niryuu/sni-each-converted huggingface dataset:
eq { count { filter_eq { all_rows ; dominant religion ( 2002 ) ; catholic christianity } } ; 2 } = true
Output: select the rows whose dominant religion  2002  record fuzzily matches to catholic christianity . the number of such rows is 2 .
most_less { all_rows ; crowd ; 30000 } = true
Output: for the crowd records of all rows , most of them are less than 30000 .
and { only { filter_greater { all_rows ; us viewers ( millions ) ; 3.0 } } ; eq { hop { filter_greater { all_rows ; us viewers ( millions ) ; 3.0 } ; title } ; pilot } } = true
Output: select the rows whose us viewers  millions  record is greater than 3.0 . there is only one such row in the table . the title record of this unqiue row is pilot .
most_eq { all_rows ; winner ; dick johnson } = true
Output: for the winner records of all rows , most of them fuzzily match to dick johnson .
eq { hop { argmax { all_rows ; goals } ; season } ; 2009 - 10 } = true
Output: select the row whose goals record of all rows is maximum . the season record of this row is 2009  10 .
round_eq { sum { all_rows ; gold } ; 36 } = true
Output: the sum of the gold record of all rows is 36 .
eq { hop { nth_argmin { all_rows ; date ; 2 } ; winning driver } ; arthur duray } = true
Output: select the row whose date record of all rows is 2nd minimum . the winning driver record of this row is arthur duray .
and { only { filter_eq { all_rows ; tournament ; spain } } ; eq { hop { filter_eq { all_rows ; tournament ; spain } ; date } ; 11 february 2008 } } = true
Output: select the rows whose tournament record fuzzily matches to spain . there is only one such row in the table . the date record of this unqiue row is 11 february 2008 .
eq { count { filter_eq { all_rows ; city of license ; san antonio } } ; 4 } = true
Output: select the rows whose city of license record fuzzily matches to san antonio . the number of such rows is 4 .
greater { hop { filter_eq { all_rows ; club ; cd sabadell cf } ; wins } ; hop { filter_eq { all_rows ; club ; deportivo alavés } ; wins } } = true
Output: select the rows whose club record fuzzily matches to cd sabadell cf . take the wins record of this row . select the rows whose club record fuzzily matches to deportivo alavés . take the wins record of this row . the first record is greater than the second record .
eq { hop { argmax { all_rows ; rebs } ; player } ; alvan adams } = true
Output: select the row whose rebs record of all rows is maximum . the player record of this row is alvan adams .
eq { count { filter_all { all_rows ; rank } } ; 19 } = true
Output: select the rows whose rank record is arbitrary . the number of such rows is 19 .
round_eq { avg { all_rows ; result } ; 3rd place } = true
Output: the average of the result record of all rows is 3rd place .
eq { count { filter_eq { filter_greater_eq { all_rows ; points ; 55 } ; opponent ; new york rangers } } ; 2 } = true
Output: select the rows whose points record is greater than or equal to 55 . among these rows , select the rows whose opponent record fuzzily matches to new york rangers . the number of such rows is 2 .
eq { count { filter_eq { all_rows ; competition ; friendly } } ; 4 } = true
Output: select the rows whose competition record fuzzily matches to friendly . the number of such rows is 4 .
and { only { filter_eq { all_rows ; result ; new seat republican gain } } ; eq { hop { filter_eq { all_rows ; result ; new seat republican gain } ; first elected } ; none ( district created ) } } = true
Output: select the rows whose result record fuzzily matches to new seat republican gain . there is only one such row in the table . the first elected record of this unqiue row is none  district created  .
eq { hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent } ; john thomas wilson } = true
Output: select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is john thomas wilson .
only { filter_greater { all_rows ; laps ; 312 } } = true
Output: select the rows whose laps record is greater than 312 . there is only one such row in the table .
round_eq { sum { all_rows ; points } ; 19 } = true
Output: the sum of the points record of all rows is 19 .
eq { count { filter_not_eq { all_rows ; wins ; 0 } } ; 4 } = true
Output: select the rows whose wins record is not equal to 0 . the number of such rows is 4 .
less { hop { filter_eq { all_rows ; actress ; marlee matlin } ; year } ; hop { filter_eq { all_rows ; actress ; jessica tandy } ; year } } = true
Output: select the rows whose actress record fuzzily matches to marlee matlin . take the year record of this row . select the rows whose actress record fuzzily matches to jessica tandy . take the year record of this row . the first record is less than the second record .
eq { hop { nth_argmax { all_rows ; bronze ; 2 } ; nation } ; colombia } = true
Output: select the row whose bronze record of all rows is 2nd maximum . the nation record of this row is colombia .
eq { count { filter_greater { all_rows ; displacement cc ; 2000 } } ; 2 } = true
Output: select the rows whose displacement cc record is greater than 2000 . the number of such rows is 2 .
most_eq { all_rows ; tournament location ; beaver meadow golf course } = true
Output: for the tournament location records of all rows , most of them fuzzily match to beaver meadow golf course .
eq { hop { nth_argmax { all_rows ; points for ; 2 } ; team } ; bourgoin } = true
Output: select the row whose points for record of all rows is 2nd maximum . the team record of this row is bourgoin .
less { hop { filter_eq { all_rows ; name ; john e wool } ; appointment date } ; hop { filter_eq { all_rows ; name ; david e twiggs } ; appointment date } } = true
Output: select the rows whose name record fuzzily matches to john e wool . take the appointment date record of this row . select the rows whose name record fuzzily matches to david e twiggs . take the appointment date record of this row . the first record is less than the second record .
round_eq { sum { all_rows ; number of seasons in superettan } ; 76 } = true
Output: the sum of the number of seasons in superettan record of all rows is 76 .
and { only { filter_eq { all_rows ; serial number ; unknown } } ; eq { hop { filter_eq { all_rows ; serial number ; unknown } ; build date } ; october 1856 } } = true
Output: select the rows whose serial number record fuzzily matches to unknown . there is only one such row in the table . the build date record of this unqiue row is october 1856 .
greater { hop { filter_eq { all_rows ; building ; richcraft - dow honda site tower i } ; floors } ; hop { filter_eq { all_rows ; building ; claridge plaza iii } ; floors } } = true
Output: select the rows whose building record fuzzily matches to richcraft  dow honda site tower i . take the floors record of this row . select the rows whose building record fuzzily matches to claridge plaza iii . take the floors record of this row . the first record is greater than the second record .
round_eq { avg { all_rows ; weight } ; 88 } = true
Output: the average of the weight record of all rows is 88 .
eq { hop { nth_argmax { all_rows ; total points ; 2 } ; player } ; kenny sanders } = true
Output: select the row whose total points record of all rows is 2nd maximum . the player record of this row is kenny sanders .
and { only { filter_eq { all_rows ; wins ; 7 } } ; eq { hop { filter_eq { all_rows ; wins ; 7 } ; driver } ; sébastien loeb } } = true
Output: select the rows whose wins record is equal to 7 . there is only one such row in the table . the driver record of this unqiue row is sébastien loeb .
only { filter_eq { all_rows ; nationality ; alatri } } = true
Output: select the rows whose nationality record fuzzily matches to alatri . there is only one such row in the table .
eq { hop { argmax { all_rows ; points } ; artist } ; marlen angelidou } = true
Output: select the row whose points record of all rows is maximum . the artist record of this row is marlen angelidou .
greater { hop { filter_eq { all_rows ; song ; kiss me } ; weeks on top } ; hop { filter_eq { all_rows ; song ; smooth } ; weeks on top } } = true
Output: select the rows whose song record fuzzily matches to kiss me . take the weeks on top record of this row . select the rows whose song record fuzzily matches to smooth . take the weeks on top record of this row . the first record is greater than the second record .
most_eq { all_rows ; date of vacancy ; march 2011 } = true
Output: for the date of vacancy records of all rows , most of them fuzzily match to march 2011 .
round_eq { avg { all_rows ; frequency ( per hour ) } ; 3.11 } = true
Output: the average of the frequency  per hour  record of all rows is 3.11 .
and { only { filter_eq { all_rows ; name of the country ; serbia ( srb ) } } ; eq { hop { filter_eq { all_rows ; name of the country ; serbia ( srb ) } ; years in world group } ; 3 ( 2 - 3 ) } } = true
Output: select the rows whose name of the country record fuzzily matches to serbia  srb  . there is only one such row in the table . the years in world group record of this unqiue row is 3  2  3  .
greater { hop { filter_eq { all_rows ; date ; july 16 } ; location / attendance } ; hop { filter_eq { all_rows ; date ; july 18 } ; location / attendance } } = true
Output: select the rows whose date record fuzzily matches to july 16 . take the location  attendance record of this row . select the rows whose date record fuzzily matches to july 18 . take the location  attendance record of this row . the first record is greater than the second record .
eq { hop { nth_argmin { all_rows ; last aired ; 2 } ; show } ; high rollers } = true
Output: select the row whose last aired record of all rows is 2nd minimum . the show record of this row is high rollers .
round_eq { sum { all_rows ; inhabitants } ; 521,203 } = true
Output: the sum of the inhabitants record of all rows is 521,203 .
eq { count { filter_eq { filter_eq { all_rows ; opponent ; pittsburgh penguins } ; location / attendance ; consol energy center } } ; 2 } = true
Output: select the rows whose opponent record fuzzily matches to pittsburgh penguins . among these rows , select the rows whose location  attendance record fuzzily matches to consol energy center . the number of such rows is 2 .
eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; date } ; 8 december 1999 } = true
Output: select the row whose attendance record of all rows is 3rd maximum . the date record of this row is 8 december 1999 .
round_eq { sum { filter_eq { all_rows ; event ; wc beijing } ; rank points } ; 23 } = true
Output: select the rows whose event record fuzzily matches to wc beijing . the sum of the rank points record of these rows is 23 .
eq { count { filter_eq { all_rows ; date ; october } } ; 4 } = true
Output: select the rows whose date record fuzzily matches to october . the number of such rows is 4 .
eq { count { filter_eq { all_rows ; gold ; 0 } } ; 4 } = true
Output: select the rows whose gold record is equal to 0 . the number of such rows is 4 .
eq { hop { nth_argmax { all_rows ; total units sold ; 2 } ; title } ; wii fit } = true
Output: select the row whose total units sold record of all rows is 2nd maximum . the title record of this row is wii fit .
eq { hop { argmax { all_rows ; total } ; athlete } ; anastasia davydova & anastasiya yermakova } = true
Output: select the row whose total record of all rows is maximum . the athlete record of this row is anastasia davydova  anastasiya yermakova .
round_eq { sum { all_rows ; votes } ; 2176341 } = true
Output: the sum of the votes record of all rows is 2176341 .
and { only { filter_eq { all_rows ; result ; died in office } } ; eq { hop { filter_eq { all_rows ; result ; died in office } ; candidates } ; john james flynt , jr ( d ) unopposed } } = true
Output: select the rows whose result record fuzzily matches to died in office . there is only one such row in the table . the candidates record of this unqiue row is john james flynt , jr  d  unopposed .
round_eq { avg { all_rows ; attendance } ; 22526 } = true
Output: the average of the attendance record of all rows is 22526 .
greater { hop { filter_eq { all_rows ; title ; last life in the universe } ; singapore gross } ; hop { filter_eq { all_rows ; title ; clouds in my coffee } ; singapore gross } } = true
Output: select the rows whose title record fuzzily matches to last life in the universe . take the singapore gross record of this row . select the rows whose title record fuzzily matches to clouds in my coffee . take the singapore gross record of this row . the first record is greater than the second record .
less { hop { filter_eq { all_rows ; label ; columbia } ; date } ; hop { filter_eq { all_rows ; label ; legacy recordings } ; date } } = true
Output: select the rows whose label record fuzzily matches to columbia . take the date record of this row . select the rows whose label record fuzzily matches to legacy recordings . take the date record of this row . the first record is less than the second record .
less { hop { filter_eq { all_rows ; jyutping ; loeng2 } ; imperial value } ; hop { filter_eq { all_rows ; jyutping ; daam3 } ; imperial value } } = true
Output: select the rows whose jyutping record fuzzily matches to loeng2 . take the imperial value record of this row . select the rows whose jyutping record fuzzily matches to daam3 . take the imperial value record of this row . the first record is less than the second record .
eq { hop { argmax { all_rows ; caps } ; name } ; ronaldo } = true
Output: select the row whose caps record of all rows is maximum . the name record of this row is ronaldo .
eq { count { filter_eq { all_rows ; pole position ; ayrton senna } } ; 8 } = true
Output: select the rows whose pole position record fuzzily matches to ayrton senna . the number of such rows is 8 .
round_eq { avg { all_rows ; attendance } ; 56169 } = true
Output: the average of the attendance record of all rows is 56169 .
eq { hop { argmax { all_rows ; date successor seated } ; district } ; ohio 6th } = true
Output: select the row whose date successor seated record of all rows is maximum . the district record of this row is ohio 6th .
round_eq { avg { all_rows ; mccain % } ; 73.54 } = true
Output: the average of the mccain  record of all rows is 73.54 .
eq { hop { argmax { all_rows ; enrollment } ; location } ; mercer island } = true
Output: select the row whose enrollment record of all rows is maximum . the location record of this row is mercer island .
greater { hop { filter_eq { all_rows ; year ; 2006 details } ; player of the tournament } ; hop { filter_eq { all_rows ; year ; 2005 details } ; player of the tournament } } = true
Output: select the rows whose year record fuzzily matches to 2006 details . take the player of the tournament record of this row . select the rows whose year record fuzzily matches to 2005 details . take the player of the tournament record of this row . the first record is greater than the second record .
most_eq { all_rows ; us hot 100 ; - } = true
Output: for the us hot 100 records of all rows , most of them are equal to  .
eq { hop { argmax { filter_eq { all_rows ; round ; 1 } ; weight } ; player name } ; felix jones } = true
Output: select the rows whose round record is equal to 1 . select the row whose weight record of these rows is maximum . the player name record of this row is felix jones .
eq { count { filter_eq { all_rows ; shooter ; sergei pyzhianov } } ; 2 } = true
Output: select the rows whose shooter record fuzzily matches to sergei pyzhianov . the number of such rows is 2 .
most_greater { all_rows ; yards ; 20 } = true
Output: for the yards records of all rows , most of them are greater than 20 .
round_eq { avg { all_rows ; quantity } ; 25.14 } = true
Output: the average of the quantity record of all rows is 25.14 .
greater { hop { filter_eq { all_rows ; coach ; steve yoder } ; record } ; hop { filter_eq { all_rows ; coach ; bill cofield } ; record } } = true
Output: select the rows whose coach record fuzzily matches to steve yoder . take the record record of this row . select the rows whose coach record fuzzily matches to bill cofield . take the record record of this row . the first record is greater than the second record .
eq { hop { nth_argmax { filter_eq { all_rows ; trailing party ; bahujan samaj party } ; trailing party % votes ; 2 } ; year } ; 1998 } = true
Output: select the rows whose trailing party record fuzzily matches to bahujan samaj party . select the row whose trailing party  votes record of these rows is 2nd maximum . the year record of this row is 1998 .
round_eq { avg { all_rows ; time } ; 6:40.52 } = true
Output: the average of the time record of all rows is 6:40.52 .
eq { count { filter_eq { filter_eq { all_rows ; location / attendance ; the omni } ; score ; l } } ; 6 } = true
Output: select the rows whose location  attendance record fuzzily matches to the omni . among these rows , select the rows whose score record fuzzily matches to l . the number of such rows is 6 .
most_eq { all_rows ; visitor ; warriors } = true
Output: for the visitor records of all rows , most of them fuzzily match to warriors .
eq { hop { argmax { all_rows ; population } ; municipality } ; malmö } = true
Output: select the row whose population record of all rows is maximum . the municipality record of this row is malmö .
greater { hop { filter_eq { all_rows ; province ; suphan buri } ; bronze } ; hop { filter_eq { all_rows ; province ; nonthaburi } ; bronze } } = true
Output: select the rows whose province record fuzzily matches to suphan buri . take the bronze record of this row . select the rows whose province record fuzzily matches to nonthaburi . take the bronze record of this row . the first record is greater than the second record .
eq { count { filter_eq { all_rows ; location ; united states } } ; 7 } = true
Output: select the rows whose location record fuzzily matches to united states . the number of such rows is 7 .
eq { count { filter_eq { filter_eq { all_rows ; country ; england } ; score ; 71 } } ; 3 } = true
Output: select the rows whose country record fuzzily matches to england . among these rows , select the rows whose score record is equal to 71 . the number of such rows is 3 .
eq { hop { nth_argmax { all_rows ; commissioned ; 2 } ; name } ; chieftain } = true
Output: select the row whose commissioned record of all rows is 2nd maximum . the name record of this row is chieftain .
eq { hop { nth_argmin { all_rows ; original air date ; 1 } ; title } ; game on } = true
Output: select the row whose original air date record of all rows is 1st minimum . the title record of this row is game on .
eq { count { filter_eq { all_rows ; label ; bronze } } ; 4 } = true
Output: select the rows whose label record fuzzily matches to bronze . the number of such rows is 4 .
eq { count { filter_eq { filter_eq { all_rows ; directed by ; steve mann } ; written by ; john ridley } } ; 3 } = true
Output: select the rows whose directed by record fuzzily matches to steve mann . among these rows , select the rows whose written by record fuzzily matches to john ridley . the number of such rows is 3 .
less { hop { filter_eq { all_rows ; opponent ; philadelphia soul } ; date } ; hop { filter_eq { all_rows ; opponent ; georgia force } ; date } } = true
Output: select the rows whose opponent record fuzzily matches to philadelphia soul . take the date record of this row . select the rows whose opponent record fuzzily matches to georgia force . take the date record of this row . the first record is less than the second record .
eq { hop { argmax { all_rows ; apps } ; name } ; jürgen grabowski } = true
Output: select the row whose apps record of all rows is maximum . the name record of this row is jürgen grabowski .
eq { hop { argmax { all_rows ; gore % } ; county } ; clark } = true
Output: select the row whose gore  record of all rows is maximum . the county record of this row is clark .
eq { count { filter_all { all_rows ; nation } } ; 12 } = true
Output: select the rows whose nation record is arbitrary . the number of such rows is 12 .
less { hop { filter_eq { all_rows ; club ; swansea uplands rfc } ; tries for } ; hop { filter_eq { all_rows ; club ; trebanos rfc } ; tries for } } = true
Output: select the rows whose club record fuzzily matches to swansea uplands rfc . take the tries for record of this row . select the rows whose club record fuzzily matches to trebanos rfc . take the tries for record of this row . the first record is less than the second record .
round_eq { sum { all_rows ; assists } ; 54 } = true
Output: the sum of the assists record of all rows is 54 .
eq { count { filter_eq { all_rows ; last title ; ( none ) } } ; 7 } = true
Output: select the rows whose last title record fuzzily matches to  none  . the number of such rows is 7 .
round_eq { avg { all_rows ; capacity } ; 8561 } = true
Output: the average of the capacity record of all rows is 8561 .
less { hop { filter_eq { all_rows ; player ; wayne walker } ; overall pick } ; hop { filter_eq { all_rows ; player ; john yarno } ; overall pick } } = true
Output: select the rows whose player record fuzzily matches to wayne walker . take the overall pick record of this row . select the rows whose player record fuzzily matches to john yarno . take the overall pick record of this row . the first record is less than the second record .
eq { hop { argmax { all_rows ; total } ; player } ; hal sutton } = true
Output: select the row whose total record of all rows is maximum . the player record of this row is hal sutton .
less { hop { filter_eq { all_rows ; city of license ; stuart , florida } ; frequency mhz } ; hop { filter_eq { all_rows ; city of license ; tradition , florida } ; frequency mhz } } = true
Output: select the rows whose city of license record fuzzily matches to stuart , florida . take the frequency mhz record of this row . select the rows whose city of license record fuzzily matches to tradition , florida . take the frequency mhz record of this row . the first record is less than the second record .
eq { hop { nth_argmax { filter_greater { all_rows ; area ( km square ) ; 100 } ; population 2000 census ; 1 } ; administrative division } ; metropolitan rio janeiro } = true
Output: select the rows whose area  km square  record is greater than 100 . select the row whose population 2000 census record of these rows is 1st maximum . the administrative division record of this row is metropolitan rio janeiro .
most_eq { all_rows ; year joined ; 1962 } = true
Output: for the year joined records of all rows , most of them are equal to 1962 .
round_eq { avg { all_rows ; height } ; 2.01 } = true
Output: the average of the height record of all rows is 2.01 .
and { only { filter_eq { all_rows ; launcher ; saturn v } } ; eq { hop { filter_eq { all_rows ; launcher ; saturn v } ; flights } ; 10 lun / or } } = true
Output: select the rows whose launcher record fuzzily matches to saturn v . there is only one such row in the table . the flights record of this unqiue row is 10 lun  or .
most_eq { filter_eq { all_rows ; seasons at this level ; 27 seasons } ; settlements ; lisbon } = true
Output: select the rows whose seasons at this level record fuzzily matches to 27 seasons . for the settlements records of these rows , most of them fuzzily match to lisbon .
eq { count { filter_eq { all_rows ; points defending ; 0 } } ; 3 } = true
Output: select the rows whose points defending record is equal to 0 . the number of such rows is 3 .
eq { hop { argmin { all_rows ; pick } ; player } ; ed o'bannon } = true
Output: select the row whose pick record of all rows is minimum . the player record of this row is ed obannon .
and { only { filter_eq { all_rows ; country ; ch } } ; eq { hop { filter_eq { all_rows ; country ; ch } ; building } ; victoria hall } } = true
Output: select the rows whose country record fuzzily matches to ch . there is only one such row in the table . the building record of this unqiue row is victoria hall .
all_eq { all_rows ; city of license ; massachusetts } = true
Output: for the city of license records of all rows , all of them fuzzily match to massachusetts .
eq { hop { argmax { all_rows ; frequency } ; callsign } ; kgbt } = true
Output: select the row whose frequency record of all rows is maximum . the callsign record of this row is kgbt .
round_eq { avg { all_rows ; score } ; 3.25 } = true
Output: the average of the score record of all rows is 3.25 .
most_eq { all_rows ; environment ; open air } = true
Output: for the environment records of all rows , most of them fuzzily match to open air .
eq { hop { argmax { all_rows ; result } ; opponent } ; buffalo bills } = true
Output: select the row whose result record of all rows is maximum . the opponent record of this row is buffalo bills .
eq { hop { nth_argmax { all_rows ; points ; 2 } ; artist } ; sirusho } = true
Output: select the row whose points record of all rows is 2nd maximum . the artist record of this row is sirusho .
greater { hop { filter_eq { all_rows ; name ; marc willers ( nzl ) } ; 1st run } ; hop { filter_eq { all_rows ; name ; mike day ( usa ) } ; 1st run } } = true
Output: select the rows whose name record fuzzily matches to marc willers  nzl  . take the 1st run record of this row . select the rows whose name record fuzzily matches to mike day  usa  . take the 1st run record of this row . the first record is greater than the second record .
round_eq { avg { all_rows ; round } ; 2 } = true
Output: the average of the round record of all rows is 2 .
greater { hop { filter_eq { all_rows ; driver ; robby gordon } ; points } ; hop { filter_eq { all_rows ; driver ; jeff gordon } ; points } } = true
Output: select the rows whose driver record fuzzily matches to robby gordon . take the points record of this row . select the rows whose driver record fuzzily matches to jeff gordon . take the points record of this row . the first record is greater than the second record .
eq { count { filter_eq { filter_eq { all_rows ; nationality ; united states } ; college / junior / club team ( league ) ; university of notre dame } } ; 2 } = true
Output: select the rows whose nationality record fuzzily matches to united states . among these rows , select the rows whose college  junior  club team  league  record fuzzily matches to university of notre dame . the number of such rows is 2 .
eq { max { all_rows ; result } ; w 42 - 10 } = true
Output: the maximum result record of all rows is w 42  10 .
eq { count { filter_greater { all_rows ; silver ; 0 } } ; 5 } = true
Output: select the rows whose silver record is greater than 0 . the number of such rows is 5 .
round_eq { avg { all_rows ; crowd } ; 35000 } = true
Output: the average of the crowd record of all rows is 35000 .
round_eq { avg { all_rows ; sun devils points } ; 38.5 } = true
Output: the average of the sun devils points record of all rows is 38.5 .
eq { count { filter_eq { filter_eq { all_rows ; result ; re - elected } ; party ; republican } } ; 2 } = true
Output: select the rows whose result record fuzzily matches to re  elected . among these rows , select the rows whose party record fuzzily matches to republican . the number of such rows is 2 .
eq { hop { nth_argmin { all_rows ; year ; 1 } ; name } ; cathedral basilica of the immaculate conception } = true
Output: select the row whose year record of all rows is 1st minimum . the name record of this row is cathedral basilica of the immaculate conception .
and { only { filter_eq { all_rows ; school / club team ; brigham young university } } ; eq { hop { filter_eq { all_rows ; school / club team ; brigham young university } ; player } ; tevita ofahengaue } } = true
Output: select the rows whose school  club team record fuzzily matches to brigham young university . there is only one such row in the table . the player record of this unqiue row is tevita ofahengaue .
greater { hop { filter_eq { all_rows ; tracks ; that 's how the whole thing started } ; length } ; hop { filter_eq { all_rows ; tracks ; do what you do } ; length } } = true
Output: select the rows whose tracks record fuzzily matches to that s how the whole thing started . take the length record of this row . select the rows whose tracks record fuzzily matches to do what you do . take the length record of this row . the first record is greater than the second record .
eq { hop { nth_argmax { all_rows ; award ; 2 } ; film } ; mercy } = true
Output: select the row whose award record of all rows is 2nd maximum . the film record of this row is mercy .
eq { hop { argmax { all_rows ; total personnel } ; type of unit } ; heavy bombardment group } = true
Output: select the row whose total personnel record of all rows is maximum . the type of unit record of this row is heavy bombardment group .
and { only { filter_eq { all_rows ; built ; 12/1915 } } ; eq { hop { filter_eq { all_rows ; built ; 12/1915 } ; hr name } ; ( river garry ) } } = true
Output: select the rows whose built record fuzzily matches to 121915 . there is only one such row in the table . the hr name record of this unqiue row is  river garry  .
eq { hop { nth_argmin { all_rows ; time ; 3 } ; athlete } ; gabriella bascelli } = true
Output: select the row whose time record of all rows is 3rd minimum . the athlete record of this row is gabriella bascelli .
eq { count { filter_eq { all_rows ; high rebounds ; chris bosh } } ; 9 } = true
Output: select the rows whose high rebounds record fuzzily matches to chris bosh . the number of such rows is 9 .
eq { count { filter_eq { filter_eq { all_rows ; place ; t1 } ; country ; united states } } ; 6 } = true
Output: select the rows whose place record fuzzily matches to t1 . among these rows , select the rows whose country record fuzzily matches to united states . the number of such rows is 6 .
eq { count { filter_eq { all_rows ; engine ; offy } } ; 4 } = true
Output: select the rows whose engine record fuzzily matches to offy . the number of such rows is 4 .
most_eq { all_rows ; where built ; marshfield } = true
Output: for the where built records of all rows , most of them fuzzily match to marshfield .
and { only { filter_eq { all_rows ; pole position ; chris goodwin andrew kirkaldy } } ; eq { hop { filter_eq { all_rows ; pole position ; chris goodwin andrew kirkaldy } ; round } ; 5 } } = true
Output: select the rows whose pole position record fuzzily matches to chris goodwin andrew kirkaldy . there is only one such row in the table . the round record of this unqiue row is 5 .
and { only { filter_eq { all_rows ; format ; digital download } } ; eq { hop { filter_eq { all_rows ; format ; digital download } ; record company } ; deutsche grammophon } } = true
Output: select the rows whose format record fuzzily matches to digital download . there is only one such row in the table . the record company record of this unqiue row is deutsche grammophon .
most_eq { all_rows ; engine ; offenhauser l4 } = true
Output: for the engine records of all rows , most of them fuzzily match to offenhauser l4 .
most_eq { all_rows ; batting style ; right-handed } = true
Output: for the batting style records of all rows , most of them fuzzily match to righthanded .
eq { count { filter_eq { all_rows ; date ; march 1981 } } ; 7 } = true
Output: select the rows whose date record fuzzily matches to march 1981 . the number of such rows is 7 .
less { hop { filter_eq { all_rows ; season ; 9 } ; viewers ( in millions ) } ; hop { filter_eq { all_rows ; season ; 4 } ; viewers ( in millions ) } } = true
Output: select the rows whose season record fuzzily matches to 9 . take the viewers  in millions  record of this row . select the rows whose season record fuzzily matches to 4 . take the viewers  in millions  record of this row . the first record is less than the second record .
eq { count { filter_eq { all_rows ; candidates ; unopposed } } ; 17 } = true
Output: select the rows whose candidates record fuzzily matches to unopposed . the number of such rows is 17 .
eq { hop { nth_argmin { all_rows ; time ; 2 } ; country } ; czech republic } = true
Output: select the row whose time record of all rows is 2nd minimum . the country record of this row is czech republic .
most_eq { all_rows ; headquarters ; sweden } = true
Output: for the headquarters records of all rows , most of them fuzzily match to sweden .
round_eq { avg { filter_less_eq { all_rows ; date ; september 15 2001 } ; distance } ; 1300 } = true
Output: select the rows whose date record is less than or equal to september 15 2001 . the average of the distance record of these rows is 1300 .
eq { count { filter_eq { all_rows ; year withdrawn ; 1936 } } ; 2 } = true
Output: select the rows whose year withdrawn record is equal to 1936 . the number of such rows is 2 .
eq { hop { nth_argmin { filter_eq { all_rows ; candidates ; unopposed } ; first elected ; 1 } ; incumbent } ; john h kerr } = true
Output: select the rows whose candidates record fuzzily matches to unopposed . select the row whose first elected record of these rows is 1st minimum . the incumbent record of this row is john h kerr .
less { hop { filter_eq { all_rows ; episode title ; new york } ; original airdate } ; hop { filter_eq { all_rows ; episode title ; beneath vesuvius } ; original airdate } } = true
Output: select the rows whose episode title record fuzzily matches to new york . take the original airdate record of this row . select the rows whose episode title record fuzzily matches to beneath vesuvius . take the original airdate record of this row . the first record is less than the second record .
most_eq { filter_eq { all_rows ; date ; december } ; final score ; w } = true
Output: select the rows whose date record fuzzily matches to december . for the final score records of these rows , most of them fuzzily match to w .
eq { diff { hop { filter_eq { all_rows ; name ; jeff thomson } ; matches } ; hop { filter_eq { all_rows ; name ; mitchell johnson } ; matches } } ; 1 } = true
Output: select the rows whose name record fuzzily matches to jeff thomson . take the matches record of this row . select the rows whose name record fuzzily matches to mitchell johnson . take the matches record of this row . the first record is 1 larger than the second record .
round_eq { avg { all_rows ; pos } ; 14.33 } = true
Output: the average of the pos record of all rows is 14.33 .
eq { count { filter_eq { filter_eq { all_rows ; wins ; 5 } ; losses ; 4 } } ; 2 } = true
Output: select the rows whose wins record is equal to 5 . among these rows , select the rows whose losses record is equal to 4 . the number of such rows is 2 .
round_eq { avg { all_rows ; number of viewers } ; 28.94 } = true
Output: the average of the number of viewers record of all rows is 28.94 .
round_eq { avg { all_rows ; population ( 2011 ) } ; 29547 } = true
Output: the average of the population  2011  record of all rows is 29547 .
and { only { filter_eq { all_rows ; year ; 2002 } } ; eq { hop { filter_eq { all_rows ; year ; 2002 } ; event } ; ozzfest 2002 } } = true
Output: select the rows whose year record is equal to 2002 . there is only one such row in the table . the event record of this unqiue row is ozzfest 2002 .
most_less { all_rows ; best ; 59.999 } = true
Output: for the best records of all rows , most of them are less than 59.999 .
eq { count { filter_eq { all_rows ; height ; 6 - 2 } } ; 3 } = true
Output: select the rows whose height record fuzzily matches to 6  2 . the number of such rows is 3 .
greater { hop { filter_eq { all_rows ; player ; lionel cann } ; runs } ; hop { filter_eq { all_rows ; player ; dean minors } ; runs } } = true
Output: select the rows whose player record fuzzily matches to lionel cann . take the runs record of this row . select the rows whose player record fuzzily matches to dean minors . take the runs record of this row . the first record is greater than the second record .
round_eq { sum { all_rows ; time } ; 15:41 } = true
Output: the sum of the time record of all rows is 15:41 .
eq { count { filter_eq { filter_eq { all_rows ; label ; alfa records } ; format ; cd } } ; 4 } = true
Output: select the rows whose label record fuzzily matches to alfa records . among these rows , select the rows whose format record fuzzily matches to cd . the number of such rows is 4 .
round_eq { avg { all_rows ; score } ; 145 } = true
Output: the average of the score record of all rows is 145 .
and { only { filter_eq { all_rows ; commanding officer ; n/a } } ; eq { hop { filter_eq { all_rows ; commanding officer ; n/a } ; parent unit } ; jagdgeschwader 54 } } = true
Output: select the rows whose commanding officer record fuzzily matches to na . there is only one such row in the table . the parent unit record of this unqiue row is jagdgeschwader 54 .
eq { hop { nth_argmin { all_rows ; became queen ; 2 } ; name } ; maria teresa of the two sicilies } = true
Output: select the row whose became queen record of all rows is 2nd minimum . the name record of this row is maria teresa of the two sicilies .
eq { count { filter_eq { all_rows ; winning driver ; klaus ludwig } } ; 2 } = true
Output: select the rows whose winning driver record fuzzily matches to klaus ludwig . the number of such rows is 2 .
all_greater { filter_eq { all_rows ; away team ; south melbourne } ; crowd ; 20000 } = true
Output: select the rows whose away team record fuzzily matches to south melbourne . for the crowd records of these rows , all of them are greater than 20000 .
and { less { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; hop { filter_eq { all_rows ; team ; jardim américa } ; played } } ; and { eq { hop { filter_eq { all_rows ; team ; sírio libanês } ; played } ; 12 } ; eq { hop { filter_eq { all_rows ; team ; jardim américa } ; played } ; 13 } } } = true
Output: select the rows whose team record fuzzily matches to sírio libanês . take the played record of this row . select the rows whose team record fuzzily matches to jardim américa . take the played record of this row . the first record is less than the second record . the played record of the first row is 12 . the played record of the second row is 13 .
round_eq { avg { all_rows ; total } ; 284.5 } = true
Output: the average of the total record of all rows is 284.5 .
eq { hop { argmin { all_rows ; growth rate } ; district } ; kolkata } = true
Output: select the row whose growth rate record of all rows is minimum . the district record of this row is kolkata .
and { only { filter_eq { all_rows ; mascot ; scorpion } } ; eq { hop { filter_eq { all_rows ; mascot ; scorpion } ; elementary schools } ; san tan ( home ) } } = true
Output: select the rows whose mascot record fuzzily matches to scorpion . there is only one such row in the table . the elementary schools record of this unqiue row is san tan  home  .
less { hop { filter_eq { all_rows ; location ; houston , texas } ; date } ; hop { filter_eq { all_rows ; location ; zapopan , jalisco } ; date } } = true
Output: select the rows whose location record fuzzily matches to houston , texas . take the date record of this row . select the rows whose location record fuzzily matches to zapopan , jalisco . take the date record of this row . the first record is less than the second record .
eq { hop { argmin { all_rows ; distance ( km ) } ; station } ; kawarada } = true
Output: select the row whose distance  km  record of all rows is minimum . the station record of this row is kawarada .
and { only { filter_eq { all_rows ; venue ; lake oval } } ; eq { hop { filter_eq { all_rows ; venue ; lake oval } ; home team } ; south melbourne } } = true
Output: select the rows whose venue record fuzzily matches to lake oval . there is only one such row in the table . the home team record of this unqiue row is south melbourne .
eq { hop { argmax { all_rows ; gold } ; nation } ; great britain } = true
Output: select the row whose gold record of all rows is maximum . the nation record of this row is great britain .
most_eq { all_rows ; clock speed ( mhz ) ; 8 } = true
Output: for the clock speed  mhz  records of all rows , most of them are equal to 8 .
eq { count { filter_eq { all_rows ; director ; chuck jones } } ; 7 } = true
Output: select the rows whose director record fuzzily matches to chuck jones . the number of such rows is 7 .
most_eq { all_rows ; manner ; sacked } = true
Output: for the manner records of all rows , most of them fuzzily match to sacked .
eq { count { filter_eq { all_rows ; venue ; candlestick park } } ; 3 } = true
Output: select the rows whose venue record fuzzily matches to candlestick park . the number of such rows is 3 .
most_eq { all_rows ; played ; 22 } = true
Output: for the played records of all rows , most of them are equal to 22 .
greater { hop { filter_eq { all_rows ; home team ; richmond } ; crowd } ; hop { filter_eq { all_rows ; home team ; geelong } ; crowd } } = true
Output: select the rows whose home team record fuzzily matches to richmond . take the crowd record of this row . select the rows whose home team record fuzzily matches to geelong . take the crowd record of this row . the first record is greater than the second record .
and { eq { nth_max { all_rows ; revenue in usd ; 2 } ; 469.2 billion } ; eq { hop { nth_argmax { all_rows ; revenue in usd ; 2 } ; company } ; walmart } } = true
Output: the 2nd maximum revenue in usd record of all rows is 469.2 billion . the company record of the row with 2nd maximum revenue in usd record is walmart .
and { only { filter_less { all_rows ; episodes ; 40 } } ; eq { hop { filter_less { all_rows ; episodes ; 40 } ; season no } ; 1 } } = true
Output: select the rows whose episodes record is less than 40 . there is only one such row in the table . the season no record of this unqiue row is 1 .
round_eq { sum { all_rows ; crowd } ; 86100 } = true
Output: the sum of the crowd record of all rows is 86100 .
eq { count { filter_eq { all_rows ; written by ; james wood } } ; 5 } = true
Output: select the rows whose written by record fuzzily matches to james wood . the number of such rows is 5 .
eq { hop { nth_argmax { all_rows ; attendance ; 4 } ; round } ; 1st round - 1st leg } = true
Output: select the row whose attendance record of all rows is 4th maximum . the round record of this row is 1st round  1st leg .
and { only { filter_eq { all_rows ; venue ; greece } } ; eq { hop { filter_eq { all_rows ; venue ; greece } ; competition } ; world athletics final } } = true
Output: select the rows whose venue record fuzzily matches to greece . there is only one such row in the table . the competition record of this unqiue row is world athletics final .
and { only { filter_eq { all_rows ; pilot ; and } } ; eq { hop { filter_eq { all_rows ; pilot ; and } ; vehicle } ; schempp - hirth nimbus - 4dm } } = true
Output: select the rows whose pilot record fuzzily matches to and . there is only one such row in the table . the vehicle record of this unqiue row is schempp  hirth nimbus  4dm .
eq { count { filter_less { filter_eq { all_rows ; date ; january } ; crowd ; 4000 } } ; 3 } = true
Output: select the rows whose date record fuzzily matches to january . among these rows , select the rows whose crowd record is less than 4000 . the number of such rows is 3 .
and { only { filter_less { all_rows ; polyunsaturated fat ; 10 % } } ; eq { hop { filter_less { all_rows ; polyunsaturated fat ; 10 % } ; } ; suet } } = true
Output: select the rows whose polyunsaturated fat record is less than 10  . there is only one such row in the table . the record of this unqiue row is suet .
eq { hop { argmax { filter_greater { all_rows ; home team score ; 10 } ; crowd } ; venue } ; victoria park } = true
Output: select the rows whose home team score record is greater than 10 . select the row whose crowd record of these rows is maximum . the venue record of this row is victoria park .
most_eq { all_rows ; country ; canada } = true
Output: for the country records of all rows , most of them fuzzily match to canada .
greater { hop { filter_eq { all_rows ; animal name ; the rabbits } ; tv seasons } ; hop { filter_eq { all_rows ; animal name ; mole } ; tv seasons } } = true
Output: select the rows whose animal name record fuzzily matches to the rabbits . take the tv seasons record of this row . select the rows whose animal name record fuzzily matches to mole . take the tv seasons record of this row . the first record is greater than the second record .
eq { hop { argmax { all_rows ; points } ; driver } ; will power } = true
Output: select the row whose points record of all rows is maximum . the driver record of this row is will power .
round_eq { sum { all_rows ; aggregate } ; 20-39 } = true
Output: the sum of the aggregate record of all rows is 2039 .
and { only { filter_eq { all_rows ; wins ; 18 } } ; eq { hop { filter_eq { all_rows ; wins ; 18 } ; driver } ; daniël willemsen } } = true
Output: select the rows whose wins record is equal to 18 . there is only one such row in the table . the driver record of this unqiue row is daniël willemsen .
round_eq { avg { all_rows ; installed capacity ( mw ) } ; 116.56 } = true
Output: the average of the installed capacity  mw  record of all rows is 116.56 .
eq { count { filter_eq { all_rows ; leading scorer ; tim duncan } } ; 7 } = true
Output: select the rows whose leading scorer record fuzzily matches to tim duncan . the number of such rows is 7 .
only { filter_greater { all_rows ; home team score ; 20 } } = true
Output: select the rows whose home team score record is greater than 20 . there is only one such row in the table .
eq { hop { nth_argmin { all_rows ; opened ; 2 } ; name } ; the shock wave } = true
Output: select the row whose opened record of all rows is 2nd minimum . the name record of this row is the shock wave .
most_eq { all_rows ; tournament ; us } = true
Output: for the tournament records of all rows , most of them fuzzily match to us .
round_eq { avg { all_rows ; enrollment } ; 1259.8 } = true
Output: the average of the enrollment record of all rows is 1259.8 .
all_eq { all_rows ; year ; 2003 } = true
Output: for the year records of all rows , all of them are equal to 2003 .
and { only { filter_eq { filter_eq { all_rows ; location attendance ; air canada centre } ; team ; dallas } } ; eq { hop { filter_eq { filter_eq { all_rows ; location attendance ; air canada centre } ; team ; dallas } ; date } ; february 6 } } = true
Output: select the rows whose location attendance record fuzzily matches to air canada centre . among these rows , select the rows whose team record fuzzily matches to dallas . there is only one such row in the table . the date record of this unqiue row is february 6 .
eq { hop { argmax { all_rows ; raiders points } ; date } ; nov 9 } = true
Output: select the row whose raiders points record of all rows is maximum . the date record of this row is nov 9 .
and { only { filter_eq { filter_less { all_rows ; elevation ( m ) ; 3000 } ; col ( m ) ; 0 } } ; eq { hop { filter_eq { filter_less { all_rows ; elevation ( m ) ; 3000 } ; col ( m ) ; 0 } ; peak } ; mount ruapehu } } = true
Output: select the rows whose elevation  m  record is less than 3000 . among these rows , select the rows whose col  m  record is equal to 0 . there is only one such row in the table . the peak record of this unqiue row is mount ruapehu .
eq { hop { nth_argmax { all_rows ; election year ; 2 } ; winning party / coalition } ; all india anna dravida munnetra kazhagam } = true
Output: select the row whose election year record of all rows is 2nd maximum . the winning party  coalition record of this row is all india anna dravida munnetra kazhagam .
most_eq { all_rows ; notes ; french } = true
Output: for the notes records of all rows , most of them fuzzily match to french .
eq { hop { argmax { all_rows ; us viewers ( millions ) } ; title } ; bea stays in the picture } = true
Output: select the row whose us viewers  millions  record of all rows is maximum . the title record of this row is bea stays in the picture .
and { eq { max { filter_eq { all_rows ; game site ; mile high stadium } ; attendance } ; 74970 } ; eq { hop { argmax { filter_eq { all_rows ; game site ; mile high stadium } ; attendance } ; date } ; sep 21 } } = true
Output: select the rows whose game site record fuzzily matches to mile high stadium . the maximum attendance record of these rows is 74970 . the date record of the row with superlative attendance record is sep 21 .
eq { hop { nth_argmax { all_rows ; us viewers ( millions ) ; 2 } ; no in season } ; 8 } = true
Output: select the row whose us viewers  millions  record of all rows is 2nd maximum . the no in season record of this row is 8 .
eq { min { filter_eq { all_rows ; country ; estonia } ; time } ; 6:27.95 } = true
Output: select the rows whose country record fuzzily matches to estonia . the minimum time record of these rows is 6:27.95 .