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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the directed by records of all rows , all of them fuzzily match to noam pitlik .
Output:
|
[
"all_eq { all_rows ; directed by ; noam pitlik }"
] |
task210-2687152f3d274af2b359229181497eea
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose first elected record is equal to 1882 . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_eq { all_rows ; first elected ; 1882 } } ; 3 }"
] |
task210-89ade26cb4514cf8a41ce9087e7da6a0
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose colour record fuzzily matches to brown . there is only one such row in the table . the name record of this unqiue row is ted .
Output:
|
[
"and { only { filter_eq { all_rows ; colour ; brown } } ; eq { hop { filter_eq { all_rows ; colour ; brown } ; name } ; ted } }"
] |
task210-5e72b1ddd78a474f99ec9456d7d6c0a0
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the points records of all rows , most of them are less than 90 .
Output:
|
[
"most_less { all_rows ; points ; 90 }"
] |
task210-dfa048dcc1fe412e8c2d36b48515c63f
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose to par record fuzzily matches to +5 . the number of such rows is 4 .
Output:
|
[
"eq { count { filter_eq { all_rows ; to par ; +5 } } ; 4 }"
] |
task210-6c061cbcd65d4abd9db00be2c9cbe976
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose incumbent record fuzzily matches to adam smith . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to dave reichert . take the first elected record of this row . the first record is less than the second record .
Output:
|
[
"less { hop { filter_eq { all_rows ; incumbent ; adam smith } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; dave reichert } ; first elected } }"
] |
task210-ec3ee716e522419a8bdd51801fd68089
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose college record fuzzily matches to san diego state . there is only one such row in the table . the name record of this unqiue row is freddie keiaho .
Output:
|
[
"and { only { filter_eq { all_rows ; college ; san diego state } } ; eq { hop { filter_eq { all_rows ; college ; san diego state } ; name } ; freddie keiaho } }"
] |
task210-ad0355438b704a448e04e43d5ead4974
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose channel record fuzzily matches to atv world . take the launch date record of this row . select the rows whose channel record fuzzily matches to tvb pearl . take the launch date record of this row . the first record is less than the second record .
Output:
|
[
"less { hop { filter_eq { all_rows ; channel ; atv world } ; launch date } ; hop { filter_eq { all_rows ; channel ; tvb pearl } ; launch date } }"
] |
task210-19803ab5422740fcae259e6622e31ce8
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose capacity record of all rows is maximum . the club record of this row is real madrid cf .
Output:
|
[
"eq { hop { argmax { all_rows ; capacity } ; club } ; real madrid cf }"
] |
task210-85c0b42d0e584b7482893f6b7c54ba40
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose attendance record of all rows is 3rd maximum . the date record of this row is 8 december 1999 .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; date } ; 8 december 1999 }"
] |
task210-11101319ceee4fbc8a65b9a670ba8f06
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose location record fuzzily matches to usa . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; location ; usa } } ; 2 }"
] |
task210-5a7159ddd7ba4f5a82cf1f00c24ba833
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the average of the crowd record of all rows is 14924 .
Output:
|
[
"round_eq { avg { all_rows ; crowd } ; 14924 }"
] |
task210-518ff84c1cdf462c8dddfc151e62d950
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose no in series record is arbitrary . the number of such rows is 5 .
Output:
|
[
"eq { count { filter_all { all_rows ; no in series } } ; 5 }"
] |
task210-45e023aae7d44186a5395aedbf346d15
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose tournament record fuzzily matches to spain . there is only one such row in the table . the date record of this unqiue row is 11 february 2008 .
Output:
|
[
"and { only { filter_eq { all_rows ; tournament ; spain } } ; eq { hop { filter_eq { all_rows ; tournament ; spain } ; date } ; 11 february 2008 } }"
] |
task210-adbff5e033ae41d691483494f5bbc601
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the sum of the charlton goals record of all rows is 178 .
Output:
|
[
"round_eq { sum { all_rows ; charlton goals } ; 178 }"
] |
task210-d97c0c21299b4616a9bcc2cd3c0823bf
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose location record fuzzily matches to usa . the number of such rows is 6 .
Output:
|
[
"eq { count { filter_eq { all_rows ; location ; usa } } ; 6 }"
] |
task210-b8602bdca46948e4b0e348b7fca0a6e1
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose locale record fuzzily matches to prince edward island . there is only one such row in the table . the skip record of this unqiue row is rod macdonald .
Output:
|
[
"and { only { filter_eq { all_rows ; locale ; prince edward island } } ; eq { hop { filter_eq { all_rows ; locale ; prince edward island } ; skip } ; rod macdonald } }"
] |
task210-52bac87917fd423aa935c354050ac790
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose couple record fuzzily matches to jason & edyta . take the score record of this row . select the rows whose couple record fuzzily matches to kristi & mark . take the score record of this row . the first record is less than the second record . the score record of the first row is 23 ( 8 , 7 , 8 ) . the score record of the second row is 27 ( 9 , 9 , 9 ) .
Output:
|
[
"and { less { hop { filter_eq { all_rows ; couple ; jason & edyta } ; score } ; hop { filter_eq { all_rows ; couple ; kristi & mark } ; score } } ; and { eq { hop { filter_eq { all_rows ; couple ; jason & edyta } ; score } ; 23 ( 8 , 7 , 8 ) } ; eq { hop { filter_eq { all_rows ; couple ; kristi & mark } ; score } ; 27 ( 9 , 9 , 9 ) } } }"
] |
task210-0b79a0700da8492ea1f6e1cb0746c266
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose event record fuzzily matches to masters . take the 2012 - 13 record of this row . select the rows whose event record fuzzily matches to autumn gold . take the 2012 - 13 record of this row . the first record fuzzily matches to the second record .
Output:
|
[
"eq { hop { filter_eq { all_rows ; event ; masters } ; 2012 - 13 } ; hop { filter_eq { all_rows ; event ; autumn gold } ; 2012 - 13 } }"
] |
task210-c60e7208fbb945c8badfcc145c1eb779
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose mens singles record fuzzily matches to andrew smith . there is only one such row in the table . the year record of this unqiue row is 2006 .
Output:
|
[
"and { only { filter_eq { all_rows ; mens singles ; andrew smith } } ; eq { hop { filter_eq { all_rows ; mens singles ; andrew smith } ; year } ; 2006 } }"
] |
task210-3d676ae9a8e1463dac75311c8fc233cc
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the average of the points record of all rows is 80 .
Output:
|
[
"round_eq { avg { all_rows ; points } ; 80 }"
] |
task210-87a1d96b6d6f4bed8708d9fbc24aeb34
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose venue record fuzzily matches to princes park . there is only one such row in the table . the home team record of this unqiue row is carlton . the away team record of this unqiue row is geelong .
Output:
|
[
"and { only { filter_eq { all_rows ; venue ; princes park } } ; and { eq { hop { filter_eq { all_rows ; venue ; princes park } ; home team } ; carlton } ; eq { hop { filter_eq { all_rows ; venue ; princes park } ; away team } ; geelong } } }"
] |
task210-0c4733073966464a831de2cafb48489d
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose crowd record of all rows is 1st maximum . the venue record of this row is brunswick street oval .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; brunswick street oval }"
] |
task210-2de2c707ecca44dc85bf999110916634
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose original channel record fuzzily matches to bbc one . there is only one such row in the table . the programme record of this unqiue row is superstars .
Output:
|
[
"and { only { filter_eq { all_rows ; original channel ; bbc one } } ; eq { hop { filter_eq { all_rows ; original channel ; bbc one } ; programme } ; superstars } }"
] |
task210-07220e20abe9456f9cc623750d29451e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose ihsaa football class record fuzzily matches to aaaa . the number of such rows is 6 .
Output:
|
[
"eq { count { filter_eq { all_rows ; ihsaa football class ; aaaa } } ; 6 }"
] |
task210-017988e5ca5b402c9f795818dd2277a9
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the of which currently forests , km square records of all rows , most of them are less than 1000 .
Output:
|
[
"most_less { all_rows ; of which currently forests , km square ; 1000 }"
] |
task210-7f1cbc38edca4f7a93638a061c506d5e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose base record fuzzily matches to united states . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; base ; united states } } ; 2 }"
] |
task210-905322d879db49d590a666e8d27ffdb3
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose final record fuzzily matches to did not advance . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_eq { all_rows ; final ; did not advance } } ; 3 }"
] |
task210-1449ab4314ba452595a83c242ec7e997
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose race 2 ( pts ) record of all rows is maximum . the country record of this row is france .
Output:
|
[
"eq { hop { argmax { all_rows ; race 2 ( pts ) } ; country } ; france }"
] |
task210-14e7f3f36a414ddd8636ee60bad8b1e1
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the lead records of all rows , most of them are greater than or equal to 10 .
Output:
|
[
"most_greater_eq { all_rows ; lead ; 10 }"
] |
task210-ab8af20357904c208be02446d51dbc0b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose circuit record fuzzily matches to marcus theatres . take the sites record of this row . select the rows whose circuit record fuzzily matches to rave motion pictures . take the sites record of this row . the second record is 7 larger than the first record .
Output:
|
[
"eq { diff { hop { filter_eq { all_rows ; circuit ; marcus theatres } ; sites } ; hop { filter_eq { all_rows ; circuit ; rave motion pictures } ; sites } } ; -7 }"
] |
task210-bdda86b08f17430eb7e2c466f1a9e4f2
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose aspect record fuzzily matches to 16:9 . there is only one such row in the table . the channel record of this unqiue row is 31.1 .
Output:
|
[
"and { only { filter_eq { all_rows ; aspect ; 16:9 } } ; eq { hop { filter_eq { all_rows ; aspect ; 16:9 } ; channel } ; 31.1 } }"
] |
task210-4ce86e7fbf344128aecdf185b13b6f1b
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the average of the round record of all rows is 3.7 .
Output:
|
[
"round_eq { avg { all_rows ; round } ; 3.7 }"
] |
task210-7089d6f8bcfb4b469fc74961a3a41bfb
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose year record is equal to 1954 . the sum of the points record of these rows is 4 .
Output:
|
[
"round_eq { sum { filter_eq { all_rows ; year ; 1954 } ; points } ; 4 }"
] |
task210-630e99d2d262434db3b432b177f1405a
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose result record fuzzily matches to re-elected . the number of such rows is 4 .
Output:
|
[
"eq { count { filter_eq { all_rows ; result ; re-elected } } ; 4 }"
] |
task210-30048027c5334438ad405efd6437cfa9
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the laps records of all rows , most of them are equal to 48 .
Output:
|
[
"most_eq { all_rows ; laps ; 48 }"
] |
task210-489e107afecd43e3a8cbe5abeebe7f6d
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose height record of all rows is maximum . the player record of this row is josé luis moltó .
Output:
|
[
"eq { hop { argmax { all_rows ; height } ; player } ; josé luis moltó }"
] |
task210-09fa22b2ed384d8687a7dd53aba0de3a
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose no of series record is equal to 3 . select the row whose episodes record of these rows is minimum . the actor record of this row is ellen thomas .
Output:
|
[
"eq { hop { argmin { filter_eq { all_rows ; no of series ; 3 } ; episodes } ; actor } ; ellen thomas }"
] |
task210-77d137f2c67c4e3fb2751a717a7d6bf5
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Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the sum of the points record of all rows is 490 .
Output:
|
[
"round_eq { sum { all_rows ; points } ; 490 }"
] |
task210-43aa792e0f5d4d5389c8a48d439fa017
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose written by record fuzzily matches to donald p bellisario . there is only one such row in the table . the title record of this unqiue row is we the people .
Output:
|
[
"and { only { filter_eq { all_rows ; written by ; donald p bellisario } } ; eq { hop { filter_eq { all_rows ; written by ; donald p bellisario } ; title } ; we the people } }"
] |
task210-43a60300d1764aacbb736a7193332831
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the 3rd minimum round record of all rows is 3 . the circuit record of the row with 3rd minimum round record is wakefield park .
Output:
|
[
"and { eq { nth_min { all_rows ; round ; 3 } ; 3 } ; eq { hop { nth_argmin { all_rows ; round ; 3 } ; circuit } ; wakefield park } }"
] |
task210-8e8ffac7e9d549e2bad1a4a6d4717c37
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose attendance record of all rows is maximum . the date record of this row is 1970 - 10 - 04 .
Output:
|
[
"eq { hop { argmax { all_rows ; attendance } ; date } ; 1970 - 10 - 04 }"
] |
task210-7d990a45797c4ff68f19cc970f92fa9b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the average of the round record of all rows is 3.8 .
Output:
|
[
"round_eq { avg { all_rows ; round } ; 3.8 }"
] |
task210-3e1ac2f7351f41e08b78ffb9aca76847
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose location record fuzzily matches to seattle . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_eq { all_rows ; location ; seattle } } ; 3 }"
] |
task210-19197548abe942e0a7e474fac4b0bc4e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose date record of all rows is 2nd minimum . the score record of this row is 3 - 6 , 2 - 6 .
Output:
|
[
"eq { hop { nth_argmin { all_rows ; date ; 2 } ; score } ; 3 - 6 , 2 - 6 }"
] |
task210-39667cc3029842c0a28ca3e4a55a20be
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose asts record of all rows is maximum . the player record of this row is gail goodrich .
Output:
|
[
"eq { hop { argmax { all_rows ; asts } ; player } ; gail goodrich }"
] |
task210-fd0e90e3ef3d433b9e44a96d4270faa1
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the average of the crowd record of all rows is 12000 .
Output:
|
[
"round_eq { avg { all_rows ; crowd } ; 12000 }"
] |
task210-179431f97e074c9396938788236c46d6
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose kit manufacturer record fuzzily matches to umbro . the number of such rows is 4 .
Output:
|
[
"eq { count { filter_eq { all_rows ; kit manufacturer ; umbro } } ; 4 }"
] |
task210-5757234c1a5f4de49ecb8d3767996f6e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the clubs involved records of all rows , most of them are greater than 10 .
Output:
|
[
"most_greater { all_rows ; clubs involved ; 10 }"
] |
task210-4a4a4f21713b4aec95606def4814b10f
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose call sign record fuzzily matches to cjjc - fm . take the frequency record of this row . select the rows whose call sign record fuzzily matches to cfgw - fm . take the frequency record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; call sign ; cjjc - fm } ; frequency } ; hop { filter_eq { all_rows ; call sign ; cfgw - fm } ; frequency } }"
] |
task210-fe96366a0cf04de7ad3a7f03f098c4bd
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the winning amount records of all rows , most of them fuzzily match to rs 10 , 00000 .
Output:
|
[
"most_eq { all_rows ; winning amount ; rs 10 , 00000 }"
] |
task210-b759cac1e842460e92a1de1a9cda84cc
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose opponent record fuzzily matches to east fife . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { all_rows ; opponent ; east fife } } ; 2 }"
] |
task210-72db1e4a0e3241eeb782eb86b3aacb70
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose title record fuzzily matches to olympic . there is only one such row in the table .
Output:
|
[
"only { filter_eq { all_rows ; title ; olympic } }"
] |
task210-0477ad8fb94a4570b816278b133452b8
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the attendance records of all rows , most of them are greater than 70000 .
Output:
|
[
"most_greater { all_rows ; attendance ; 70000 }"
] |
task210-b511ab6a235845e9a1d3fe953b42c8f3
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose country record fuzzily matches to bosnia and herzegovina . there is only one such row in the table . the film record of this unqiue row is prva plata .
Output:
|
[
"and { only { filter_eq { all_rows ; country ; bosnia and herzegovina } } ; eq { hop { filter_eq { all_rows ; country ; bosnia and herzegovina } ; film } ; prva plata } }"
] |
task210-aac70c56701f431c960f58154d8db497
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose played record is equal to 114 . for the points records of these rows , most of them are greater than 100 .
Output:
|
[
"most_greater { filter_eq { all_rows ; played ; 114 } ; points ; 100 }"
] |
task210-ea037fb28a9840d0bc3d46a348d24613
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose points record of all rows is maximum . the year record of this row is 2010 .
Output:
|
[
"eq { hop { argmax { all_rows ; points } ; year } ; 2010 }"
] |
task210-c087b258627647219c5963f98d3f647a
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the seaman records of all rows , most of them fuzzily match to petty officer .
Output:
|
[
"most_eq { all_rows ; seaman ; petty officer }"
] |
task210-a799d90a4dac44c0bc1beba1f90987b7
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose enrollment record is greater than 3000 . there is only one such row in the table . the school record of this unqiue row is lake central .
Output:
|
[
"and { only { filter_greater { all_rows ; enrollment ; 3000 } } ; eq { hop { filter_greater { all_rows ; enrollment ; 3000 } ; school } ; lake central } }"
] |
task210-4a65b6966442468184de131f807dc902
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose directed by record fuzzily matches to steve mann . among these rows , select the rows whose written by record fuzzily matches to john ridley . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_eq { filter_eq { all_rows ; directed by ; steve mann } ; written by ; john ridley } } ; 3 }"
] |
task210-54d22e2a82c64fd7bf29dabae27b4f66
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose season record is greater than 2005 . among these rows , select the rows whose teams record is equal to 16 . the number of such rows is 4 .
Output:
|
[
"eq { count { filter_eq { filter_greater { all_rows ; season ; 2005 } ; teams ; 16 } } ; 4 }"
] |
task210-eb400e6a27aa4ac4973a1e00f72799af
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the average of the viewers record of all rows is 872100 .
Output:
|
[
"round_eq { avg { all_rows ; viewers } ; 872100 }"
] |
task210-fb97b70c192f4a498a4bff6a64107c5c
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the population ( 2008 ) records of all rows , most of them are greater than 100000 .
Output:
|
[
"most_greater { all_rows ; population ( 2008 ) ; 100000 }"
] |
task210-033798e037ec4e528602581d33eb1a3c
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose pick record of all rows is minimum . the nhl team record of this row is hartford whalers .
Output:
|
[
"eq { hop { argmin { all_rows ; pick } ; nhl team } ; hartford whalers }"
] |
task210-ed5a7e1e95904623805695e522b8c2f7
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose current streak record of all rows is 2nd maximum . the missouri vs record of this row is drake .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; current streak ; 2 } ; missouri vs } ; drake }"
] |
task210-081056611b7f479db4cce611a7e56bc9
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose year record is equal to 2010 . among these rows , select the rows whose recipient record fuzzily matches to the suite life on deck . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { filter_eq { all_rows ; year ; 2010 } ; recipient ; the suite life on deck } } ; 2 }"
] |
task210-10439944646142f593188871a4fd856f
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose crowd record is greater than 30000 . there is only one such row in the table . the home team record of this unqiue row is melbourne .
Output:
|
[
"and { only { filter_greater { all_rows ; crowd ; 30000 } } ; eq { hop { filter_greater { all_rows ; crowd ; 30000 } ; home team } ; melbourne } }"
] |
task210-97f3a0b267894b70afbef73ab8d39cc9
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose away team record fuzzily matches to south melbourne . take the away team score record of this row . select the rows whose away team record fuzzily matches to north melbourne . take the away team score record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; away team ; south melbourne } ; away team score } ; hop { filter_eq { all_rows ; away team ; north melbourne } ; away team score } }"
] |
task210-9f356ccebfda4d148e865dcc070a1ed4
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose finish record fuzzily matches to avignon . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_eq { all_rows ; finish ; avignon } } ; 3 }"
] |
task210-d7c9339628424116b8e718a46df852a5
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose to par record of all rows is 2nd maximum . the player record of this row is mark hensby .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; to par ; 2 } ; player } ; mark hensby }"
] |
task210-d493aa87e29940568dab8d02dda74db0
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose country record does not match to united states . there is only one such row in the table . the player record of this unqiue row is david graham .
Output:
|
[
"and { only { filter_not_eq { all_rows ; country ; united states } } ; eq { hop { filter_not_eq { all_rows ; country ; united states } ; player } ; david graham } }"
] |
task210-bfd66845b93a4a00abf0438928a0304f
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the 2nd minimum year record of all rows is 1994 . the men 's singles record of the row with 2nd minimum year record is juraj brestovský .
Output:
|
[
"and { eq { nth_min { all_rows ; year ; 2 } ; 1994 } ; eq { hop { nth_argmin { all_rows ; year ; 2 } ; men 's singles } ; juraj brestovský } }"
] |
task210-67d512d79a094c6b9eeb4595caa56c3d
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose name of rivalry record fuzzily matches to auburn - tennessee football rivalry . take the games played record of this row . select the rows whose name of rivalry record fuzzily matches to auburn - clemson rivalry . take the games played record of this row . the first record is 3 larger than the second record .
Output:
|
[
"eq { diff { hop { filter_eq { all_rows ; name of rivalry ; auburn - tennessee football rivalry } ; games played } ; hop { filter_eq { all_rows ; name of rivalry ; auburn - clemson rivalry } ; games played } } ; 3 }"
] |
task210-9df29e2e429241ab879ffd0d8b521acc
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose squadron record fuzzily matches to squadron 552 . among these rows , select the rows whose dates record fuzzily matches to 2006-present . the number of such rows is 1 .
Output:
|
[
"eq { count { filter_eq { filter_eq { all_rows ; squadron ; squadron 552 } ; dates ; 2006-present } } ; 1 }"
] |
task210-762da0caf8ef433fab82a9f7b55ee6c8
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose won record is equal to 16 . there is only one such row in the table . the club record of this unqiue row is northampton saints ( sf ) .
Output:
|
[
"and { only { filter_eq { all_rows ; won ; 16 } } ; eq { hop { filter_eq { all_rows ; won ; 16 } ; club } ; northampton saints ( sf ) } }"
] |
task210-2704f4ba37b2435aaf3f2fb297f9a6cc
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose score record of all rows is maximum . the opponent record of this row is boston bruins .
Output:
|
[
"eq { hop { argmax { all_rows ; score } ; opponent } ; boston bruins }"
] |
task210-413f1fc39c854e16be54158f98366145
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose score record of all rows is 2nd maximum . the competition record of this row is 2007 afc asian cup qualification .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; score ; 2 } ; competition } ; 2007 afc asian cup qualification }"
] |
task210-a7023c23cfa64b1db33028fe00bf0eea
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose episode record fuzzily matches to episode 5 . take the viewing figure record of this row . select the rows whose episode record fuzzily matches to episode 7 . take the viewing figure record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; episode ; episode 5 } ; viewing figure } ; hop { filter_eq { all_rows ; episode ; episode 7 } ; viewing figure } }"
] |
task210-3d9a978089a742e7b2241e598d89c8a2
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose record label record fuzzily matches to for us . there is only one such row in the table . the single record of this unqiue row is moped girls .
Output:
|
[
"and { only { filter_eq { all_rows ; record label ; for us } } ; eq { hop { filter_eq { all_rows ; record label ; for us } ; single } ; moped girls } }"
] |
task210-a93b0bb1c4fc468dbb2676429b9aed59
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose total elected 2001 record of all rows is 2nd maximum . the party record of this row is democratic party .
Output:
|
[
"eq { hop { nth_argmax { all_rows ; total elected 2001 ; 2 } ; party } ; democratic party }"
] |
task210-4d846447d3bd4ee0b715d76380dfd74b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: 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 .
Output:
|
[
"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 } } }"
] |
task210-c5c33f8a2d554291b862d32c1b1b6420
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the row whose enrollment record of all rows is maximum . the institution record of this row is east carolina university .
Output:
|
[
"eq { hop { argmax { all_rows ; enrollment } ; institution } ; east carolina university }"
] |
task210-899dda21f7f248a1b3a6951a4d6bda1f
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose directed by record fuzzily matches to alex chapple . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_eq { all_rows ; directed by ; alex chapple } } ; 3 }"
] |
task210-49db22b97aed4983ace74141b1739a39
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose location record fuzzily matches to sheffield , england . among these rows , select the rows whose type record fuzzily matches to club trophy . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { filter_eq { all_rows ; location ; sheffield , england } ; type ; club trophy } } ; 2 }"
] |
task210-61fb80b15cc6475892306ef37ca7e408
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose film record fuzzily matches to bullets over broadway . among these rows , select the rows whose result record fuzzily matches to nominated . the number of such rows is 2 .
Output:
|
[
"eq { count { filter_eq { filter_eq { all_rows ; film ; bullets over broadway } ; result ; nominated } } ; 2 }"
] |
task210-bbd39768164844c7aa6968c7b8ce45f5
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose writer ( s ) record fuzzily matches to mark james . there is only one such row in the table . the track record of this unqiue row is 4 . the song title record of this unqiue row is moody blue .
Output:
|
[
"and { only { filter_eq { all_rows ; writer ( s ) ; mark james } } ; and { eq { hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; track } ; 4 } ; eq { hop { filter_eq { all_rows ; writer ( s ) ; mark james } ; song title } ; moody blue } } }"
] |
task210-ba1261589add44a99b78b001477bf4f6
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose successor record fuzzily matches to bob livingston ( r ) . take the date successor seated record of this row . select the rows whose successor record fuzzily matches to robert garcía ( d ) . take the date successor seated record of this row . the first record is less than the second record .
Output:
|
[
"less { hop { filter_eq { all_rows ; successor ; bob livingston ( r ) } ; date successor seated } ; hop { filter_eq { all_rows ; successor ; robert garcía ( d ) } ; date successor seated } }"
] |
task210-2dba5e815de34286affc992f696337d3
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the uk broadcast date records of all rows , all of them are equal to 1996 .
Output:
|
[
"all_eq { all_rows ; uk broadcast date ; 1996 }"
] |
task210-8b151e2fb26e482881b9c84f20bd0f5e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose date record fuzzily matches to 14 march 1984 . there is only one such row in the table . the home team record of this unqiue row is derby county .
Output:
|
[
"and { only { filter_eq { all_rows ; date ; 14 march 1984 } } ; eq { hop { filter_eq { all_rows ; date ; 14 march 1984 } ; home team } ; derby county } }"
] |
task210-4387de9eeef541b1b4fbd742920f048a
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose height record is greater than 80 . the number of such rows is 4 .
Output:
|
[
"eq { count { filter_greater { all_rows ; height ; 80 } } ; 4 }"
] |
task210-3e43fe0d70fd4d0bab2ff3a622dd44f5
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose institution record fuzzily matches to mercy college . take the enrollment record of this row . select the rows whose institution record fuzzily matches to dowling college . take the enrollment record of this row . the first record is greater than the second record .
Output:
|
[
"greater { hop { filter_eq { all_rows ; institution ; mercy college } ; enrollment } ; hop { filter_eq { all_rows ; institution ; dowling college } ; enrollment } }"
] |
task210-da002e6d434544c7baf9fda8ce5f28bb
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: the average of the rank record of all rows is 20 .
Output:
|
[
"round_eq { avg { all_rows ; rank } ; 20 }"
] |
task210-627425f32d124905951226e26948bfbe
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose chassis record fuzzily matches to williams fw04 . there is only one such row in the table . the year record of this unqiue row is 1975 . the entrant record of this unqiue row is frank williams racing cars .
Output:
|
[
"and { only { filter_eq { all_rows ; chassis ; williams fw04 } } ; and { eq { hop { filter_eq { all_rows ; chassis ; williams fw04 } ; year } ; 1975 } ; eq { hop { filter_eq { all_rows ; chassis ; williams fw04 } ; entrant } ; frank williams racing cars } } }"
] |
task210-6a04485e5b4e495ca1bc98269dd40796
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose sunday record fuzzily matches to rylan clark . there is only one such row in the table .
Output:
|
[
"only { filter_eq { all_rows ; sunday ; rylan clark } }"
] |
task210-e591cef2a05644c19128c3ee47ca921e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose points record is less than 40 . there is only one such row in the table . the song record of this unqiue row is cold shoulder .
Output:
|
[
"and { only { filter_less { all_rows ; points ; 40 } } ; eq { hop { filter_less { all_rows ; points ; 40 } ; song } ; cold shoulder } }"
] |
task210-73a9034216654e05a801edceb74d437b
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: for the directed by records of all rows , all of them fuzzily match to tyler perry .
Output:
|
[
"all_eq { all_rows ; directed by ; tyler perry }"
] |
task210-2d9e57355ea2474cac590b8723dde246
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose home team score record is greater than 4 . among these rows , select the rows whose venue record fuzzily matches to brunswick street oval . there is only one such row in the table . the home team record of this unqiue row is fitzroy .
Output:
|
[
"and { only { filter_eq { filter_greater { all_rows ; home team score ; 4 } ; venue ; brunswick street oval } } ; eq { hop { filter_eq { filter_greater { all_rows ; home team score ; 4 } ; venue ; brunswick street oval } ; home team } ; fitzroy } }"
] |
task210-2868b6acd9334de8907439e35bf75937
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose away team score record is less than 10 . among these rows , select the rows whose crowd record is less than 40000 . the number of such rows is 3 .
Output:
|
[
"eq { count { filter_less { filter_less { all_rows ; away team score ; 10 } ; crowd ; 40000 } } ; 3 }"
] |
task210-17786d76258b4002843d92a91200bd85
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose position record fuzzily matches to left wing . for the nationality records of these rows , most of them fuzzily match to canada .
Output:
|
[
"most_eq { filter_eq { all_rows ; position ; left wing } ; nationality ; canada }"
] |
task210-81ec9cfb11f74f0694f35f473af0749e
|
Definition: In this task, you are given a natural language interpretation of commands (consist of logical operations) to select relevant rows from the given table. Your job is to generate command (in terms of logical operations) from given natural language interpretation. Define body (contains a collection of statements that define what the this logical operator does) of each logical operator between '{}' parenthesis. Here are the definitions of logical operators that you can use while generating command:
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.
Positive Example 1 -
Input: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Output: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 }
Positive Example 2 -
Input: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Output: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard }
Negative Example 1 -
Input: select the row whose total record of all rows is 3rd maximum . the club record of this row is maidstone united .
Output: eq { hop { nth_argmax { all_rows ; total ; 3 } } ; maidstone united }
Negative Example 2 -
Input: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Output: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china }
Now complete the following example -
Input: select the rows whose goal difference record is less than 0 . the number of such rows is 5 .
Output:
|
[
"eq { count { filter_less { all_rows ; goal difference ; 0 } } ; 5 }"
] |
task210-b9e81a53587b4117bd5a117c2800cd1d
|
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