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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 registered voters record of all rows is 3rd maximum . the city record of this row is encinitas .
Output:
| [
"eq { hop { nth_argmax { all_rows ; registered voters ; 3 } ; city } ; encinitas }"
] | task210-1a60617cf1134c289e5b96d3bc6d98fb |
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 continent record fuzzily matches to asia . the number of such rows is 2 .
Output:
| [
"eq { count { filter_eq { all_rows ; continent ; asia } } ; 2 }"
] | task210-0ebd48019c25490ab8a26d68b4ee8973 |
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 frequency record of all rows is 2200 mhz .
Output:
| [
"round_eq { avg { all_rows ; frequency } ; 2200 mhz }"
] | task210-07238989a7604315a7bf6dd52f1179d2 |
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 1987 . the sum of the notes record of these rows is 4:27:46 .
Output:
| [
"round_eq { sum { filter_eq { all_rows ; year ; 1987 } ; notes } ; 4:27:46 }"
] | task210-8a0d8cf9ac9249e0bc61025646ef6a4d |
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 st pete times forum . select the row whose game record of these rows is 1st minimum . the attendance record of this row is 16104 .
Output:
| [
"eq { hop { nth_argmin { filter_eq { all_rows ; location ; st pete times forum } ; game ; 1 } ; attendance } ; 16104 }"
] | task210-23aa07a5752b47f4be5a3397a5d4e988 |
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 club record fuzzily matches to sporting de gijón . take the points record of this row . select the rows whose club record fuzzily matches to cádiz cf . take the points record of this row . the first record is greater than the second record .
Output:
| [
"greater { hop { filter_eq { all_rows ; club ; sporting de gijón } ; points } ; hop { filter_eq { all_rows ; club ; cádiz cf } ; points } }"
] | task210-43c9e5396b4a4621983823b852c443b2 |
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 days held record of all rows is 196 .
Output:
| [
"eq { nth_min { all_rows ; days held ; 3 } ; 196 }"
] | task210-3c226bc4e5244f089756f2ac6338f2d6 |
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 beirut . among these rows , select the rows whose result record does not match to win . the number of such rows is 2 .
Output:
| [
"eq { count { filter_not_eq { filter_eq { all_rows ; venue ; beirut } ; result ; win } } ; 2 }"
] | task210-4519ff3b72e74506b6033f465a89fbd1 |
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 language record fuzzily matches to yiddish . take the number record of this row . select the rows whose language record fuzzily matches to russian . take the number record of this row . the first record is greater than the second record .
Output:
| [
"greater { hop { filter_eq { all_rows ; language ; yiddish } ; number } ; hop { filter_eq { all_rows ; language ; russian } ; number } }"
] | task210-e8fa7f4b833f42d1b537109f4fd2bc5b |
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 date record of this row is 12 august 2007 .
Output:
| [
"eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; date } ; 12 august 2007 }"
] | task210-64ea62bb5ca6479ea48888e71bd2d198 |
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 sport record fuzzily matches to boxing . among these rows , select the rows whose event record fuzzily matches to men 's light flyweight . the number of such rows is 2 .
Output:
| [
"eq { count { filter_eq { filter_eq { all_rows ; sport ; boxing } ; event ; men 's light flyweight } } ; 2 }"
] | task210-efd74718e8204428b271f468784de82b |
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 mccain % record fuzzily matches to 75.7 % . the number of such rows is 1 .
Output:
| [
"eq { count { filter_eq { all_rows ; mccain % ; 75.7 % } } ; 1 }"
] | task210-893a8bd0754a41b9842bcba2797f5a9e |
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 polyunsaturated fat record is less than 10 % . there is only one such row in the table . the record of this unqiue row is suet .
Output:
| [
"and { only { filter_less { all_rows ; polyunsaturated fat ; 10 % } } ; eq { hop { filter_less { all_rows ; polyunsaturated fat ; 10 % } ; } ; suet } }"
] | task210-a7478f535e7144298c4ce6a1502dd2d4 |
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 nationality records of all rows , all of them fuzzily match to canada .
Output:
| [
"all_eq { all_rows ; nationality ; canada }"
] | task210-bdae776be0d149d9993df0db0d5aac09 |
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 wins record is equal to 0 . the number of such rows is 2 .
Output:
| [
"eq { count { filter_eq { all_rows ; wins ; 0 } } ; 2 }"
] | task210-97313fe0b6eb4cd19607a134b0d24a60 |
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 competition record fuzzily matches to world championships . the number of such rows is 3 .
Output:
| [
"eq { count { filter_eq { all_rows ; competition ; world championships } } ; 3 }"
] | task210-2369f4cd6cb7464581fddf9462c3402c |
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 original air date ( uk ) record of all rows is 1st maximum . the episode title record of this row is loyalties ii .
Output:
| [
"eq { hop { nth_argmax { all_rows ; original air date ( uk ) ; 1 } ; episode title } ; loyalties ii }"
] | task210-ba5e9369b6fd48a0b6791b226783fc9f |
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 disease area records of all rows , most of them fuzzily match to cancer .
Output:
| [
"most_eq { all_rows ; disease area ; cancer }"
] | task210-ae889857b940401592e0072fcd58c693 |
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 nation record fuzzily matches to sweden . take the gold record of this row . select the rows whose nation record fuzzily matches to germany . take the gold record of this row . the first record is greater than the second record . the gold record of the first row is 2 . the gold record of the second row is 1 .
Output:
| [
"and { greater { hop { filter_eq { all_rows ; nation ; sweden } ; gold } ; hop { filter_eq { all_rows ; nation ; germany } ; gold } } ; and { eq { hop { filter_eq { all_rows ; nation ; sweden } ; gold } ; 2 } ; eq { hop { filter_eq { all_rows ; nation ; germany } ; gold } ; 1 } } }"
] | task210-5a2c468192764083bcd1e6748d388034 |
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 surface record fuzzily matches to hard . among these rows , select the rows whose partner record fuzzily matches to magdalena maleeva . there is only one such row in the table . the date record of this unqiue row is july 16 , 1992 .
Output:
| [
"and { only { filter_eq { filter_eq { all_rows ; surface ; hard } ; partner ; magdalena maleeva } } ; eq { hop { filter_eq { filter_eq { all_rows ; surface ; hard } ; partner ; magdalena maleeva } ; date } ; july 16 , 1992 } }"
] | task210-99ff6e3e2f804446a558b9fdc05ccfe9 |
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 united kingdom . take the date record of this row . select the rows whose country record fuzzily matches to united states . take the date record of this row . the first record is less than the second record .
Output:
| [
"less { hop { filter_eq { all_rows ; country ; united kingdom } ; date } ; hop { filter_eq { all_rows ; country ; united states } ; date } }"
] | task210-c3159bcd1f5348dc8cd4bf7944b66605 |
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 attendance record of all rows is 45557.14 .
Output:
| [
"round_eq { avg { all_rows ; attendance } ; 45557.14 }"
] | task210-ea1a0344b83746058e3c7c26aa907624 |
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 player record fuzzily matches to tom watson . take the earnings record of this row . select the rows whose player record fuzzily matches to lee trevino . take the earnings record of this row . the first record is greater than the second record .
Output:
| [
"greater { hop { filter_eq { all_rows ; player ; tom watson } ; earnings } ; hop { filter_eq { all_rows ; player ; lee trevino } ; earnings } }"
] | task210-11be94c5c16f4865997b07e7753c5c40 |
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 winner record fuzzily matches to russell ingall . the number of such rows is 3 .
Output:
| [
"eq { count { filter_eq { all_rows ; winner ; russell ingall } } ; 3 }"
] | task210-78ce7140293944b18dfc5cc49b412f0f |
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 4th . the number of such rows is 2 .
Output:
| [
"eq { count { filter_eq { all_rows ; position ; 4th } } ; 2 }"
] | task210-afddcd0db2fb46c581bf2055cea658d6 |
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 minimum . the player record of this row is ben hogan .
Output:
| [
"eq { hop { argmin { all_rows ; score } ; player } ; ben hogan }"
] | task210-37570b03c5a84a25a1ea65f8bb626a96 |
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 shot pct record is greater than or equal to 80 % . the number of such rows is 3 .
Output:
| [
"eq { count { filter_greater_eq { all_rows ; shot pct ; 80 % } } ; 3 }"
] | task210-5a07a5c495534f0f878c716bdb582c62 |
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 runner - up record fuzzily matches to dynamo moscow . take the season record of this row . select the rows whose runner - up record fuzzily matches to lokomotiv moscow . take the season record of this row . the first record is less than the second record .
Output:
| [
"less { hop { filter_eq { all_rows ; runner - up ; dynamo moscow } ; season } ; hop { filter_eq { all_rows ; runner - up ; lokomotiv moscow } ; season } }"
] | task210-dd02f99e46ae41b2b9db6c4c159b9ce6 |
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 length record of all rows is 2nd minimum . the line record of this row is sofia - dragoman .
Output:
| [
"eq { hop { nth_argmin { all_rows ; length ; 2 } ; line } ; sofia - dragoman }"
] | task210-e1eecd7746db4e4183cbcd65ea5da293 |
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 class record fuzzily matches to dx . take the number in service record of this row . select the rows whose class record fuzzily matches to dsc . take the number in service record of this row . the first record is greater than the second record .
Output:
| [
"greater { hop { filter_eq { all_rows ; class ; dx } ; number in service } ; hop { filter_eq { all_rows ; class ; dsc } ; number in service } }"
] | task210-c2de83f376b84f4eb08ee6dde5c23391 |
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 dec . for the result records of these rows , most of them fuzzily match to win .
Output:
| [
"most_eq { filter_eq { all_rows ; date ; dec } ; result ; win }"
] | task210-28e950cc557b44858382778f7c8c3986 |
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 gender record fuzzily matches to f . among these rows , select the rows whose residence record fuzzily matches to halifax . the number of such rows is 2 .
Output:
| [
"eq { count { filter_eq { filter_eq { all_rows ; gender ; f } ; residence ; halifax } } ; 2 }"
] | task210-68c853caa9ec4359a824ea97a903a30f |
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 toronto maple leafs . the sum of the score record of these rows is 12 .
Output:
| [
"round_eq { sum { filter_eq { all_rows ; opponent ; toronto maple leafs } ; score } ; 12 }"
] | task210-c888cc1881ef4106bc80e063eeae4c4e |
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 november . for the attendance records of these rows , most of them are greater than or equal to 10000 .
Output:
| [
"most_greater_eq { filter_eq { all_rows ; date ; november } ; attendance ; 10000 }"
] | task210-088f4d5f14174331be058b93c20d5c8f |
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 administrative panel record of all rows is maximum . the party record of this row is fine gael .
Output:
| [
"eq { hop { argmax { all_rows ; administrative panel } ; party } ; fine gael }"
] | task210-d567fef1605e4338b79ca0d8f6aeab13 |
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 opponents record fuzzily matches to palamós . select the row whose kick off record of these rows is minimum . the referee record of this row is daudén ibáñez .
Output:
| [
"eq { hop { argmin { filter_eq { all_rows ; opponents ; palamós } ; kick off } ; referee } ; daudén ibáñez }"
] | task210-2090e9cdd5ed4b2ca259b16fbecf5db1 |
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 method record fuzzily matches to rear naked choke . there is only one such row in the table . the opponent record of this unqiue row is helio dipp .
Output:
| [
"and { only { filter_eq { all_rows ; method ; rear naked choke } } ; eq { hop { filter_eq { all_rows ; method ; rear naked choke } ; opponent } ; helio dipp } }"
] | task210-40a40c9e355149e0b06eabad7439d8e4 |
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 san francisco . the number of such rows is 2 .
Output:
| [
"eq { count { filter_eq { all_rows ; venue ; san francisco } } ; 2 }"
] | task210-6542d17540ee4098a0c4c3802d515e33 |
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 player record of this row is james lofton .
Output:
| [
"eq { hop { argmin { all_rows ; pick } ; player } ; james lofton }"
] | task210-65ac1d8247964cc2b2cdd5e603866438 |
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 screen size ( inch ) records of all rows , most of them are greater than or equal to 7 .
Output:
| [
"most_greater_eq { all_rows ; screen size ( inch ) ; 7 }"
] | task210-ead086daaec2415a984bf2345ff3a4da |
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 2nd component record fuzzily matches to acetone . the number of such rows is 3 .
Output:
| [
"eq { count { filter_eq { all_rows ; 2nd component ; acetone } } ; 3 }"
] | task210-f13d0067687b4eac9f0cf44c5c9db1c8 |
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 saskatchewan . among these rows , select the rows whose position record fuzzily matches to k . there is only one such row in the table . the player record of this unqiue row is matt kellett .
Output:
| [
"and { only { filter_eq { filter_eq { all_rows ; college ; saskatchewan } ; position ; k } } ; eq { hop { filter_eq { filter_eq { all_rows ; college ; saskatchewan } ; position ; k } ; player } ; matt kellett } }"
] | task210-14b519968c2d4b339c6471c2f0687b74 |
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 department record is arbitrary . the number of such rows is 7 .
Output:
| [
"eq { count { filter_all { all_rows ; department } } ; 7 }"
] | task210-8418488a8c124b0a91e54d587214993d |
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 tsirion stadium , limassol . take the date record of this row . select the rows whose venue record fuzzily matches to king abdullah stadium , amman . take the date record of this row . the first record is less than the second record .
Output:
| [
"less { hop { filter_eq { all_rows ; venue ; tsirion stadium , limassol } ; date } ; hop { filter_eq { all_rows ; venue ; king abdullah stadium , amman } ; date } }"
] | task210-82f503f45a8c42c4a6ff855f04a292e8 |
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 sets lost record of all rows is 2nd maximum . the team record of this row is far eastern university .
Output:
| [
"eq { hop { nth_argmax { all_rows ; sets lost ; 2 } ; team } ; far eastern university }"
] | task210-a6ce87aad5df4e548285a07cc66f583a |
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 born record of all rows is minimum . the archbishop record of this row is jean baptiste lamy .
Output:
| [
"eq { hop { argmin { all_rows ; born } ; archbishop } ; jean baptiste lamy }"
] | task210-9b4eadeed84a44f5aec6557534bde28e |
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 seating records of all rows , most of them are less than 100000 .
Output:
| [
"most_less { all_rows ; seating ; 100000 }"
] | task210-16789c874e3943198ebd2affe08bf419 |
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 season premiere date records of all rows , all of them fuzzily match to 20 .
Output:
| [
"all_eq { all_rows ; season premiere date ; 20 }"
] | task210-2cb10d1f1eba4c5b8e318ac792d4d488 |
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 races record of all rows is 14.4 .
Output:
| [
"round_eq { avg { all_rows ; races } ; 14.4 }"
] | task210-3972d51d954a40f6b726b4dff67e909c |
End of preview. Expand
in Dataset Viewer.
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task210_logic2text_structured_text_generation
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks},
author={Yizhong Wang and Swaroop Mishra and Pegah Alipoormolabashi and Yeganeh Kordi and Amirreza Mirzaei and Anjana Arunkumar and Arjun Ashok and Arut Selvan Dhanasekaran and Atharva Naik and David Stap and Eshaan Pathak and Giannis Karamanolakis and Haizhi Gary Lai and Ishan Purohit and Ishani Mondal and Jacob Anderson and Kirby Kuznia and Krima Doshi and Maitreya Patel and Kuntal Kumar Pal and Mehrad Moradshahi and Mihir Parmar and Mirali Purohit and Neeraj Varshney and Phani Rohitha Kaza and Pulkit Verma and Ravsehaj Singh Puri and Rushang Karia and Shailaja Keyur Sampat and Savan Doshi and Siddhartha Mishra and Sujan Reddy and Sumanta Patro and Tanay Dixit and Xudong Shen and Chitta Baral and Yejin Choi and Noah A. Smith and Hannaneh Hajishirzi and Daniel Khashabi},
year={2022},
eprint={2204.07705},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2204.07705},
}
More details can also be found in the following paper:
@misc{brüelgabrielsson2024compressserveservingthousands,
title={Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead},
author={Rickard Brüel-Gabrielsson and Jiacheng Zhu and Onkar Bhardwaj and Leshem Choshen and Kristjan Greenewald and Mikhail Yurochkin and Justin Solomon},
year={2024},
eprint={2407.00066},
archivePrefix={arXiv},
primaryClass={cs.DC},
url={https://arxiv.org/abs/2407.00066},
}
Contact Information
For any comments or questions, please email Rickard Brüel Gabrielsson
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