instruction:
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.
question:
Command: eq { count { filter_greater_eq { filter_greater_eq { all_rows ; gold ; 10 } ; silver ; 20 } } ; 3 }, interpretation: select the rows whose gold record is greater than or equal to 10 . among these rows , select the rows whose silver record is greater than or equal to 20 . the number of such rows is 3 .
answer:
yes


question:
Command: round_eq { avg { filter_eq { all_rows ; release date ; january 2011 } ; release price ( usd ) } ; 507.71 }, interpretation: select the rows whose gold record is greater than 100 . select the row whose silver record of these rows is maximum . the country record of this row is indonesia .
answer:
no


question:
Command: and { not_eq { hop { filter_eq { all_rows ; tournament ; paris } ; career win - loss } ; hop { filter_eq { all_rows ; tournament ; rome } ; career win - loss } } ; and { eq { hop { filter_eq { all_rows ; tournament ; paris } ; career win - loss } ; 6 - 4 } ; eq { hop { filter_eq { all_rows ; tournament ; rome } ; career win - loss } ; 0 - 8 } } }, interpretation: select the rows whose tournament record fuzzily matches to paris . take the career win - loss record of this row . select the rows whose tournament record fuzzily matches to rome . take the career win - loss record of this row . the first record does not match to the second record . the career win - loss record of the first row is 6 - 4 . the career win - loss record of the second row is 0 - 8 .
answer:

yes