niryuu/sni-each-converted huggingface dataset:
and { only { filter_eq { filter_eq { all_rows ; director ; hollingsworth morse } ; writer ( s ) ; george eckstein } } ; eq { hop { filter_eq { filter_eq { all_rows ; director ; hollingsworth morse } ; writer ( s ) ; george eckstein } ; title } ; huck of la mancha } } = true
Output: select the rows whose director record fuzzily matches to hollingsworth morse . among these rows , select the rows whose writer  s  record fuzzily matches to george eckstein . there is only one such row in the table . the title record of this unqiue row is huck of la mancha .
eq { hop { nth_argmax { all_rows ; number of seasons in top division ; 3 } ; club } ; atlante } = true
Output: select the row whose number of seasons in top division record of all rows is 3rd maximum . the club record of this row is atlante .
eq { hop { argmax { all_rows ; top - 10 } ; tournament } ; us open } = true
Output: select the row whose top  10 record of all rows is maximum . the tournament record of this row is us open .
eq { hop { argmin { filter_eq { all_rows ; constructor ; ferrari } ; time / retired } ; driver } ; rubens barrichello } = true
Output: select the rows whose constructor record fuzzily matches to ferrari . select the row whose time  retired record of these rows is minimum . the driver record of this row is rubens barrichello .
and { only { filter_eq { all_rows ; competition ; friendly } } ; eq { hop { filter_eq { all_rows ; competition ; friendly } ; date } ; 15 august 2012 } } = true
Output: select the rows whose competition record fuzzily matches to friendly . there is only one such row in the table . the date record of this unqiue row is 15 august 2012 .
eq { count { filter_greater { filter_eq { all_rows ; locomotive type ; steam } ; withdrawn ; 1969 } } ; 2 } = true
Output: select the rows whose locomotive type record fuzzily matches to steam . among these rows , select the rows whose withdrawn record is greater than 1969 . the number of such rows is 2 .
eq { count { filter_greater { all_rows ; erp / power w ; 5000 } } ; 3 } = true
Output: select the rows whose erp  power w record is greater than 5000 . the number of such rows is 3 .
most_greater_eq { all_rows ; 1st week sales ; 200000 } = true
Output: for the 1st week sales records of all rows , most of them are greater than or equal to 200000 .
eq { count { filter_greater { all_rows ; points ; 0 } } ; 2 } = true
Output: select the rows whose points record is greater than 0 . the number of such rows is 2 .
eq { hop { argmin { all_rows ; first elected } ; incumbent } ; jim kolbe } = true
Output: select the row whose first elected record of all rows is minimum . the incumbent record of this row is jim kolbe .
and { only { filter_eq { all_rows ; date ; - } } ; eq { hop { filter_eq { all_rows ; date ; - } ; week } ; 9 } } = true
Output: select the rows whose date record is equal to  . there is only one such row in the table . the week record of this unqiue row is 9 .
eq { count { filter_eq { all_rows ; to par ; +5 } } ; 3 } = true
Output: select the rows whose to par record fuzzily matches to +5 . the number of such rows is 3 .
eq { hop { nth_argmax { all_rows ; win % ; 1 } ; opposition } ; pune warriors india } = true
Output: select the row whose win  record of all rows is 1st maximum . the opposition record of this row is pune warriors india .
eq { hop { nth_argmin { all_rows ; year ; 4 } ; song title } ; hrudayam ekkadunnadi } = true
Output: select the row whose year record of all rows is 4th minimum . the song title record of this row is hrudayam ekkadunnadi .
greater { hop { filter_eq { all_rows ; branding ; radio victoria } ; frequency } ; hop { filter_eq { all_rows ; branding ; kool fm } ; frequency } } = true
Output: select the rows whose branding record fuzzily matches to radio victoria . take the frequency record of this row . select the rows whose branding record fuzzily matches to kool fm . take the frequency record of this row . the first record is greater than the second record .
eq { hop { argmax { all_rows ; points against } ; opponent } ; port adelaide } = true
Output: select the row whose points against record of all rows is maximum . the opponent record of this row is port adelaide .
eq { count { filter_eq { all_rows ; niederbayern ; fc passau } } ; 4 } = true
Output: select the rows whose niederbayern record fuzzily matches to fc passau . the number of such rows is 4 .
all_eq { all_rows ; venue ; national stadium , tokyo , tokyo } = true
Output: for the venue records of all rows , all of them fuzzily match to national stadium , tokyo , tokyo .
eq { count { filter_eq { filter_greater { all_rows ; capacity ; 30000 } ; stadium ; stadio giuseppe meazza } } ; 2 } = true
Output: select the rows whose capacity record is greater than 30000 . among these rows , select the rows whose stadium record fuzzily matches to stadio giuseppe meazza . the number of such rows is 2 .
and { only { filter_eq { all_rows ; release date ; august } } ; eq { hop { filter_eq { all_rows ; release date ; august } ; song } ; here it comes } } = true
Output: select the rows whose release date record fuzzily matches to august . there is only one such row in the table . the song record of this unqiue row is here it comes .
eq { count { filter_eq { all_rows ; round winner ; glenn seton } } ; 4 } = true
Output: select the rows whose round winner record fuzzily matches to glenn seton . the number of such rows is 4 .
and { eq { hop { nth_argmin { all_rows ; date ; 3 } ; venue } ; victoria park } ; eq { hop { nth_argmin { all_rows ; date ; 3 } ; crowd } ; 23000 } } = true
Output: select the row whose date record of all rows is 3rd minimum . the venue record of this row is victoria park . the crowd record of this row is 23000 .
eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; home } ; montreal } = true
Output: select the row whose attendance record of all rows is 1st maximum . the home record of this row is montreal .
and { only { filter_greater { all_rows ; us viewers ( million ) ; 12 } } ; eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 12 } ; title } ; the transformation } } = true
Output: select the rows whose us viewers  million  record is greater than 12 . there is only one such row in the table . the title record of this unqiue row is the transformation .
eq { count { filter_all { all_rows ; nation } } ; 6 } = true
Output: select the rows whose nation record is arbitrary . the number of such rows is 6 .
eq { hop { nth_argmax { all_rows ; date ; 2 } ; tournament } ; moscow } = true
Output: select the row whose date record of all rows is 2nd maximum . the tournament record of this row is moscow .
and { only { filter_eq { filter_eq { all_rows ; location ; china } ; authors ; yuan } } ; eq { hop { filter_eq { filter_eq { all_rows ; location ; china } ; authors ; yuan } ; name } ; didactylornis } } = true
Output: select the rows whose location record fuzzily matches to china . among these rows , select the rows whose authors record fuzzily matches to yuan . there is only one such row in the table . the name record of this unqiue row is didactylornis .
and { only { filter_eq { all_rows ; opponent ; philadelphia eagles } } ; eq { hop { filter_eq { all_rows ; opponent ; philadelphia eagles } ; week } ; 1 } } = true
Output: select the rows whose opponent record fuzzily matches to philadelphia eagles . there is only one such row in the table . the week record of this unqiue row is 1 .
eq { min { filter_eq { all_rows ; result ; w } ; date } ; september 13 } = true
Output: select the rows whose result record fuzzily matches to w . the minimum date record of these rows is september 13 .
greater { hop { filter_eq { all_rows ; official name ; blackville } ; area km 2 } ; hop { filter_eq { all_rows ; official name ; rogersville } ; area km 2 } } = true
Output: select the rows whose official name record fuzzily matches to blackville . take the area km 2 record of this row . select the rows whose official name record fuzzily matches to rogersville . take the area km 2 record of this row . the first record is greater than the second record .
less { hop { filter_eq { all_rows ; incumbent ; jimmy duncan jr } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; zach wamp } ; first elected } } = true
Output: select the rows whose incumbent record fuzzily matches to jimmy duncan jr . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to zach wamp . take the first elected record of this row . the first record is less than the second record .
and { only { filter_eq { all_rows ; opponent in the final ; adriano panatta } } ; eq { hop { filter_eq { all_rows ; opponent in the final ; adriano panatta } ; championship } ; bologna , italy } } = true
Output: select the rows whose opponent in the final record fuzzily matches to adriano panatta . there is only one such row in the table . the championship record of this unqiue row is bologna , italy .
eq { count { filter_eq { all_rows ; album ; lost souls } } ; 3 } = true
Output: select the rows whose album record fuzzily matches to lost souls . the number of such rows is 3 .
eq { hop { argmax { all_rows ; population , in thousands , ( 1905 ) } ; governorate } ; warsaw governorate } = true
Output: select the row whose population , in thousands ,  1905  record of all rows is maximum . the governorate record of this row is warsaw governorate .
most_greater { all_rows ; aircraft movements ; 100 } = true
Output: for the aircraft movements records of all rows , most of them are greater than 100 .
all_eq { all_rows ; points ; 0 } = true
Output: for the points records of all rows , all of them are equal to 0 .
round_eq { avg { all_rows ; position } ; 13.56 } = true
Output: the average of the position record of all rows is 13.56 .
eq { max { filter_eq { all_rows ; venue ; western oval } ; crowd } ; 7000 } = true
Output: select the rows whose venue record fuzzily matches to western oval . the maximum crowd record of these rows is 7000 .
eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent } ; martin sabo } = true
Output: select the row whose first elected record of all rows is 2nd minimum . the incumbent record of this row is martin sabo .
eq { hop { argmax { all_rows ; w } ; skip ( club ) } ; brad gushue ( bally haly ) } = true
Output: select the row whose w record of all rows is maximum . the skip  club  record of this row is brad gushue  bally haly  .
most_greater { all_rows ; laps ; 60 } = true
Output: for the laps records of all rows , most of them are greater than 60 .
greater { hop { filter_eq { all_rows ; opponent ; troy nelson } ; round } ; hop { filter_eq { all_rows ; opponent ; shelton barnes } ; round } } = true
Output: select the rows whose opponent record fuzzily matches to troy nelson . take the round record of this row . select the rows whose opponent record fuzzily matches to shelton barnes . take the round record of this row . the first record is greater than the second record .
eq { hop { argmax { all_rows ; points } ; game } ; 10 } = true
Output: select the row whose points record of all rows is maximum . the game record of this row is 10 .
and { only { filter_eq { all_rows ; result ; 5-0 } } ; eq { hop { filter_eq { all_rows ; result ; 5-0 } ; winner } ; kiveton park } } = true
Output: select the rows whose result record fuzzily matches to 50 . there is only one such row in the table . the winner record of this unqiue row is kiveton park .
eq { count { filter_greater { filter_less { all_rows ; home team score ; 10.0 } ; crowd ; 16000 } } ; 2 } = true
Output: select the rows whose home team score record is less than 10.0 . among these rows , select the rows whose crowd record is greater than 16000 . the number of such rows is 2 .
and { only { filter_eq { all_rows ; founding university ; barnard college } } ; eq { hop { filter_eq { all_rows ; founding university ; barnard college } ; organization } ; alpha epsilon phi 2 } } = true
Output: select the rows whose founding university record fuzzily matches to barnard college . there is only one such row in the table . the organization record of this unqiue row is alpha epsilon phi 2 .
and { eq { hop { argmax { all_rows ; agg } ; team 1 } ; matera ( h15 ) } ; eq { hop { argmax { all_rows ; agg } ; team 2 } ; ( h14 ) quarto } } = true
Output: select the row whose agg record of all rows is maximum . the team 1 record of this row is matera  h15  . the team 2 record of this row is  h14  quarto .
eq { count { filter_eq { all_rows ; directed by ; patrick duffy } } ; 8 } = true
Output: select the rows whose directed by record fuzzily matches to patrick duffy . the number of such rows is 8 .
and { only { filter_eq { all_rows ; elimination move ; pinfall after a diving headbutt } } ; eq { hop { filter_eq { all_rows ; elimination move ; pinfall after a diving headbutt } ; wrestler } ; zach gowen } } = true
Output: select the rows whose elimination move record fuzzily matches to pinfall after a diving headbutt . there is only one such row in the table . the wrestler record of this unqiue row is zach gowen .
round_eq { avg { all_rows ; points ( pts ) } ; 24.6 } = true
Output: the average of the points  pts  record of all rows is 24.6 .
and { eq { nth_min { all_rows ; no ; 14 } ; 14 } ; and { eq { hop { nth_argmin { all_rows ; no ; 14 } ; date } ; 18 mar 2012 } ; eq { hop { nth_argmin { all_rows ; no ; 14 } ; winners share } ; 225000 } } } = true
Output: the 14th minimum no record of all rows is 14 . the date record of the row with 14th minimum no record is 18 mar 2012 . the winners share record of the row with 14th minimum no record is 225000 .
eq { count { filter_greater { filter_eq { all_rows ; game site ; shea stadium } ; attendance ; 63000 } } ; 4 } = true
Output: select the rows whose game site record fuzzily matches to shea stadium . among these rows , select the rows whose attendance record is greater than 63000 . the number of such rows is 4 .
less { hop { filter_eq { all_rows ; name ; john childress } ; overall } ; hop { filter_eq { all_rows ; name ; claude crabb } ; overall } } = true
Output: select the rows whose name record fuzzily matches to john childress . take the overall record of this row . select the rows whose name record fuzzily matches to claude crabb . take the overall record of this row . the first record is less than the second record .
eq { hop { argmin { filter_eq { all_rows ; position ; guard } ; years in orlando } ; player } ; todd lichti } = true
Output: select the rows whose position record fuzzily matches to guard . select the row whose years in orlando record of these rows is minimum . the player record of this row is todd lichti .
eq { hop { argmin { all_rows ; elected } ; incumbent } ; john lewis } = true
Output: select the row whose elected record of all rows is minimum . the incumbent record of this row is john lewis .
eq { count { filter_eq { all_rows ; navy ; lithuanian naval force } } ; 2 } = true
Output: select the rows whose navy record fuzzily matches to lithuanian naval force . the number of such rows is 2 .
and { only { filter_eq { all_rows ; place ; 1st } } ; eq { hop { filter_eq { all_rows ; place ; 1st } ; date } ; 7 dec 2008 } } = true
Output: select the rows whose place record fuzzily matches to 1st . there is only one such row in the table . the date record of this unqiue row is 7 dec 2008 .
and { only { filter_eq { all_rows ; gold ; 6 } } ; eq { hop { filter_eq { all_rows ; gold ; 6 } ; nation } ; united states } } = true
Output: select the rows whose gold record is equal to 6 . there is only one such row in the table . the nation record of this unqiue row is united states .
and { only { filter_eq { all_rows ; christians ; 41 % } } ; eq { hop { filter_eq { all_rows ; christians ; 41 % } ; ethnic group } ; kunama } } = true
Output: select the rows whose christians record fuzzily matches to 41  . there is only one such row in the table . the ethnic group record of this unqiue row is kunama .
eq { count { filter_greater { filter_eq { all_rows ; country ; united states } ; money ; 52000 } } ; 3 } = true
Output: select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose money record is greater than 52000 . the number of such rows is 3 .
eq { hop { argmax { all_rows ; vote percentage } ; player } ; hamit altıntop } = true
Output: select the row whose vote percentage record of all rows is maximum . the player record of this row is hamit altıntop .
eq { count { filter_eq { all_rows ; written by ; davey holmes } } ; 2 } = true
Output: select the rows whose written by record fuzzily matches to davey holmes . the number of such rows is 2 .
eq { hop { argmax { all_rows ; points for } ; club } ; betws rfc } = true
Output: select the row whose points for record of all rows is maximum . the club record of this row is betws rfc .
eq { count { filter_eq { all_rows ; position ; cornerback } } ; 2 } = true
Output: select the rows whose position record fuzzily matches to cornerback . the number of such rows is 2 .
eq { hop { argmax { all_rows ; erp w } ; call sign } ; k211ch } = true
Output: select the row whose erp w record of all rows is maximum . the call sign record of this row is k211ch .
most_eq { all_rows ; wheels ; 4 - 4 - 2t } = true
Output: for the wheels records of all rows , most of them fuzzily match to 4  4  2t .
eq { count { filter_eq { all_rows ; years ; 1 - 8 } } ; 2 } = true
Output: select the rows whose years record fuzzily matches to 1  8 . the number of such rows is 2 .
eq { count { filter_eq { all_rows ; paul mccartney ; acoustic guitar } } ; 2 } = true
Output: select the rows whose paul mccartney record fuzzily matches to acoustic guitar . the number of such rows is 2 .
eq { count { filter_eq { all_rows ; opponent ; baltimore ravens } } ; 2 } = true
Output: select the rows whose opponent record fuzzily matches to baltimore ravens . the number of such rows is 2 .
most_eq { all_rows ; high points ; jalen rose } = true
Output: for the high points records of all rows , most of them fuzzily match to jalen rose .
all_eq { all_rows ; ihsaa class ; aaa } = true
Output: for the ihsaa class records of all rows , all of them fuzzily match to aaa .
greater { hop { filter_eq { all_rows ; team 1 ; as saint - étienne ( d1 ) } ; score } ; hop { filter_eq { all_rows ; team 1 ; girondins de bordeaux ( d1 ) } ; score } } = true
Output: select the rows whose team 1 record fuzzily matches to as saint  étienne  d1  . take the score record of this row . select the rows whose team 1 record fuzzily matches to girondins de bordeaux  d1  . take the score record of this row . the first record is greater than the second record .
round_eq { avg { all_rows ; weight } ; 250.5 } = true
Output: the average of the weight record of all rows is 250.5 .
eq { count { filter_greater { all_rows ; games ; 30 } } ; 3 } = true
Output: select the rows whose games record is greater than 30 . the number of such rows is 3 .
round_eq { avg { all_rows ; top speed ( in operation ) （ km / h ） } ; 106.33 } = true
Output: the average of the top speed  in operation  （ km  h ） record of all rows is 106.33 .
less { hop { filter_eq { all_rows ; rider ; wattie brown } ; time } ; hop { filter_eq { all_rows ; rider ; chris swallow } ; time } } = true
Output: select the rows whose rider record fuzzily matches to wattie brown . take the time record of this row . select the rows whose rider record fuzzily matches to chris swallow . take the time record of this row . the first record is less than the second record .
and { only { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; lost } } ; eq { hop { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; lost } ; incumbent } ; dan crane } } = true
Output: select the rows whose party record fuzzily matches to republican . among these rows , select the rows whose result record fuzzily matches to lost . there is only one such row in the table . the incumbent record of this unqiue row is dan crane .
most_eq { filter_eq { all_rows ; date ; december } ; result ; l } = true
Output: select the rows whose date record fuzzily matches to december . for the result records of these rows , most of them fuzzily match to l .
and { only { filter_eq { all_rows ; school / club team ; georgia tech } } ; eq { hop { filter_eq { all_rows ; school / club team ; georgia tech } ; player } ; matt harpring } } = true
Output: select the rows whose school  club team record fuzzily matches to georgia tech . there is only one such row in the table . the player record of this unqiue row is matt harpring .
most_eq { all_rows ; result ; re-elected } = true
Output: for the result records of all rows , most of them fuzzily match to reelected .
and { less { hop { filter_eq { all_rows ; date ; may 5 } ; location attendance } ; hop { filter_eq { all_rows ; date ; may 8 } ; location attendance } } ; and { eq { hop { filter_eq { all_rows ; date ; may 5 } ; location attendance } ; new orleans arena 17927 } ; eq { hop { filter_eq { all_rows ; date ; may 8 } ; location attendance } ; at & t center 18797 } } } = true
Output: select the rows whose date record fuzzily matches to may 5 . take the location attendance record of this row . select the rows whose date record fuzzily matches to may 8 . take the location attendance record of this row . the first record is less than the second record . the location attendance record of the first row is new orleans arena 17927 . the location attendance record of the second row is at  t center 18797 .
all_eq { all_rows ; highest rank ; maegashira } = true
Output: for the highest rank records of all rows , all of them fuzzily match to maegashira .
round_eq { avg { filter_eq { all_rows ; team ; rhein fire } ; capacity } ; 56308 } = true
Output: select the rows whose team record fuzzily matches to rhein fire . the average of the capacity record of these rows is 56308 .
eq { hop { nth_argmin { all_rows ; price ; 2 } ; internet plan } ; internet 30 } = true
Output: select the row whose price record of all rows is 2nd minimum . the internet plan record of this row is internet 30 .
and { only { filter_eq { all_rows ; emperor 's cup ; semi - final } } ; eq { hop { filter_eq { all_rows ; emperor 's cup ; semi - final } ; season } ; 2000 } } = true
Output: select the rows whose emperor s cup record fuzzily matches to semi  final . there is only one such row in the table . the season record of this unqiue row is 2000 .
eq { hop { nth_argmin { all_rows ; oilers points ; 3 } ; date } ; oct 29 } = true
Output: select the row whose oilers points record of all rows is 3rd minimum . the date record of this row is oct 29 .
and { only { filter_eq { all_rows ; date of vacancy ; 21 december 2010 } } ; eq { hop { filter_eq { all_rows ; date of vacancy ; 21 december 2010 } ; outgoing head coach } ; jorge costa } } = true
Output: select the rows whose date of vacancy record fuzzily matches to 21 december 2010 . there is only one such row in the table . the outgoing head coach record of this unqiue row is jorge costa .
eq { hop { argmax { all_rows ; attendance } ; game site } ; commerzbank - arena } = true
Output: select the row whose attendance record of all rows is maximum . the game site record of this row is commerzbank  arena .
eq { count { filter_eq { all_rows ; first elected ; 1824 } } ; 3 } = true
Output: select the rows whose first elected record is equal to 1824 . the number of such rows is 3 .
eq { count { filter_eq { all_rows ; writer ; sally malcolm } } ; 4 } = true
Output: select the rows whose writer record fuzzily matches to sally malcolm . the number of such rows is 4 .
eq { hop { argmax { all_rows ; earnings } ; year } ; 2013 } = true
Output: select the row whose earnings record of all rows is maximum . the year record of this row is 2013 .
most_eq { all_rows ; competition ; 1908 olympics } = true
Output: for the competition records of all rows , most of them fuzzily match to 1908 olympics .
most_greater { filter_greater_eq { all_rows ; home team score ; 11 } ; crowd ; 10000 } = true
Output: select the rows whose home team score record is greater than or equal to 11 . for the crowd records of these rows , most of them are greater than 10000 .
greater { hop { filter_eq { all_rows ; rider ; john hopkins } ; laps } ; hop { filter_eq { all_rows ; rider ; marco melandri } ; laps } } = true
Output: select the rows whose rider record fuzzily matches to john hopkins . take the laps record of this row . select the rows whose rider record fuzzily matches to marco melandri . take the laps record of this row . the first record is greater than the second record .
round_eq { sum { all_rows ; pts } ; 23 } = true
Output: the sum of the pts record of all rows is 23 .
greater { hop { filter_eq { all_rows ; opponent ; lee hasdell } ; round } ; hop { filter_eq { all_rows ; opponent ; zabir elbiev } ; round } } = true
Output: select the rows whose opponent record fuzzily matches to lee hasdell . take the round record of this row . select the rows whose opponent record fuzzily matches to zabir elbiev . take the round record of this row . the first record is greater than the second record .
eq { count { filter_eq { all_rows ; county ; marshall } } ; 2 } = true
Output: select the rows whose county record fuzzily matches to marshall . the number of such rows is 2 .
most_eq { all_rows ; partnering ; ken flach } = true
Output: for the partnering records of all rows , most of them fuzzily match to ken flach .
eq { count { filter_eq { all_rows ; position ; point guard } } ; 2 } = true
Output: select the rows whose position record fuzzily matches to point guard . the number of such rows is 2 .
eq { hop { nth_argmin { filter_eq { all_rows ; sp ; 10 / 1 } ; position ; 1 } ; jockey } ; richard johnson } = true
Output: select the rows whose sp record fuzzily matches to 10  1 . select the row whose position record of these rows is 1st minimum . the jockey record of this row is richard johnson .
and { only { filter_eq { all_rows ; margin of victory ; 4 strokes } } ; eq { hop { filter_eq { all_rows ; margin of victory ; 4 strokes } ; tournament } ; barclays scottish open } } = true
Output: select the rows whose margin of victory record fuzzily matches to 4 strokes . there is only one such row in the table . the tournament record of this unqiue row is barclays scottish open .
and { only { filter_eq { all_rows ; reason for change ; to enter the us army } } ; eq { hop { filter_eq { all_rows ; reason for change ; to enter the us army } ; vacator } ; charles i faddis ( d ) } } = true
Output: select the rows whose reason for change record fuzzily matches to to enter the us army . there is only one such row in the table . the vacator record of this unqiue row is charles i faddis  d  .
round_eq { avg { all_rows ; gold } ; 1 } = true
Output: the average of the gold record of all rows is 1 .
most_greater { filter_eq { all_rows ; summary ; runners - up } ; wins ; 10 } = true
Output: select the rows whose summary record fuzzily matches to runners  up . for the wins records of these rows , most of them are greater than 10 .
eq { hop { nth_argmax { all_rows ; frequency ; 3 } ; callsign } ; xeas } = true
Output: select the row whose frequency record of all rows is 3rd maximum . the callsign record of this row is xeas .
and { only { filter_eq { filter_eq { all_rows ; location ; nijmegen } ; traction type ; electric } } ; eq { hop { filter_eq { filter_eq { all_rows ; location ; nijmegen } ; traction type ; electric } ; date ( from ) } ; 4 june 1911 } } = true
Output: select the rows whose location record fuzzily matches to nijmegen . among these rows , select the rows whose traction type record fuzzily matches to electric . there is only one such row in the table . the date  from  record of this unqiue row is 4 june 1911 .
eq { hop { nth_argmax { all_rows ; date of vacancy ; 2 } ; team } ; coventry city } = true
Output: select the row whose date of vacancy record of all rows is 2nd maximum . the team record of this row is coventry city .
eq { hop { nth_argmax { filter_greater { all_rows ; population ; 4000 } ; area km 2 ; 1 } ; official name } ; douglas } = true
Output: select the rows whose population record is greater than 4000 . select the row whose area km 2 record of these rows is 1st maximum . the official name record of this row is douglas .
all_eq { all_rows ; type ; private } = true
Output: for the type records of all rows , all of them fuzzily match to private .
most_eq { all_rows ; high rebounds ; greg monroe } = true
Output: for the high rebounds records of all rows , most of them fuzzily match to greg monroe .
less { hop { filter_eq { all_rows ; venue ; bursa atatürk stadium } ; capacity } ; hop { filter_eq { all_rows ; venue ; şükrü saracoğlu stadium } ; capacity } } = true
Output: select the rows whose venue record fuzzily matches to bursa atatürk stadium . take the capacity record of this row . select the rows whose venue record fuzzily matches to şükrü saracoğlu stadium . take the capacity record of this row . the first record is less than the second record .
most_eq { all_rows ; season premiere ; september } = true
Output: for the season premiere records of all rows , most of them fuzzily match to september .
and { eq { max { all_rows ; length } ; 9:00 } ; eq { hop { argmax { all_rows ; length } ; version } ; uk remix } } = true
Output: the maximum length record of all rows is 9:00 . the version record of the row with superlative length record is uk remix .
eq { hop { argmax { all_rows ; high rebounds } ; date } ; december 11 } = true
Output: select the row whose high rebounds record of all rows is maximum . the date record of this row is december 11 .
most_eq { all_rows ; high assists ; lebron james } = true
Output: for the high assists records of all rows , most of them fuzzily match to lebron james .
round_eq { avg { all_rows ; away team score } ; 11.36 } = true
Output: the average of the away team score record of all rows is 11.36 .
less { hop { filter_eq { all_rows ; title ; the chipmunk adventure } ; year } ; hop { filter_eq { all_rows ; title ; alvin and the chipmunks meet the wolfman } ; year } } = true
Output: select the rows whose title record fuzzily matches to the chipmunk adventure . take the year record of this row . select the rows whose title record fuzzily matches to alvin and the chipmunks meet the wolfman . take the year record of this row . the first record is less than the second record .
eq { hop { nth_argmax { all_rows ; average ; 2 } ; team } ; boca juniors } = true
Output: select the row whose average record of all rows is 2nd maximum . the team record of this row is boca juniors .
eq { hop { nth_argmin { all_rows ; rank ; 4 } ; rowers } ; zsolt hirling , tamã ¡ s varga } = true
Output: select the row whose rank record of all rows is 4th minimum . the rowers record of this row is zsolt hirling , tamã ¡ s varga .
eq { hop { nth_argmin { filter_less_eq { all_rows ; year ; 1978 } ; year ; 1 } ; place } ; cairo } = true
Output: select the rows whose year record is less than or equal to 1978 . select the row whose year record of these rows is 1st minimum . the place record of this row is cairo .
and { only { filter_eq { all_rows ; indian scorers ; own goal } } ; eq { hop { filter_eq { all_rows ; indian scorers ; own goal } ; date } ; 23 june 2011 } } = true
Output: select the rows whose indian scorers record fuzzily matches to own goal . there is only one such row in the table . the date record of this unqiue row is 23 june 2011 .
most_greater { all_rows ; date ; 1980 } = true
Output: for the date records of all rows , most of them are greater than 1980 .
eq { hop { argmin { all_rows ; place } ; player } ; chris dimarco } = true
Output: select the row whose place record of all rows is minimum . the player record of this row is chris dimarco .
eq { hop { argmax { all_rows ; upstream rate } ; version } ; adsl2 + + } = true
Output: select the row whose upstream rate record of all rows is maximum . the version record of this row is adsl2 + + .
and { only { filter_eq { all_rows ; method ; tko } } ; eq { hop { filter_eq { all_rows ; method ; tko } ; opponent } ; gegard mousasi } } = true
Output: select the rows whose method record fuzzily matches to tko . there is only one such row in the table . the opponent record of this unqiue row is gegard mousasi .
eq { count { filter_eq { all_rows ; directed by ; mel damski } } ; 4 } = true
Output: select the rows whose directed by record fuzzily matches to mel damski . the number of such rows is 4 .
eq { hop { argmax { all_rows ; first broadcast } ; episode } ; 3x08 } = true
Output: select the row whose first broadcast record of all rows is maximum . the episode record of this row is 3x08 .
eq { hop { nth_argmax { all_rows ; goals ; 2 } ; nationality } ; ireland } = true
Output: select the row whose goals record of all rows is 2nd maximum . the nationality record of this row is ireland .
round_eq { avg { all_rows ; earnings } ; 11647073 } = true
Output: the average of the earnings record of all rows is 11647073 .
eq { hop { nth_argmax { all_rows ; total ; 2 } ; nation } ; netherlands } = true
Output: select the row whose total record of all rows is 2nd maximum . the nation record of this row is netherlands .
eq { count { filter_eq { all_rows ; place ; 3rd } } ; 5 } = true
Output: select the rows whose place record fuzzily matches to 3rd . the number of such rows is 5 .
most_less_eq { all_rows ; score ; 3 } = true
Output: for the score records of all rows , most of them are less than or equal to 3 .
and { only { filter_greater { filter_eq { all_rows ; venue ; away } ; attendance ; 10000 } } ; eq { hop { filter_greater { filter_eq { all_rows ; venue ; away } ; attendance ; 10000 } ; date } ; 19 january 1988 } } = true
Output: select the rows whose venue record fuzzily matches to away . among these rows , select the rows whose attendance record is greater than 10000 . there is only one such row in the table . the date record of this unqiue row is 19 january 1988 .
eq { count { filter_eq { all_rows ; result ; w } } ; 8 } = true
Output: select the rows whose result record fuzzily matches to w . the number of such rows is 8 .
eq { count { filter_greater { all_rows ; position ; 0 } } ; 6 } = true
Output: select the rows whose position record is greater than 0 . the number of such rows is 6 .
most_eq { all_rows ; total fat ; 100 } = true
Output: for the total fat records of all rows , most of them are equal to 100 .
eq { hop { argmin { all_rows ; place } ; player } ; billy casper } = true
Output: select the row whose place record of all rows is minimum . the player record of this row is billy casper .
most_greater { all_rows ; attendance ; 70000 } = true
Output: for the attendance records of all rows , most of them are greater than 70000 .
eq { hop { argmax { all_rows ; result } ; venue } ; estádio campo desportivo , macau } = true
Output: select the row whose result record of all rows is maximum . the venue record of this row is estádio campo desportivo , macau .
eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; finis j garrett } = true
Output: select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is finis j garrett .
eq { hop { nth_argmax { all_rows ; total ; 2 } ; athlete } ; andrea fuentes & gemma mengual } = true
Output: select the row whose total record of all rows is 2nd maximum . the athlete record of this row is andrea fuentes  gemma mengual .
greater { hop { filter_eq { all_rows ; date ; october 15 } ; time } ; hop { filter_eq { all_rows ; date ; october 12 } ; time } } = true
Output: select the rows whose date record fuzzily matches to october 15 . take the time record of this row . select the rows whose date record fuzzily matches to october 12 . take the time record of this row . the first record is greater than the second record .
eq { count { filter_eq { all_rows ; result ; re-elected } } ; 6 } = true
Output: select the rows whose result record fuzzily matches to reelected . the number of such rows is 6 .
all_eq { all_rows ; introduction ; 12 december 1928 } = true
Output: for the introduction records of all rows , all of them fuzzily match to 12 december 1928 .
most_greater { all_rows ; overall ; 100 } = true
Output: for the overall records of all rows , most of them are greater than 100 .
and { eq { hop { argmax { all_rows ; attendance } ; date } ; april 8 } ; and { eq { hop { argmax { all_rows ; attendance } ; visitor } ; los angeles lakers } ; eq { hop { argmax { all_rows ; attendance } ; home } ; portland trail blazers } } } = true
Output: select the row whose attendance record of all rows is maximum . the date record of this row is april 8 . the visitor record of this row is los angeles lakers . the home record of this row is portland trail blazers .
eq { hop { nth_argmax { all_rows ; number of crews ; 2 } ; type of unit } ; troop carrier group } = true
Output: select the row whose number of crews record of all rows is 2nd maximum . the type of unit record of this row is troop carrier group .
eq { hop { argmax { all_rows ; area ( hectares ) } ; municipality } ; caramoran } = true
Output: select the row whose area  hectares  record of all rows is maximum . the municipality record of this row is caramoran .
eq { count { filter_eq { filter_eq { all_rows ; result ; re - elected } ; first elected ; 1944 } } ; 2 } = true
Output: 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 .
round_eq { avg { filter_eq { all_rows ; high points ; nolan } ; high points } ; 25.25 } = true
Output: select the rows whose high points record fuzzily matches to nolan . the average of the high points record of these rows is 25.25 .
eq { hop { argmax { all_rows ; money } ; place } ; 1 } = true
Output: select the row whose money record of all rows is maximum . the place record of this row is 1 .
eq { count { filter_eq { all_rows ; winner ; billy casper } } ; 3 } = true
Output: select the rows whose winner record fuzzily matches to billy casper . the number of such rows is 3 .
eq { hop { argmax { all_rows ; winnings } ; year } ; 1994 } = true
Output: select the row whose winnings record of all rows is maximum . the year record of this row is 1994 .
round_eq { avg { all_rows ; time } ; 5.603 } = true
Output: the average of the time record of all rows is 5.603 .
less { hop { filter_eq { all_rows ; club ( city / town ) ; hankook verdes united ( san ignacio ) } ; goals for / against } ; hop { filter_eq { all_rows ; club ( city / town ) ; fc belize ( belize city ) } ; goals for / against } } = true
Output: select the rows whose club  city  town  record fuzzily matches to hankook verdes united  san ignacio  . take the goals for  against record of this row . select the rows whose club  city  town  record fuzzily matches to fc belize  belize city  . take the goals for  against record of this row . the first record is less than the second record .
eq { hop { argmin { all_rows ; time } ; name } ; tyson gay } = true
Output: select the row whose time record of all rows is minimum . the name record of this row is tyson gay .
eq { hop { argmax { all_rows ; date of commissioning } ; unit number } ; 8 } = true
Output: select the row whose date of commissioning record of all rows is maximum . the unit number record of this row is 8 .
eq { count { filter_eq { all_rows ; outcome ; winner } } ; 4 } = true
Output: select the rows whose outcome record fuzzily matches to winner . the number of such rows is 4 .
most_eq { all_rows ; competition ; uefa intertoto cup } = true
Output: for the competition records of all rows , most of them fuzzily match to uefa intertoto cup .
eq { count { filter_eq { all_rows ; party ; labour party } } ; 3 } = true
Output: select the rows whose party record fuzzily matches to labour party . the number of such rows is 3 .
eq { count { filter_eq { all_rows ; decision ; joseph } } ; 4 } = true
Output: select the rows whose decision record fuzzily matches to joseph . the number of such rows is 4 .
eq { count { filter_eq { all_rows ; home / away ; home } } ; 8 } = true
Output: select the rows whose home  away record fuzzily matches to home . the number of such rows is 8 .
eq { count { filter_eq { all_rows ; score ; 0 } } ; 2 } = true
Output: select the rows whose score record fuzzily matches to 0 . the number of such rows is 2 .
eq { count { filter_eq { all_rows ; year joined ; 1956 } } ; 4 } = true
Output: select the rows whose year joined record is equal to 1956 . the number of such rows is 4 .
eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; brunswick street oval } = true
Output: select the row whose crowd record of all rows is 1st maximum . the venue record of this row is brunswick street oval .
most_eq { all_rows ; games ; 5 } = true
Output: for the games records of all rows , most of them are equal to 5 .
less { hop { filter_eq { all_rows ; athlete ; shawn crawford } ; result } ; hop { filter_eq { all_rows ; athlete ; kevin little } ; result } } = true
Output: select the rows whose athlete record fuzzily matches to shawn crawford . take the result record of this row . select the rows whose athlete record fuzzily matches to kevin little . take the result record of this row . the first record is less than the second record .
and { eq { nth_max { all_rows ; crowd ; 1 } ; 26000 } ; and { eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; punt road oval } ; eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; date } ; 9 august 1941 } } } = true
Output: the 1st maximum crowd record of all rows is 26000 . the venue record of the row with 1st maximum crowd record is punt road oval . the date record of the row with 1st maximum crowd record is 9 august 1941 .
round_eq { sum { all_rows ; attendance } ; 471,075 } = true
Output: the sum of the attendance record of all rows is 471,075 .
eq { hop { argmax { all_rows ; games } ; season } ; 2007 } = true
Output: select the row whose games record of all rows is maximum . the season record of this row is 2007 .
and { only { filter_eq { all_rows ; segment d ; part 2 } } ; eq { hop { filter_eq { all_rows ; segment d ; part 2 } ; series ep } ; 4 - 04 } } = true
Output: select the rows whose segment d record fuzzily matches to part 2 . there is only one such row in the table . the series ep record of this unqiue row is 4  04 .
eq { count { filter_all { all_rows ; goal } } ; 6 } = true
Output: select the rows whose goal record is arbitrary . the number of such rows is 6 .
and { eq { max { all_rows ; duration ( days ) } ; 184.84 } ; eq { hop { argmax { all_rows ; duration ( days ) } ; expedition } ; salyut 6 - eo - 4 } } = true
Output: the maximum duration  days  record of all rows is 184.84 . the expedition record of the row with superlative duration  days  record is salyut 6  eo  4 .
greater { hop { filter_eq { all_rows ; opponent ; 2 syracuse } ; result / score } ; hop { filter_eq { all_rows ; opponent ; 1 georgetown } ; result / score } } = true
Output: select the rows whose opponent record fuzzily matches to 2 syracuse . take the result  score record of this row . select the rows whose opponent record fuzzily matches to 1 georgetown . take the result  score record of this row . the first record is greater than the second record .
only { filter_eq { all_rows ; high points ; feenstra } } = true
Output: select the rows whose high points record fuzzily matches to feenstra . there is only one such row in the table .
eq { hop { argmin { filter_eq { all_rows ; surface ; hard } ; date } ; opponent in the final } ; andre agassi } = true
Output: select the rows whose surface record fuzzily matches to hard . select the row whose date record of these rows is minimum . the opponent in the final record of this row is andre agassi .
eq { count { filter_eq { all_rows ; language ; english } } ; 2 } = true
Output: select the rows whose language record fuzzily matches to english . the number of such rows is 2 .
most_eq { all_rows ; country ; belgium } = true
Output: for the country records of all rows , most of them fuzzily match to belgium .
most_greater_eq { all_rows ; socialist ; 42 % } = true
Output: for the socialist records of all rows , most of them are greater than or equal to 42  .
round_eq { sum { all_rows ; runs scored } ; 1,097 } = true
Output: the sum of the runs scored record of all rows is 1,097 .
round_eq { avg { all_rows ; first downs } ; 19.42 } = true
Output: the average of the first downs record of all rows is 19.42 .
eq { count { filter_eq { all_rows ; fat32 ; yes } } ; 4 } = true
Output: select the rows whose fat32 record fuzzily matches to yes . the number of such rows is 4 .
eq { count { filter_eq { filter_greater { all_rows ; attendance ; 70000 } ; tv time ; nbc } } ; 4 } = true
Output: select the rows whose attendance record is greater than 70000 . among these rows , select the rows whose tv time record fuzzily matches to nbc . the number of such rows is 4 .
and { only { filter_eq { all_rows ; college ; auburn } } ; eq { hop { filter_eq { all_rows ; college ; auburn } ; player } ; charles barkley } } = true
Output: select the rows whose college record fuzzily matches to auburn . there is only one such row in the table . the player record of this unqiue row is charles barkley .
round_eq { sum { all_rows ; points } ; 434 } = true
Output: the sum of the points record of all rows is 434 .
eq { count { filter_eq { all_rows ; position ; goaltender } } ; 3 } = true
Output: select the rows whose position record fuzzily matches to goaltender . the number of such rows is 3 .
eq { hop { nth_argmax { all_rows ; % of votes khuzestan ; 2 } ; candidates } ; akbar hashemi rafsanjani } = true
Output: select the row whose  of votes khuzestan record of all rows is 2nd maximum . the candidates record of this row is akbar hashemi rafsanjani .
eq { hop { argmax { all_rows ; gdp ( billion us ) } ; member countries } ; eu25 ( 2004 ) } = true
Output: select the row whose gdp  billion us  record of all rows is maximum . the member countries record of this row is eu25  2004  .
most_eq { all_rows ; manner of departure ; mutual consent } = true
Output: for the manner of departure records of all rows , most of them fuzzily match to mutual consent .
eq { count { filter_all { all_rows ; name } } ; 11 } = true
Output: select the rows whose name record is arbitrary . the number of such rows is 11 .
eq { nth_min { all_rows ; date ; 16 } ; december 20 , 1981 } = true
Output: the 16th minimum date record of all rows is december 20 , 1981 .
only { filter_eq { all_rows ; date ; 11 march 1981 } } = true
Output: select the rows whose date record fuzzily matches to 11 march 1981 . there is only one such row in the table .
most_eq { all_rows ; award ceremony ; drama desk award } = true
Output: for the award ceremony records of all rows , most of them fuzzily match to drama desk award .
eq { hop { nth_argmax { all_rows ; population ( 2011 ) ; 2 } ; settlement } ; aleksandrovo } = true
Output: select the row whose population  2011  record of all rows is 2nd maximum . the settlement record of this row is aleksandrovo .
and { only { filter_eq { all_rows ; position ; guard } } ; eq { hop { filter_eq { all_rows ; position ; guard } ; player } ; steve kerr } } = true
Output: select the rows whose position record fuzzily matches to guard . there is only one such row in the table . the player record of this unqiue row is steve kerr .
all_eq { all_rows ; episodes ; 22 } = true
Output: for the episodes records of all rows , all of them are equal to 22 .
most_greater { all_rows ; conversions ; 50 } = true
Output: for the conversions records of all rows , most of them are greater than 50 .
eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; home team } ; sunderland } = true
Output: select the row whose attendance record of all rows is 1st maximum . the home team record of this row is sunderland .
eq { hop { nth_argmax { all_rows ; total elected 2001 ; 2 } ; party } ; democratic party } = true
Output: select the row whose total elected 2001 record of all rows is 2nd maximum . the party record of this row is democratic party .
greater { hop { filter_eq { all_rows ; school ; owen valley } ; enrollment } ; hop { filter_eq { all_rows ; school ; sullivan } ; enrollment } } = true
Output: select the rows whose school record fuzzily matches to owen valley . take the enrollment record of this row . select the rows whose school record fuzzily matches to sullivan . take the enrollment record of this row . the first record is greater than the second record .
only { filter_eq { all_rows ; engine name ; 1.6 tdi ecomotive } } = true
Output: select the rows whose engine name record fuzzily matches to 1.6 tdi ecomotive . there is only one such row in the table .