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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 |
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 ; crowd ; 2 } ; home team } ; adelaide 36ers } = true
Output:
| [
"select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is adelaide 36ers ."
] | task110-33fe817de7e545adab032c25d82e346e |
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 { filter_greater_eq { all_rows ; period ; 2000 } ; win % } ; manager } ; voit talgaev } = true
Output:
| [
"select the rows whose period record is greater than or equal to 2000 . select the row whose win record of these rows is maximum . the manager record of this row is voit talgaev ."
] | task110-76eb54fe947942f6b82b921cca22a154 |
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 ; production code ; 2 } ; episode } ; 809 } = true
Output:
| [
"select the row whose production code record of all rows is 2nd maximum . the episode record of this row is 809 ."
] | task110-dc695e6a9ff6484ab62d2894d373e12c |
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: all_eq { all_rows ; venue ; national stadium , tokyo , tokyo } = true
Output:
| [
"for the venue records of all rows , all of them fuzzily match to national stadium , tokyo , tokyo ."
] | task110-086188938fae483986d093450709c065 |
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 ; ship ; lützow } ; total } ; hop { filter_eq { all_rows ; ship ; seydlitz } ; total } } = true
Output:
| [
"select the rows whose ship record fuzzily matches to lützow . take the total record of this row . select the rows whose ship record fuzzily matches to seydlitz . take the total record of this row . the first record is greater than the second record ."
] | task110-2cdaa7be17dc4392937dfb6170dd5ec6 |
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 ; lost } ; 28.2 } = true
Output:
| [
"the average of the lost record of all rows is 28.2 ."
] | task110-dc56f29c39594e288ca8620e642f225e |
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 ; tournaments ; 2 } ; name } ; kyokunankai } = true
Output:
| [
"select the row whose tournaments record of all rows is 2nd maximum . the name record of this row is kyokunankai ."
] | task110-5fd17703edf34bafbe67dac57aad077f |
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 ; distance } ; race } ; cox plate } = true
Output:
| [
"select the row whose distance record of all rows is maximum . the race record of this row is cox plate ."
] | task110-c00d61dd0b6449b0af44c5e6f4654172 |
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 ; attendance } ; date } ; 19th } = true
Output:
| [
"select the row whose attendance record of all rows is maximum . the date record of this row is 19th ."
] | task110-f9096952ba9b496b9c31cd81bd1f6e4a |
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 ; stages } ; name } ; air21 tour pilipinas } = true
Output:
| [
"select the row whose stages record of all rows is maximum . the name record of this row is air21 tour pilipinas ."
] | task110-b5ae62c1e6074adbb8d405905dce7366 |
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 ; college ; mississippi } } ; eq { hop { filter_eq { all_rows ; college ; mississippi } ; player } ; allen brown } } = true
Output:
| [
"select the rows whose college record fuzzily matches to mississippi . there is only one such row in the table . the player record of this unqiue row is allen brown ."
] | task110-ecdfa5cf3fd74f169f564b7cbd8e47c8 |
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 ; points } ; 626 } = true
Output:
| [
"the sum of the points record of all rows is 626 ."
] | task110-d1f0932f2c0642198caf4ef058aa48f1 |
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 ; chassis ; lola t370 } } ; eq { hop { filter_eq { all_rows ; chassis ; lola t370 } ; year } ; 1974 } } = true
Output:
| [
"select the rows whose chassis record fuzzily matches to lola t370 . there is only one such row in the table . the year record of this unqiue row is 1974 ."
] | task110-f5089cfa45bd4a7db3a66504bdbe909d |
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 ; payout ( us ) } ; 16,030,000 } = true
Output:
| [
"the sum of the payout us record of all rows is 16,030,000 ."
] | task110-62d713fa60fc4c34b0e006289adc2949 |
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 ; round } ; 8 } = true
Output:
| [
"the sum of the round record of all rows is 8 ."
] | task110-cde3ab6cefd24e83ad3b843f9d920f65 |
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 ; team ; indians } ; division record } ; hop { filter_eq { all_rows ; team ; blue raiders } ; division record } } = true
Output:
| [
"select the rows whose team record fuzzily matches to indians . take the division record record of this row . select the rows whose team record fuzzily matches to blue raiders . take the division record record of this row . the first record is greater than the second record ."
] | task110-926fe707371a4841ba38e60c8415fb59 |
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 { all_rows ; crowd ; 10000 } } ; 2 } = true
Output:
| [
"select the rows whose crowd record is greater than 10000 . the number of such rows is 2 ."
] | task110-19e58395dcf0490c95df5beea849bf8c |
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 ; money raised , 2q } ; 10,369,822.5 } = true
Output:
| [
"the average of the money raised , 2q record of all rows is 10,369,822.5 ."
] | task110-ce997942205c4da59ff37a7d9cf56e8a |
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 ; st louis blues } } ; 2 } = true
Output:
| [
"select the rows whose opponent record fuzzily matches to st louis blues . the number of such rows is 2 ."
] | task110-f8a99b7aac5a42159c2f867ce199bb07 |
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_eq { all_rows ; broadcast ; espn } ; attendance ; 100000 } = true
Output:
| [
"select the rows whose broadcast record fuzzily matches to espn . for the attendance records of these rows , most of them are less than 100000 ."
] | task110-79eea823384f45178ab1f14d4a1bf4f4 |
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 { max { filter_eq { all_rows ; match points ; 2 - 2 } ; points margin } ; 20 } = true
Output:
| [
"select the rows whose match points record fuzzily matches to 2 2 . the maximum points margin record of these rows is 20 ."
] | task110-cb5e0f31cc3d4d2cad6f83054676ef59 |
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 ; best ; 59.999 } = true
Output:
| [
"for the best records of all rows , most of them are less than 59.999 ."
] | task110-f337cb6c913846e1868da3195721bb63 |
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 ; gymnast ; kor } } ; 2 } = true
Output:
| [
"select the rows whose gymnast record fuzzily matches to kor . the number of such rows is 2 ."
] | task110-a3a99ba35c554d7abdca56dbd14cb5e3 |
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 ; director ; sharon gosling } = true
Output:
| [
"for the director records of all rows , most of them fuzzily match to sharon gosling ."
] | task110-23949fcf140c4826a9d22b78ed91727b |
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 ; earnings ; 560000 } } ; eq { hop { filter_less { all_rows ; earnings ; 560000 } ; player } ; gene littler } } = true
Output:
| [
"select the rows whose earnings record is less than 560000 . there is only one such row in the table . the player record of this unqiue row is gene littler ."
] | task110-ad925cff02bf42d58697f12de1df9419 |
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 ; population ( 2011 ) ; 2 } ; urban settlement } ; ruma } = true
Output:
| [
"select the row whose population 2011 record of all rows is 2nd maximum . the urban settlement record of this row is ruma ."
] | task110-1f7a14696d9e410fa4f59e05c7eb1633 |
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 ; points } ; artist } ; marlen angelidou } = true
Output:
| [
"select the row whose points record of all rows is maximum . the artist record of this row is marlen angelidou ."
] | task110-80b50f5ae7aa476db0257d48dd0eb7b7 |
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 ; quantity made } ; 151 } = true
Output:
| [
"the sum of the quantity made record of all rows is 151 ."
] | task110-2d0412fc453f401290924db12d72afb2 |
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 ; date introduced ; june } } ; 5 } = true
Output:
| [
"select the rows whose date introduced record fuzzily matches to june . the number of such rows is 5 ."
] | task110-e7f80da4478f4d30b94f718992ddb72d |
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 ; score } ; 1554 } = true
Output:
| [
"the sum of the score record of all rows is 1554 ."
] | task110-ff84160c64f9486baa2be21883a0c15a |
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 ; population ( 2011 ) ; 2 } ; settlement } ; aleksandrovo } = true
Output:
| [
"select the row whose population 2011 record of all rows is 2nd maximum . the settlement record of this row is aleksandrovo ."
] | task110-203a8af7518548eba1fbe495964ec2fa |
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 ; opponents } ; opponent } ; penn state } = true
Output:
| [
"select the row whose opponents record of all rows is maximum . the opponent record of this row is penn state ."
] | task110-05eee2f1b1a74fc48ba08b6c436fe6f4 |
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 ; indigenous mining production 2006 ; 0 } } ; 4 } = true
Output:
| [
"select the rows whose indigenous mining production 2006 record is equal to 0 . the number of such rows is 4 ."
] | task110-eea883a8bcef4529bae00391a8d1b898 |
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 ; first elected ; 1801 } } ; eq { hop { filter_eq { all_rows ; first elected ; 1801 } ; incumbent } ; john smith } } = true
Output:
| [
"select the rows whose first elected record is equal to 1801 . there is only one such row in the table . the incumbent record of this unqiue row is john smith ."
] | task110-8308072855e04d4d8e45643518472242 |
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 ; bronze } ; nation } ; spain } = true
Output:
| [
"select the row whose bronze record of all rows is maximum . the nation record of this row is spain ."
] | task110-9570014597f34c7492a2105b3260a3c7 |
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 ; reason for change ; contested election } } ; eq { hop { filter_eq { all_rows ; reason for change ; contested election } ; vacator } ; josã m gallegos ( d ) } } = true
Output:
| [
"select the rows whose reason for change record fuzzily matches to contested election . there is only one such row in the table . the vacator record of this unqiue row is josã m gallegos d ."
] | task110-9ec80e1f85084e3a97b0e89aa518d350 |
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 ; visitor ; chicago black hawks } } ; 3 } = true
Output:
| [
"select the rows whose visitor record fuzzily matches to chicago black hawks . the number of such rows is 3 ."
] | task110-a80bd661e969474fa42352b4825ed731 |
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 ; winning constructor ; bugatti } } ; 4 } = true
Output:
| [
"select the rows whose winning constructor record fuzzily matches to bugatti . the number of such rows is 4 ."
] | task110-0b9ce1563fef466abecab88d08b71561 |
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 ; score } ; 4577 } = true
Output:
| [
"the sum of the score record of all rows is 4577 ."
] | task110-7411af1b760b4496bf07e0036436005a |
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 ; date first lit ; 1 } ; lighthouse } ; pasig river light ( 1 ) } = true
Output:
| [
"select the row whose date first lit record of all rows is 1st minimum . the lighthouse record of this row is pasig river light 1 ."
] | task110-72d945120da944cd8031e0734281e3e9 |
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 ; nationality ; usa } } ; eq { hop { filter_eq { all_rows ; nationality ; usa } ; athlete } ; chaunté lowe } } = true
Output:
| [
"select the rows whose nationality record fuzzily matches to usa . there is only one such row in the table . the athlete record of this unqiue row is chaunté lowe ."
] | task110-cecaa558f4034b3894a89353892a5b2f |
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 ; district ; belize } = true
Output:
| [
"for the district records of all rows , most of them fuzzily match to belize ."
] | task110-2d9bbeaa3f734bb79b23b6f74cfafec0 |
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 ; area } ; rr romaja } ; gyeongsangbuk } = true
Output:
| [
"select the row whose area record of all rows is maximum . the rr romaja record of this row is gyeongsangbuk ."
] | task110-b70a2aabd4cd45a38501a34ec69c83ed |
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 ; silver } ; nation } ; cyprus } = true
Output:
| [
"select the row whose silver record of all rows is maximum . the nation record of this row is cyprus ."
] | task110-2333f2ffd45242c69bb6a2695c7bbf85 |
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 ; genre ; sitcom } } ; 2 } = true
Output:
| [
"select the rows whose genre record fuzzily matches to sitcom . the number of such rows is 2 ."
] | task110-a68e879d26f04290930b830d3dde04a7 |
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 ; points } ; 16 } = true
Output:
| [
"the sum of the points record of all rows is 16 ."
] | task110-b67eb9487e9e4195b5b609e64a205ec6 |
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 ; date ; 1 } ; opposing team } ; wellington } = true
Output:
| [
"select the row whose date record of all rows is 1st minimum . the opposing team record of this row is wellington ."
] | task110-30e91e9a158041c1b181e8ebc8f773f7 |