In this task, you are given commands (in terms of logical operations) and natural interpretation of the given command to select relevant rows from the given table. Your job is to generate a label "yes" if the interpretation is appropriate for the command, otherwise generate label "no". 
 Here are the definitions of logical operators: 
 1. count: returns the number of rows in the view. 
 2. only: returns whether there is exactly one row in the view. 
 3. hop: returns the value under the header column of the row. 
 4. and: returns the boolean operation result of two arguments. 
 5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column. 
 6. nth_max/nth_min: returns the n-th max/n-th min of the values under the header column. 
 7. argmax/argmin: returns the row with the max/min value in header column. 
 8. nth_argmax/nth_argmin: returns the row with the n-th max/min value in header column. 
 9. eq/not_eq: returns if the two arguments are equal. 
 10. round_eq: returns if the two arguments are roughly equal under certain tolerance. 
 11. greater/less: returns if the first argument is greater/less than the second argument. 
 12. diff: returns the difference between two arguments. 
 13. filter_eq/ filter_not_eq: returns the subview whose values under the header column is equal/not equal to the third argument. 
 14. filter_greater/filter_less: returns the subview whose values under the header column is greater/less than the third argument. 
 15. filter_greater_eq /filter_less_eq: returns the subview whose values under the header column is greater/less or equal than the third argument. 
 16. filter_all: returns the view itself for the case of describing the whole table 
 17. all_eq/not_eq: returns whether all the values under the header column are equal/not equal to the third argument. 
 18. all_greater/less: returns whether all the values under the header column are greater/less than the third argument. 
 19. all_greater_eq/less_eq: returns whether all the values under the header column are greater/less or equal to the third argument. 
 20. most_eq/not_eq: returns whether most of the values under the header column are equal/not equal to the third argument. 
 21. most_greater/less: returns whether most of the values under the header column are greater/less than the third argument. 
 22. most_greater_eq/less_eq: returns whether most of the values under the header column are greater/less or equal to the third argument.

Ex Input:
Command: and { only { filter_less { all_rows ; crowd ; 10000 } } ; and { eq { hop { filter_less { all_rows ; crowd ; 10000 } ; home team } ; geelong } ; and { eq { hop { filter_less { all_rows ; crowd ; 10000 } ; away team } ; north melbourne } ; eq { hop { filter_less { all_rows ; crowd ; 10000 } ; venue } ; kardinia park } } } }, interpretation: select the rows whose crowd record is less than 10000 . there is only one such row in the table . the home team record of this unqiue row is geelong . the away team record of this unqiue row is north melbourne . the venue record of this unqiue row is kardinia park .

Ex Output:
yes


Ex Input:
Command: eq { hop { argmax { all_rows ; density } ; english name } ; xinluo district }, interpretation: select the rows whose city of license record fuzzily matches to ellijay , georgia . take the frequency mhz record of this row . select the rows whose city of license record fuzzily matches to morrow , georgia . take the frequency mhz record of this row . the first record is less than the second record .

Ex Output:
no


Ex Input:
Command: eq { count { filter_eq { filter_eq { all_rows ; engine ; 4.7 l powertech v8 } ; years ; 2005-2007 } } ; 1 }, interpretation: select the rows whose engine record fuzzily matches to 4.7 l powertech v8 . among these rows , select the rows whose years record fuzzily matches to 2005-2007 . the number of such rows is 1 .

Ex Output:

yes