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.

Command: most_eq { all_rows ; location ; south dakota }, interpretation: select the rows whose model number record fuzzily matches to core i7 - 2649 m . take the frequency record of this row . select the rows whose model number record fuzzily matches to core i7 - 2629 m . take the frequency record of this row . the first record is greater than the second record .
no

Command: and { greater { hop { filter_eq { all_rows ; date ; april 1 } ; record } ; hop { filter_eq { all_rows ; date ; march 30 } ; record } } ; and { eq { hop { filter_eq { all_rows ; date ; april 1 } ; record } ; 3 - 2 } ; eq { hop { filter_eq { all_rows ; date ; march 30 } ; record } ; 2 - 2 } } }, interpretation: select the rows whose date record fuzzily matches to april 1 . take the record record of this row . select the rows whose date record fuzzily matches to march 30 . take the record record of this row . the first record is greater than the second record . the record record of the first row is 3 - 2 . the record record of the second row is 2 - 2 .
yes

Command: greater { hop { filter_eq { all_rows ; opponent ; dallas cowboys } ; attendance } ; hop { filter_eq { all_rows ; opponent ; philadelphia eagles } ; attendance } }, interpretation: select the rows whose opponent record fuzzily matches to dallas cowboys . take the attendance record of this row . select the rows whose opponent record fuzzily matches to philadelphia eagles . take the attendance record of this row . the first record is greater than the second record .

yes