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Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { sum { all_rows ; attendance } ; 203,967 } = true
Output:
| [
"the sum of the attendance record of all rows is 203,967 ."
] | task110-0151ae8134284ed3984d171986035cc8 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; losses } ; 3.43 } = true
Output:
| [
"the average of the losses record of all rows is 3.43 ."
] | task110-57393d710f3d40d0831458b0446426f2 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: greater { hop { filter_eq { all_rows ; player ; b lee } ; wkts } ; hop { filter_eq { all_rows ; player ; z khan } ; wkts } } = true
Output:
| [
"select the rows whose player record fuzzily matches to b lee . take the wkts record of this row . select the rows whose player record fuzzily matches to z khan . take the wkts record of this row . the first record is greater than the second record ."
] | task110-48a529c3f32543db9d6359c1699390f2 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_not_eq { all_rows ; qual 2 ; - } = true
Output:
| [
"for the qual 2 records of all rows , most of them are not equal to ."
] | task110-981f35afd2a44b339b0cad9b35755c41 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; gold ; 1 } } ; 2 } = true
Output:
| [
"select the rows whose gold record is equal to 1 . the number of such rows is 2 ."
] | task110-994bfd463056419489e915b118920fcc |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; number of powiats } ; 2.5 } = true
Output:
| [
"the average of the number of powiats record of all rows is 2.5 ."
] | task110-4f1b71a09ab64f6493f6534db59d073e |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; total } ; 15 } = true
Output:
| [
"the average of the total record of all rows is 15 ."
] | task110-f5b8873e5388409ebf1fed0a83251818 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_less_eq { all_rows ; score ; 3 } = true
Output:
| [
"for the score records of all rows , most of them are less than or equal to 3 ."
] | task110-04f8a4cb07964422a57f76991d9ea6cb |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; opponent ; boston bruins } } ; 2 } = true
Output:
| [
"select the rows whose opponent record fuzzily matches to boston bruins . the number of such rows is 2 ."
] | task110-287218258a5844fcb8cc0f4a240f30c1 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: less { hop { filter_eq { all_rows ; outgoing manager ; karol marko } ; date of vacancy } ; hop { filter_eq { all_rows ; outgoing manager ; ivan vrabec } ; date of vacancy } } = true
Output:
| [
"select the rows whose outgoing manager record fuzzily matches to karol marko . take the date of vacancy record of this row . select the rows whose outgoing manager record fuzzily matches to ivan vrabec . take the date of vacancy record of this row . the first record is less than the second record ."
] | task110-7369b010f3ee4ce786929ac468e39f76 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; overall } ; 125.1 } = true
Output:
| [
"the average of the overall record of all rows is 125.1 ."
] | task110-dc09115ad12f459280e35a49fb38e427 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { greater { hop { filter_eq { all_rows ; home team ; collingwood } ; crowd } ; hop { filter_eq { all_rows ; home team ; carlton } ; crowd } } ; and { eq { hop { filter_eq { all_rows ; home team ; collingwood } ; away team } ; south melbourne } ; eq { hop { filter_eq { all_rows ; home team ; carlton } ; away team } ; geelong } } } = true
Output:
| [
"select the rows whose home team record fuzzily matches to collingwood . take the crowd record of this row . select the rows whose home team record fuzzily matches to carlton . take the crowd record of this row . the first record is greater than the second record . the away team record of the first row is south melbourne . the away team record of the second row is geelong ."
] | task110-a78702373d6641fc8a8f634bb8b12e1f |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmin { all_rows ; 1980 ; 2 } ; greek national account } ; public debt 8 ( billion ) } = true
Output:
| [
"select the row whose 1980 record of all rows is 2nd minimum . the greek national account record of this row is public debt 8 billion ."
] | task110-a3a9443fe619409abba465fa13c53f27 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; pole position ; ayrton senna } } ; 8 } = true
Output:
| [
"select the rows whose pole position record fuzzily matches to ayrton senna . the number of such rows is 8 ."
] | task110-18ab7bddcffd41ceadeab04adfc61620 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmin { all_rows ; release date ; 1 } ; developer ( s ) } ; valve corporation } = true
Output:
| [
"select the row whose release date record of all rows is 1st minimum . the developer s record of this row is valve corporation ."
] | task110-45f16bb9b3514b9ca4507b7bd0e7a869 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; gp ; 56 } } ; 2 } = true
Output:
| [
"select the rows whose gp record is equal to 56 . the number of such rows is 2 ."
] | task110-21ecd8da85d64c758bcd0f7e53f6c6c0 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: greater { hop { filter_eq { all_rows ; animal name ; the rabbits } ; tv seasons } ; hop { filter_eq { all_rows ; animal name ; mole } ; tv seasons } } = true
Output:
| [
"select the rows whose animal name record fuzzily matches to the rabbits . take the tv seasons record of this row . select the rows whose animal name record fuzzily matches to mole . take the tv seasons record of this row . the first record is greater than the second record ."
] | task110-54bed963e48a4f63a2eb9897eb2b65a0 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_not_eq { all_rows ; status ; re - elected } } ; eq { hop { filter_not_eq { all_rows ; status ; re - elected } ; incumbent } ; rick santorum } } = true
Output:
| [
"select the rows whose status record does not match to re elected . there is only one such row in the table . the incumbent record of this unqiue row is rick santorum ."
] | task110-92fda1dbb935490186257c90a3aac565 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; season outcome ; div i playoffs } } ; 2 } = true
Output:
| [
"select the rows whose season outcome record fuzzily matches to div i playoffs . the number of such rows is 2 ."
] | task110-2fc0d3b847d74031bfd7bde07477ebb4 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; commissioned ; 1930 } } ; 7 } = true
Output:
| [
"select the rows whose commissioned record fuzzily matches to 1930 . the number of such rows is 7 ."
] | task110-26ed9151f85f470589037cd43e171f92 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_less { filter_greater { all_rows ; round ; 3 } ; overall ; 200 } } ; 3 } = true
Output:
| [
"select the rows whose round record is greater than 3 . among these rows , select the rows whose overall record is less than 200 . the number of such rows is 3 ."
] | task110-a418e11ed1ff4c2a88764c4bbc9c05c0 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: only { filter_less { all_rows ; attendance ; 10000 } } = true
Output:
| [
"select the rows whose attendance record is less than 10000 . there is only one such row in the table ."
] | task110-d5b231a617b944d0a6be6efa9429d1f9 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; earnings } ; 424466 } = true
Output:
| [
"the average of the earnings record of all rows is 424466 ."
] | task110-823c0e8be6374dbdaec7a68f9395d695 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_all { all_rows ; nation } } ; 16 } = true
Output:
| [
"select the rows whose nation record is arbitrary . the number of such rows is 16 ."
] | task110-9b68d84ced5a40d0abe97a308e5b4358 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmax { all_rows ; attendance / g ; 2 } ; season } ; 2005 } = true
Output:
| [
"select the row whose attendance g record of all rows is 2nd maximum . the season record of this row is 2005 ."
] | task110-553b494b2afe4f3fa9e2242666919423 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_less { all_rows ; attendance ; 17000 } = true
Output:
| [
"for the attendance records of all rows , most of them are less than 17000 ."
] | task110-ee53d0bbc92c4e23830356831982df87 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_less { all_rows ; population ( in 2008 ) ; 1000 } } ; eq { hop { filter_less { all_rows ; population ( in 2008 ) ; 1000 } ; suburb } ; o'malley } } = true
Output:
| [
"select the rows whose population in 2008 record is less than 1000 . there is only one such row in the table . the suburb record of this unqiue row is omalley ."
] | task110-9b69baf75fbb450fb8b00f1b2ca60b2d |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { sum { all_rows ; against } ; 49 } = true
Output:
| [
"the sum of the against record of all rows is 49 ."
] | task110-547c326c337c4eeeb7f9f4e254a0f72a |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmax { filter_eq { all_rows ; position ; fw } ; number ; 2 } ; player } ; fwayo tembo } = true
Output:
| [
"select the rows whose position record fuzzily matches to fw . select the row whose number record of these rows is 2nd maximum . the player record of this row is fwayo tembo ."
] | task110-3169f3363bb34128a8e720c24726858e |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; partner ; stephanie vogt } } ; 2 } = true
Output:
| [
"select the rows whose partner record fuzzily matches to stephanie vogt . the number of such rows is 2 ."
] | task110-e19c814eefdf49ec9db84b9a244224b9 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: less { hop { filter_eq { all_rows ; opponent ; jason st louis } ; time } ; hop { filter_eq { all_rows ; opponent ; mike swick } ; time } } = true
Output:
| [
"select the rows whose opponent record fuzzily matches to jason st louis . take the time record of this row . select the rows whose opponent record fuzzily matches to mike swick . take the time record of this row . the first record is less than the second record ."
] | task110-742a0b2875054060b149fa7c720a7c8b |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_eq { all_rows ; language ; hindi } = true
Output:
| [
"for the language records of all rows , most of them fuzzily match to hindi ."
] | task110-dac0fdf3a280409fb838ec601c374935 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { sum { filter_less { all_rows ; decile ; 8 } ; roll } ; 770 } = true
Output:
| [
"select the rows whose decile record is less than 8 . the sum of the roll record of these rows is 770 ."
] | task110-382be2f0281442d4b01f6ef3240df4cc |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_greater { filter_eq { all_rows ; location ; st pete times forum } ; attendance ; 16000 } } ; 5 } = true
Output:
| [
"select the rows whose location record fuzzily matches to st pete times forum . among these rows , select the rows whose attendance record is greater than 16000 . the number of such rows is 5 ."
] | task110-703922c0b5684ef187de53e3703c8d7a |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; earpads ; comfort pads } } ; 4 } = true
Output:
| [
"select the rows whose earpads record fuzzily matches to comfort pads . the number of such rows is 4 ."
] | task110-ca532bb632af431abe29e3b26b7c331f |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_eq { all_rows ; status ; display only } } ; eq { hop { filter_eq { all_rows ; status ; display only } ; number } ; 1 } } = true
Output:
| [
"select the rows whose status record fuzzily matches to display only . there is only one such row in the table . the number record of this unqiue row is 1 ."
] | task110-e48d97ef2ccb45eaba0d822616370484 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_eq { all_rows ; power kw ; 10 kw } = true
Output:
| [
"for the power kw records of all rows , most of them fuzzily match to 10 kw ."
] | task110-76fdac4ab97d47d388ae10b46eff12d5 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmin { all_rows ; hosted 4 teams since } ; metropolitan area } ; detroit , michigan } = true
Output:
| [
"select the row whose hosted 4 teams since record of all rows is minimum . the metropolitan area record of this row is detroit , michigan ."
] | task110-0ba587051c7b451ba8aac0e60f8364c7 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmax { all_rows ; total ; 3 } ; nation } ; mongolia } = true
Output:
| [
"select the row whose total record of all rows is 3rd maximum . the nation record of this row is mongolia ."
] | task110-8f438d5e30c14e2baba30c446e8a8b41 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_eq { all_rows ; ties ; 3 } } ; eq { hop { filter_eq { all_rows ; ties ; 3 } ; season } ; 2008 } } = true
Output:
| [
"select the rows whose ties record is equal to 3 . there is only one such row in the table . the season record of this unqiue row is 2008 ."
] | task110-07896dd2097f49b89147803268250694 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; 2010 ; sf } } ; 2 } = true
Output:
| [
"select the rows whose 2010 record fuzzily matches to sf . the number of such rows is 2 ."
] | task110-aa33bd6b731c4e348a564fd1e5ebc58d |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: greater { hop { filter_eq { all_rows ; municipality ; san miguel } ; no of barangays } ; hop { filter_eq { all_rows ; municipality ; gigmoto } ; no of barangays } } = true
Output:
| [
"select the rows whose municipality record fuzzily matches to san miguel . take the no of barangays record of this row . select the rows whose municipality record fuzzily matches to gigmoto . take the no of barangays record of this row . the first record is greater than the second record ."
] | task110-616fc3899d0f4aafac28cd11161456c8 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_less { filter_less { all_rows ; points ; 20 } ; lost ; 10 } = true
Output:
| [
"select the rows whose points record is less than 20 . for the lost records of these rows , most of them are less than 10 ."
] | task110-5d97b1a7234243ca88e9e8b4f77bfe52 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: most_eq { all_rows ; manner ; sacked } = true
Output:
| [
"for the manner records of all rows , most of them fuzzily match to sacked ."
] | task110-356d048d381e42a4bf0f151deddf4fc1 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_all { all_rows ; season } } ; 6 } = true
Output:
| [
"select the rows whose season record is arbitrary . the number of such rows is 6 ."
] | task110-5fce43d73b75491fae107706c88752fc |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: greater { hop { filter_eq { all_rows ; name ; víctor valdés } ; games } ; hop { filter_eq { all_rows ; name ; joan segarra } ; games } } = true
Output:
| [
"select the rows whose name record fuzzily matches to víctor valdés . take the games record of this row . select the rows whose name record fuzzily matches to joan segarra . take the games record of this row . the first record is greater than the second record ."
] | task110-3471f662659046abb87401aae94507ae |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_all { all_rows ; episode } } ; 13 } = true
Output:
| [
"select the rows whose episode record is arbitrary . the number of such rows is 13 ."
] | task110-456a2cdc7d1c448b905ef7dd66f29e11 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: round_eq { avg { all_rows ; crowd } ; 13916 } = true
Output:
| [
"the average of the crowd record of all rows is 13916 ."
] | task110-127d065d627845a0abc88e177a55ee4b |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: and { only { filter_eq { all_rows ; result ; lost re - election republican gain } } ; eq { hop { filter_eq { all_rows ; result ; lost re - election republican gain } ; incumbent } ; dixie gilmer } } = true
Output:
| [
"select the rows whose result record fuzzily matches to lost re election republican gain . there is only one such row in the table . the incumbent record of this unqiue row is dixie gilmer ."
] | task110-7d564fda94cb46f0b705a336678fde7c |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { argmax { all_rows ; played } ; manager } ; juan carlos chávez } = true
Output:
| [
"select the row whose played record of all rows is maximum . the manager record of this row is juan carlos chávez ."
] | task110-b81806c6853646fc8ef34af30f0e5625 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { count { filter_eq { all_rows ; innings ; 8 } } ; 3 } = true
Output:
| [
"select the rows whose innings record is equal to 8 . the number of such rows is 3 ."
] | task110-7b4d81810d4d457eaf0f16f283404f8f |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: greater { hop { filter_eq { all_rows ; driver / passenger ; daniãl willemsen / sven verbrugge 1 } ; points } ; hop { filter_eq { all_rows ; driver / passenger ; janis daiders / lauris daiders } ; points } } = true
Output:
| [
"select the rows whose driver passenger record fuzzily matches to daniãl willemsen sven verbrugge 1 . take the points record of this row . select the rows whose driver passenger record fuzzily matches to janis daiders lauris daiders . take the points record of this row . the first record is greater than the second record ."
] | task110-4723c47757354c39ae02b5c49321d722 |
Definition: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. only: returns whether there is exactly one row in the view
3. hop: returns the value under the header column of the row
4. and: returns the boolean operation result of two arguments
5. max/min/avg/sum: returns the max/min/average/sum of the values under the header column
6. nth max/nth min: returns the n-th max/n-th min of the values under the header column
7. argmax/argmin: returns the row with the max/min value in header column
8. nth argmax/nth argmin: returns the row with the n-th max/min value in header column
9. eq/not eq: returns if the two arguments are equal
10. round eq: returns if the two arguments are roughly equal under certain tolerance
11. greater/less: returns if argument 1 is greater/less than argument 2
12. diff: returns the difference between two arguments
13. filter eq/not eq: returns the subview whose values under the header column is equal/not equal to argument 3
14. filter greater/less: returns the subview whose values under the header column is greater/less than argument 3
15. filter greater eq /less eq: returns the subview whose values under the header column is greater/less or equal than argument 3
16. filter all: returns the view itself for the case of describing the whole table
17. all eq/not eq: returns whether all the values under the header column are equal/not equal to argument 3
18. all greater/less: returns whether all the values under the header column are greater/less than argument 3
19. all greater eq/less eq: returns whether all the values under the header column are greater/less or equal to argument 3
20. most eq/not eq: returns whether most of the values under the header column are equal/not equal to argument 3
21. most greater/less: returns whether most of the values under the header column are greater/less than argument 3
22. most greater eq/less eq: returns whether most of the values under the header column are greater/less or equal to argument 3
Positive Example 1 -
Input: eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; competition } ; danish superliga 2005 - 06 } = true
Output: select the row whose attendance record of all rows is 3rd maximum. the competition record of this row is danish superliga 2005-06.
Positive Example 2 -
Input: eq { hop { argmax { all_rows ; duration } ; actor } ; lesley saweard } = true
Output: select the row whose duration record of all rows is maximum. the actor record of this row is lesley saweard.
Negative Example 1 -
Input: round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; -7.6 } = true
Output: select the rows whose name of county record fuzzily matches to veszprém. take the area (km square) record of this row. select the rows whose name of county record fuzzily matches to tolna.
Negative Example 2 -
Input: eq { hop { nth_argmax { all_rows ; goal gain ; 3 } ; team } ; south china } = true
Output: select the row whose goal gain record of all rows is 3rd maximum. the team record of this row is india.
Now complete the following example -
Input: eq { hop { nth_argmax { all_rows ; caps ; 3 } ; player } ; kyle beckerman } = true
Output:
| [
"select the row whose caps record of all rows is 3rd maximum . the player record of this row is kyle beckerman ."
] | task110-3c37b0d13eb04b58afa5e64a3500618d |
End of preview. Expand
in Dataset Viewer.
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task110_logic2text_sentence_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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