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.

Example Input: Command: and { eq { nth_min { filter_eq { all_rows ; result ; l } ; date ; 2 } ; october 11 , 1998 } ; eq { hop { nth_argmin { filter_eq { all_rows ; result ; l } ; date ; 2 } ; opponent } ; new england patriots } }, interpretation: select the row whose year record of all rows is 1st minimum . the name record of this row is franklin exchange building .
Example Output: no

Example Input: Command: and { greater { hop { filter_eq { all_rows ; name ; adam gilchrist ( wk ) } ; innings } ; hop { filter_eq { all_rows ; name ; matthew hayden } ; innings } } ; and { eq { hop { filter_eq { all_rows ; name ; adam gilchrist ( wk ) } ; innings } ; 8 } ; eq { hop { filter_eq { all_rows ; name ; matthew hayden } ; innings } ; 6 } } }, interpretation: select the rows whose winning team record fuzzily matches to texas . among these rows , select the rows whose winning pitcher record fuzzily matches to chris young . the number of such rows is 2 .
Example Output: no

Example Input: Command: 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 } }, interpretation: select the rows whose area ( km 2 ) record is less than 50 . select the row whose population record of these rows is 1st maximum . the common of record of this row is moncalieri .
Example Output:
no