is maximum . the opponent record of this row is buffalo bills .
Output: no
Command: eq { hop { argmax { all_rows ; attendance } ; opponent } ; buffalo bills }, interpretation: select the row whose attendance record of all rows is maximum . the opponent record of this row is buffalo bills .
Output: yes
Command: eq { hop { argmax { all_rows ; attendance } ; opponent } ; buffalo bills }, interpretation: select the rows whose nation record fuzzily matches to usa . the sum of the goals record of these rows is 74 .
Output: no
Command: round_eq { sum { filter_eq { all_rows ; nation ; usa } ; goals } ; 74 }, interpretation: select the rows whose nation record fuzzily matches to usa . the sum of the goals record of these rows is 74 .
Output: yes
Command: round_eq { sum { filter_eq { all_rows ; nation ; usa } ; goals } ; 74 }, interpretation: select the rows whose nation record is arbitrary . the number of such rows is 17 .
Output: no
Command: eq { count { filter_all { all_rows ; nation } } ; 17 }, interpretation: select the rows whose nation record is arbitrary . the number of such rows is 17 .
Output: yes
Command: eq { count { filter_all { all_rows ; nation } } ; 17 }, interpretation: select the rows whose original air date record fuzzily matches to february 2010 . the number of such rows is 3 .
Output: no
Command: eq { count { filter_eq { all_rows ; original air date ; february 2010 } } ; 3 }, interpretation: select the rows whose original air date record fuzzily matches to february 2010 . the number of such rows is 3 .
Output: yes
Command: eq { count { filter_eq { all_rows ; original air date ; february 2010 } } ; 3 }, interpretation: select the row whose scoring average record of all rows is minimum . the year record of this row is 2007 .
Output: no
Command: eq { hop { argmin { all_rows ; scoring average } ; year } ; 2007 }, interpretation: select the row whose scoring average record of all rows is minimum . the year record of this row is 2007 .
Output: yes
Command: eq { hop { argmin { all_rows ; scoring average } ; year } ; 2007 }, interpretation: select the rows whose laps record is equal to 46 . the number of such rows is 4 .
Output: no
Command: eq { count { filter_eq { all_rows ; laps ; 46 } } ; 4 }, interpretation: select the rows whose laps record is equal to 46 . the number of such rows is 4 .
Output: yes
Command: eq { count { filter_eq { all_rows ; laps ; 46 } } ; 4 }, interpretation: select the rows whose ceased to be consort record fuzzily matches to husband 's death . the number of such rows is 3 .
Output: no
Command: eq { count { filter_eq { all_rows ; ceased to be consort ; husband 's death } } ; 3 }, interpretation: select the rows whose ceased to be consort record fuzzily matches to husband 's death . the number of such rows is 3 .
Output: yes
Command: eq { count { filter_eq { all_rows ; ceased to be consort ; husband 's death } } ; 3 }, interpretation: select the rows whose team record fuzzily matches to tauro . take the goals scored record of this row . select the rows whose team record fuzzily matches to alianza . take the goals scored record of this row . the first record is greater than the second record .
Output: no
Command: greater { hop { filter_eq { all_rows ; team ; tauro } ; goals scored } ; hop { filter_eq { all_rows ; team ; alianza } ; goals scored } }, interpretation: select the rows whose team record fuzzily matches to tauro . take the goals scored record of this row . select the rows whose team record fuzzily matches to alianza . take the goals scored record of this row . the first record is greater than the second record .
Output: yes
Command: greater { hop { filter_eq { all_rows ; team ; tauro } ; goals scored } ; hop { filter_eq { all_rows ; team ; alianza } ; goals scored } }, interpretation: select the rows whose result record fuzzily matches to re - elected . among these rows , select the rows whose first elected record is equal to 1944 . the number of such rows is 2 .
Output: no
Command: eq { count { filter_eq { filter_eq { all_rows ; result ; re - elected } ; first elected ; 1944 } } ; 2 }, interpretation: select the rows whose result record fuzzily matches to re - elected . among these rows , select the rows whose first elected record is equal to 1944 . the number of such rows is 2 .
Output: yes
Command: eq { count { filter_eq { filter_eq { all_rows ; result ; re - elected } ; first elected ; 1944 } } ; 2 }, interpretation: for the wins records of all rows , most of them are greater than 10 .
Output: no
Command: most_greater { all_rows ; wins ; 10 }, interpretation: for the wins records of all rows , most of them are greater than 10 .
Output: yes