TASK DEFINITION: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command. 
 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 argument 1 is greater/less than argument 2 
 12. diff: returns the difference between two arguments 
 13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3 
 14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3 
 15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3 
 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 argument 3 
 18. all greater/less: returns whether all the values under the header column are greater/less than argument 3 
 19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3 
 20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3 
 21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3 
 22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
PROBLEM: and { eq { diff { hop { filter_eq { all_rows ; tournament ; bc open } ; margin of victory } ; hop { filter_eq { all_rows ; tournament ; glen campbell - los angeles open } ; margin of victory } } ; 3 } ; and { eq { hop { filter_eq { all_rows ; tournament ; bc open } ; margin of victory } ; 5 strokes } ; eq { hop { filter_eq { all_rows ; tournament ; glen campbell - los angeles open } ; margin of victory } ; 2 strokes } } } = true

SOLUTION: select the rows whose tournament record fuzzily matches to bc open . take the margin of victory record of this row . select the rows whose tournament record fuzzily matches to glen campbell  los angeles open . take the margin of victory record of this row . the first record is 3 larger than the second record . the margin of victory record of the first row is 5 strokes . the margin of victory record of the second row is 2 strokes .

PROBLEM: eq { count { filter_greater { filter_less { all_rows ; home team score ; 15 } ; crowd ; 20000 } } ; 3 } = true

SOLUTION: select the rows whose home team score record is less than 15 . among these rows , select the rows whose crowd record is greater than 20000 . the number of such rows is 3 .

PROBLEM: and { greater { hop { filter_eq { all_rows ; date ; sept 15 } ; attendance } ; hop { filter_eq { all_rows ; date ; nov 3 } ; attendance } } ; and { eq { hop { filter_eq { all_rows ; date ; sept 15 } ; opponent } ; green bay packers } ; eq { hop { filter_eq { all_rows ; date ; nov 3 } ; opponent } ; chicago bears } } } = true

SOLUTION:
select the rows whose date record fuzzily matches to sept 15 . take the attendance record of this row . select the rows whose date record fuzzily matches to nov 3 . take the attendance record of this row . the first record is greater than the second record . the opponent record of the first row is green bay packers . the opponent record of the second row is chicago bears .