inputs stringlengths 2.3k 3.85k | targets stringlengths 43 473 | _template_idx int64 0 9 | _task_source stringclasses 1
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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 wheth... | select the rows whose defensive record fuzzily matches to matt disher . the number of such rows is 3 .
| 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Given the task definition, example input & output, solve the new input case.
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... | the sum of the loans received , 3q record of all rows is 8550000 . | 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose year record is equal to 2010 . among these rows , select the rows whose recipient record fuzzily matches to the suite life on deck . the number of such rows is 2 . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose club record is arbitrary . the number of such rows is 11 . | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
instruction:
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: ... | select the rows whose club record is arbitrary . the number of such rows is 11 .
| 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose high rebounds record fuzzily matches to wallace . the average of the high rebounds record of these rows is 11 .
| 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose date record fuzzily matches to oct . among these rows , select the rows whose opponent record fuzzily matches to new england patriots . there is only one such row in the table .
| 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the score record of all rows is 143 . | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to 6 . the number of such rows is 2 .
| 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Output: select the rows whose club team record fuzzily matches to plymouth whalers ohl . there is only one such row in the table . the player record of this unqiue row is stefan noesen .
| 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose director record fuzzily matches to pamela fryman . among these rows , select the rows whose original air date record fuzzily matches to april . the number of such rows is 3 .
| 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | select the row whose total record of all rows is minimum . the player record of this row is seve ballesteros . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose year completed record is less than 2000 . among these rows , select the rows whose floors stories record is equal to 12 . the number of such rows is 2 .
| 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose model engine record fuzzily matches to 1.8 duratec he . take the capacity record of this row . select the rows whose model engine record fuzzily matches to 2.0 duratec he . take the capacity record of this row . the first record is less than the second record . | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose wins record is equal to 10 . there is only one such row in the table . the club record of this unqiue row is east bengal club .
| 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
TASK DEFINITION: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. on... | the average of the gold record of all rows is 2.86 .
| 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Output: select the row whose date record of all rows is 2nd maximum . the tournament record of this row is cincinnati , united states .
| 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose 2nd place team record fuzzily matches to nitehawks . the number of such rows is 2 .
| 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Output: select the rows whose region record fuzzily matches to japan . take the date record of this row . select the rows whose region record fuzzily matches to united kingdom . take the date record of this row . the first record is less than the second record .
| 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Output: for the region records of all rows , all of them fuzzily match to colorado .
| 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
instruction:
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: ... | 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 .
| 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose sales record of all rows is maximum . the title record of this row is m . | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | select the row whose time record of all rows is 5th minimum . the athlete record of this row is craig virgin . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose floors record is greater than 30 . the number of such rows is 3 . | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Detailed Instructions: 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
... | select the row whose time record of all rows is 3rd minimum . the country record of this row is united states . | 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose opponent record fuzzily matches to arizona . among these rows , select the rows whose result record fuzzily matches to ot . there is only one such row in the table . | 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | the average of the away team score record of all rows is 14.2 . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose position record fuzzily matches to running back . among these rows , select the rows whose overall record is greater than 100th . there is only one such row in the table . the name record of this unqiue row is david tolomu .
| 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Output: select the rows whose floors record is greater than 30 . the number of such rows is 3 .
| 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the sum of the points record of all rows is 66 .
| 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Detailed Instructions: 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
... | the average of the international tourism expenditure 2011 record of all rows is 4548 billion . | 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose name record fuzzily matches to northern eagle . take the year record of this row . select the rows whose name record fuzzily matches to northern hawk . take the year record of this row . the second record is 15 years larger than the first record .
| 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose nationality record fuzzily matches to united states . the number of such rows is 5 .
****
| 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose win record of all rows is maximum . the played record of this row is 16 . the wins record of this row is 9 . | 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | select the row whose established record of all rows is 2nd maximum . the league record of this row is ahl . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Output: select the rows whose titles record is equal to 1 . the number of such rows is 2 .
| 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Given the task definition, example input & output, solve the new input case.
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... | the average of the round record of all rows is 1.7 . | 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
instruction:
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: ... | the average of the round record of all rows is 1.7 .
| 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the bodyweight record of all rows is 100.55 . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
instruction:
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: ... | select the rows whose surface record fuzzily matches to clay . the number of such rows is 4 .
| 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Given the task definition, example input & output, solve the new input case.
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... | select the rows whose vocalist record fuzzily matches to kanako . there is only one such row in the table . | 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Detailed Instructions: 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
... | the average of the total record of all rows is 19.71 . | 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
instruction:
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: ... | select the row whose opening week nett gross record of all rows is maximum . the movie record of this row is chennai express .
| 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the 2nd run records of all rows , most of them are less than 40 .
| 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose established record of all rows is 2nd maximum . the league record of this row is ahl .
| 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose club record fuzzily matches to sussex . the number of such rows is 3 . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the weeks at 1 record of all rows is 4.8 .
****
| 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the sprints classification records of all rows , most of them fuzzily match to rené weissinger .
| 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose money record of all rows is 4th maximum . the score record of this row is 68 + 68 + 69 + 79 = 284 .
| 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose tournament record fuzzily matches to china . there is only one such row in the table . | 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose position record fuzzily matches to left wing . for the nationality records of these rows , most of them fuzzily match to canada . | 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose name record fuzzily matches to over the deel . take the age record of this row . select the rows whose name record fuzzily matches to captain dibble . take the age record of this row . the first record is less than the second record .
| 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | select the rows whose margin of victory record fuzzily matches to playoff . the number of such rows is 2 . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose position record fuzzily matches to left wing . for the nationality records of these rows , most of them fuzzily match to canada .
| 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the sum of the total g record of all rows is 44 . | 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose margin of victory record fuzzily matches to playoff . the number of such rows is 3 .
| 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the points record of all rows is 14.56 . | 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the partner records of all rows , most of them fuzzily match to app .
| 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Detailed Instructions: 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
... | select the rows whose visitor record fuzzily matches to colorado . the number of such rows is 3 . | 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | select the rows whose candidates record does not match to unopposed . there is only one such row in the table . the incumbent record of this unqiue row is hale boggs . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is finis j garrett . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Solution: the sum of the money record of all rows is 3,164,543 . | 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the final records of all rows , most of them fuzzily match to did not advance .
****
| 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose couple record fuzzily matches to jason edyta . take the score record of this row . select the rows whose couple record fuzzily matches to kristi mark . take the score record of this row . the first record is less than the second record . the score record of the first row is 23 8 , 7 , 8 . the ... | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Output: select the rows whose surface record fuzzily matches to carpet i . there is only one such row in the table . the tournament record of this unqiue row is opole .
| 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose general classification record fuzzily matches to igor antón . among these rows , select the rows whose winner record fuzzily matches to markus fothen . there is only one such row in the table . the stage record of this unqiue row is 5 .
| 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Part 1. 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. ... | for the series records of all rows , most of them fuzzily match to lt . | 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
TASK DEFINITION: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. on... | select the rows whose name record fuzzily matches to marc willers nzl . take the 1st run record of this row . select the rows whose name record fuzzily matches to mike day usa . take the 1st run record of this row . the first record is greater than the second record .
| 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the tournament records of all rows , most of them fuzzily match to 25000 .
| 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose height metres ft record of all rows is maximum . the name record of this row is shard london bridge . | 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose directed by record fuzzily matches to patrick duffy . the number of such rows is 8 .
| 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
instruction:
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: ... | select the rows whose sydney record fuzzily matches to yes . the number of such rows is 13 .
| 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose directed by record fuzzily matches to alison maclean . there is only one such row in the table . the title record of this unqiue row is the river .
| 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose manner of departure record fuzzily matches to mutual consent . the number of such rows is 3 . | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose transmission record fuzzily matches to 8 speed . the number of such rows is 6 . | 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose result record of all rows is maximum . the date record of this row is 9 october 2010 . | 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Solution: select the rows whose away team record fuzzily matches to melbourne . the sum of the crowd record of these rows is 25000 . | 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose laps record is equal to 200 . the number of such rows is 6 . | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose number in service record of all rows is maximum . the class record of this row is dc .
| 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the level record of all rows is 8 .
| 3 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
TASK DEFINITION: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. on... | select the rows whose competition record fuzzily matches to friendly match . the minimum date record of these rows is 7 november 1997 .
| 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose crowd record of all rows is 2nd maximum . the home team record of this row is carlton . | 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Solution: select the rows whose competition record fuzzily matches to friendly match . the minimum date record of these rows is 7 november 1997 . | 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the row whose date record of all rows is 1st minimum . the date record of this row is may 14 , 2008 . | 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose directed by record fuzzily matches to steve buscemi . the number of such rows is 2 . | 9 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose republican ticket record fuzzily matches to frank . the number of such rows is 2 .
****
| 4 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose player record fuzzily matches to adam gilchrist . take the matches record of this row . select the rows whose player record fuzzily matches to steve rixon . take the matches record of this row . the first record is greater than the second record .
| 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose away team record fuzzily matches to melbourne . the sum of the crowd record of these rows is 25000 .
| 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
You will be given a definition of a task first, then an example. Follow the example to solve a new instance of the task.
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.
H... | select the row whose innings record of all rows is maximum . the player record of this row is ricky ponting . | 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
TASK DEFINITION: In this task, you are given commands (in terms of logical operations) to select relevant rows from the given table. Your job is to generate a natural language interpretation of the given command.
Here are the definitions of logical operators:
1. count: returns the number of rows in the view
2. on... | select the rows whose incumbent record fuzzily matches to none district created . the number of such rows is 2 .
| 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose status record fuzzily matches to re elected . the number of such rows is 3 .
| 0 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose date record fuzzily matches to may 2008 . for the original artist records of these rows , all of them fuzzily match to beatles .
| 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | select the rows whose authority record fuzzily matches to state integrated . there is only one such row in the table . the name record of this unqiue row is st joseph s school . | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Teacher: 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: retu... | select the rows whose matches record is less than 10 . among these rows , select the rows whose innings record is greater than 14 . the number of such rows is 2 . | 2 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Given the task definition, example input & output, solve the new input case.
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... | select the rows whose school ihsaa id record fuzzily matches to knox community . take the enrollment record of this row . select the rows whose school ihsaa id record fuzzily matches to culver community . take the enrollment record of this row . the first record is greater than the second record . | 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | for the position records of all rows , most of them are less than 50 . | 6 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Given the task definition, example input & output, solve the new input case.
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... | select the row whose place record of all rows is minimum . the artist record of this row is liam reilly . the song record of this row is somewhere in europe . | 1 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | the average of the score record of all rows is 4.67 . | 8 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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 wheth... | Solution: select the row whose hosted 4 teams since record of all rows is minimum . the metropolitan area record of this row is detroit , michigan . | 5 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
Part 1. 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. ... | the average of the score record of all rows is 3.25 . | 7 | NIv2 | task110_logic2text_sentence_generation | fs_opt |
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