Convert dataset to Parquet

#3
by albertvillanova HF staff - opened
Files changed (39) hide show
  1. README.md +291 -16
  2. mode=first,char_skip=25/adversarial-00000-of-00001.parquet +3 -0
  3. mode=first,char_skip=25/buzzdev-00000-of-00001.parquet +3 -0
  4. mode=first,char_skip=25/buzztest-00000-of-00001.parquet +3 -0
  5. mode=first,char_skip=25/buzztrain-00000-of-00001.parquet +3 -0
  6. mode=first,char_skip=25/guessdev-00000-of-00001.parquet +3 -0
  7. mode=first,char_skip=25/guesstest-00000-of-00001.parquet +3 -0
  8. mode=first,char_skip=25/guesstrain-00000-of-00001.parquet +3 -0
  9. mode=full,char_skip=25/adversarial-00000-of-00001.parquet +3 -0
  10. mode=full,char_skip=25/buzzdev-00000-of-00001.parquet +3 -0
  11. mode=full,char_skip=25/buzztest-00000-of-00001.parquet +3 -0
  12. mode=full,char_skip=25/buzztrain-00000-of-00001.parquet +3 -0
  13. mode=full,char_skip=25/guessdev-00000-of-00001.parquet +3 -0
  14. mode=full,char_skip=25/guesstest-00000-of-00001.parquet +3 -0
  15. mode=full,char_skip=25/guesstrain-00000-of-00001.parquet +3 -0
  16. mode=runs,char_skip=25/adversarial-00000-of-00001.parquet +3 -0
  17. mode=runs,char_skip=25/buzzdev-00000-of-00001.parquet +3 -0
  18. mode=runs,char_skip=25/buzztest-00000-of-00001.parquet +3 -0
  19. mode=runs,char_skip=25/buzztrain-00000-of-00002.parquet +3 -0
  20. mode=runs,char_skip=25/buzztrain-00001-of-00002.parquet +3 -0
  21. mode=runs,char_skip=25/guessdev-00000-of-00001.parquet +3 -0
  22. mode=runs,char_skip=25/guesstest-00000-of-00001.parquet +3 -0
  23. mode=runs,char_skip=25/guesstrain-00000-of-00008.parquet +3 -0
  24. mode=runs,char_skip=25/guesstrain-00001-of-00008.parquet +3 -0
  25. mode=runs,char_skip=25/guesstrain-00002-of-00008.parquet +3 -0
  26. mode=runs,char_skip=25/guesstrain-00003-of-00008.parquet +3 -0
  27. mode=runs,char_skip=25/guesstrain-00004-of-00008.parquet +3 -0
  28. mode=runs,char_skip=25/guesstrain-00005-of-00008.parquet +3 -0
  29. mode=runs,char_skip=25/guesstrain-00006-of-00008.parquet +3 -0
  30. mode=runs,char_skip=25/guesstrain-00007-of-00008.parquet +3 -0
  31. mode=sentences,char_skip=25/adversarial-00000-of-00001.parquet +3 -0
  32. mode=sentences,char_skip=25/buzzdev-00000-of-00001.parquet +3 -0
  33. mode=sentences,char_skip=25/buzztest-00000-of-00001.parquet +3 -0
  34. mode=sentences,char_skip=25/buzztrain-00000-of-00001.parquet +3 -0
  35. mode=sentences,char_skip=25/guessdev-00000-of-00001.parquet +3 -0
  36. mode=sentences,char_skip=25/guesstest-00000-of-00001.parquet +3 -0
  37. mode=sentences,char_skip=25/guesstrain-00000-of-00002.parquet +3 -0
  38. mode=sentences,char_skip=25/guesstrain-00001-of-00002.parquet +3 -0
  39. qanta.py +0 -289
README.md CHANGED
@@ -1,15 +1,14 @@
1
  ---
2
  annotations_creators:
3
  - machine-generated
4
- language:
5
- - en
6
  language_creators:
7
  - found
 
 
8
  license:
9
  - unknown
10
  multilinguality:
11
  - monolingual
12
- pretty_name: Quizbowl
13
  size_categories:
14
  - 100K<n<1M
15
  source_datasets:
@@ -18,9 +17,11 @@ task_categories:
18
  - question-answering
19
  task_ids: []
20
  paperswithcode_id: quizbowl
 
21
  tags:
22
  - quizbowl
23
  dataset_info:
 
24
  features:
25
  - name: id
26
  dtype: string
@@ -66,31 +67,305 @@ dataset_info:
66
  dtype: string
67
  - name: year
68
  dtype: int32
69
- config_name: mode=first,char_skip=25
70
  splits:
71
- - name: adversarial
72
- num_bytes: 1258844
73
- num_examples: 1145
 
 
 
 
 
 
74
  - name: buzzdev
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- num_bytes: 1553636
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  num_examples: 1161
 
 
 
77
  - name: buzztest
78
- num_bytes: 2653425
79
  num_examples: 1953
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
80
  - name: buzztrain
81
- num_bytes: 19699736
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  num_examples: 16706
83
  - name: guessdev
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- num_bytes: 1414882
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  num_examples: 1055
 
 
 
86
  - name: guesstest
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- num_bytes: 2997123
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  num_examples: 2151
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
89
  - name: guesstrain
90
- num_bytes: 117599750
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- num_examples: 96221
92
- download_size: 170754918
93
- dataset_size: 147177396
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
94
  ---
95
 
96
  # Dataset Card for "qanta"
 
1
  ---
2
  annotations_creators:
3
  - machine-generated
 
 
4
  language_creators:
5
  - found
6
+ language:
7
+ - en
8
  license:
9
  - unknown
10
  multilinguality:
11
  - monolingual
 
12
  size_categories:
13
  - 100K<n<1M
14
  source_datasets:
 
17
  - question-answering
18
  task_ids: []
19
  paperswithcode_id: quizbowl
20
+ pretty_name: Quizbowl
21
  tags:
22
  - quizbowl
23
  dataset_info:
24
+ - config_name: mode=first,char_skip=25
25
  features:
26
  - name: id
27
  dtype: string
 
67
  dtype: string
68
  - name: year
69
  dtype: int32
 
70
  splits:
71
+ - name: guesstrain
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+ num_bytes: 117599150
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+ num_examples: 96221
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+ - name: buzztrain
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+ num_bytes: 19699616
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+ num_examples: 16706
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+ - name: guessdev
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+ num_bytes: 1414822
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+ num_examples: 1055
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  - name: buzzdev
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+ num_bytes: 1553576
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  num_examples: 1161
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+ - name: guesstest
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+ num_bytes: 2997063
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+ num_examples: 2151
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  - name: buzztest
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+ num_bytes: 2653365
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  num_examples: 1953
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+ - name: adversarial
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+ num_bytes: 1258784
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+ num_examples: 1145
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+ download_size: 90840024
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+ dataset_size: 147176376
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+ - config_name: mode=full,char_skip=25
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+ features:
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+ - name: id
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+ dtype: string
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+ - name: qanta_id
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+ dtype: int32
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+ - name: proto_id
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+ dtype: string
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+ - name: qdb_id
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+ dtype: int32
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+ - name: dataset
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+ dtype: string
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+ - name: text
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+ dtype: string
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+ - name: full_question
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+ dtype: string
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+ - name: first_sentence
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+ dtype: string
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+ - name: char_idx
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+ dtype: int32
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+ - name: sentence_idx
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+ dtype: int32
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+ - name: tokenizations
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+ sequence:
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+ sequence: int32
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+ length: 2
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+ - name: answer
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+ dtype: string
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+ - name: page
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+ dtype: string
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+ - name: raw_answer
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+ dtype: string
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+ - name: fold
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+ dtype: string
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+ - name: gameplay
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+ dtype: bool
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+ - name: category
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+ dtype: string
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+ - name: subcategory
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+ dtype: string
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+ - name: tournament
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+ dtype: string
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+ - name: difficulty
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+ dtype: string
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+ - name: year
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+ dtype: int32
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+ splits:
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+ - name: guesstrain
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+ num_bytes: 168874612
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+ num_examples: 96221
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  - name: buzztrain
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+ num_bytes: 27989445
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  num_examples: 16706
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  - name: guessdev
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+ num_bytes: 2098857
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  num_examples: 1055
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+ - name: buzzdev
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+ num_bytes: 2301145
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+ num_examples: 1161
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  - name: guesstest
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+ num_bytes: 4434626
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  num_examples: 2151
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+ - name: buzztest
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+ num_bytes: 3930150
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+ num_examples: 1953
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+ - name: adversarial
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+ num_bytes: 1799969
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+ num_examples: 1145
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+ download_size: 133005755
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+ dataset_size: 211428804
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+ - config_name: mode=runs,char_skip=25
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+ features:
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+ - name: id
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+ dtype: string
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+ - name: qanta_id
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+ dtype: int32
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+ - name: proto_id
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+ dtype: string
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+ - name: qdb_id
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+ dtype: int32
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+ - name: dataset
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+ dtype: string
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+ - name: text
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+ - name: full_question
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+ dtype: string
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+ - name: char_idx
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+ dtype: int32
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+ dtype: int32
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+ - name: tokenizations
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+ sequence: int32
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+ length: 2
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+ - name: answer
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+ dtype: string
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+ - name: page
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+ dtype: string
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+ - name: raw_answer
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+ dtype: string
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+ - name: fold
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+ dtype: string
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+ - name: gameplay
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+ dtype: bool
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+ - name: tournament
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+ dtype: string
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+ - name: difficulty
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+ dtype: string
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+ - name: year
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+ dtype: int32
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+ splits:
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  - name: guesstrain
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+ num_bytes: 3975570298
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+ num_examples: 2641161
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+ - name: buzztrain
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+ num_bytes: 622976884
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+ num_examples: 433552
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+ - name: guessdev
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+ num_bytes: 55281178
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+ num_examples: 33602
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+ - name: buzzdev
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+ num_bytes: 60226416
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+ num_examples: 36803
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+ - name: guesstest
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+ num_bytes: 120192213
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+ num_examples: 70772
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+ - name: buzztest
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+ num_bytes: 104422131
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+ num_examples: 63050
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+ - name: adversarial
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+ num_bytes: 37874827
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+ num_examples: 27986
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+ download_size: 306157359
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+ dataset_size: 4976543947
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+ - config_name: mode=sentences,char_skip=25
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+ features:
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+ - name: id
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+ dtype: string
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+ - name: qanta_id
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+ dtype: int32
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+ - name: proto_id
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+ dtype: string
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+ - name: qdb_id
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+ dtype: int32
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+ - name: dataset
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+ dtype: string
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+ - name: text
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+ dtype: string
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+ dtype: string
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+ - name: char_idx
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+ dtype: int32
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+ - name: tokenizations
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+ sequence: int32
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+ - name: page
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+ dtype: string
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+ - name: difficulty
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+ - name: year
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+ dtype: int32
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+ splits:
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+ - name: guesstrain
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+ num_bytes: 629450237
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+ num_examples: 505321
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+ - name: buzztrain
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+ - name: guessdev
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+ - name: guesstest
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+ - name: buzztest
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+ num_examples: 12610
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+ - name: adversarial
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+ num_bytes: 6491504
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+ num_examples: 5812
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+ download_size: 150604036
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+ dataset_size: 790402951
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+ configs:
305
+ - config_name: mode=first,char_skip=25
306
+ data_files:
307
+ - split: guesstrain
308
+ path: mode=first,char_skip=25/guesstrain-*
309
+ - split: buzztrain
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+ path: mode=first,char_skip=25/buzztrain-*
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+ - split: guessdev
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+ path: mode=first,char_skip=25/guessdev-*
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+ - split: buzzdev
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+ path: mode=first,char_skip=25/buzzdev-*
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+ - split: guesstest
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+ path: mode=first,char_skip=25/guesstest-*
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+ - split: buzztest
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+ path: mode=first,char_skip=25/buzztest-*
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+ - split: adversarial
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+ path: mode=first,char_skip=25/adversarial-*
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+ - config_name: mode=full,char_skip=25
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+ data_files:
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+ - split: guesstrain
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+ path: mode=full,char_skip=25/guesstrain-*
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+ - split: buzztrain
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+ path: mode=full,char_skip=25/buzztrain-*
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+ - split: guessdev
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+ path: mode=full,char_skip=25/guessdev-*
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+ - split: buzzdev
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+ path: mode=full,char_skip=25/buzzdev-*
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+ - split: guesstest
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+ path: mode=full,char_skip=25/guesstest-*
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+ - split: buzztest
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+ path: mode=full,char_skip=25/buzztest-*
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+ - split: adversarial
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+ path: mode=full,char_skip=25/adversarial-*
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+ - config_name: mode=runs,char_skip=25
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+ data_files:
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+ - split: guesstrain
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+ path: mode=runs,char_skip=25/guesstrain-*
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+ - split: buzztrain
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+ path: mode=runs,char_skip=25/buzztrain-*
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+ - split: guessdev
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+ path: mode=runs,char_skip=25/guessdev-*
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+ - split: buzzdev
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+ path: mode=runs,char_skip=25/buzzdev-*
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+ - split: guesstest
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+ path: mode=runs,char_skip=25/guesstest-*
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+ - split: buzztest
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+ path: mode=runs,char_skip=25/buzztest-*
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+ - split: adversarial
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+ path: mode=runs,char_skip=25/adversarial-*
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+ - config_name: mode=sentences,char_skip=25
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+ data_files:
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+ - split: guesstrain
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+ path: mode=sentences,char_skip=25/guesstrain-*
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+ - split: buzztrain
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+ path: mode=sentences,char_skip=25/buzztrain-*
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+ - split: guessdev
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+ path: mode=sentences,char_skip=25/guessdev-*
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+ - split: buzzdev
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+ path: mode=sentences,char_skip=25/buzzdev-*
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+ - split: guesstest
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+ path: mode=sentences,char_skip=25/guesstest-*
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+ - split: buzztest
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+ path: mode=sentences,char_skip=25/buzztest-*
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+ - split: adversarial
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+ path: mode=sentences,char_skip=25/adversarial-*
369
  ---
370
 
371
  # Dataset Card for "qanta"
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qanta.py DELETED
@@ -1,289 +0,0 @@
1
- """qanta dataset."""
2
-
3
-
4
- import json
5
- from typing import List, Tuple
6
-
7
- import datasets
8
-
9
-
10
- _CITATION = """
11
- @article{Rodriguez2019QuizbowlTC,
12
- title={Quizbowl: The Case for Incremental Question Answering},
13
- author={Pedro Rodriguez and Shi Feng and Mohit Iyyer and He He and Jordan L. Boyd-Graber},
14
- journal={ArXiv},
15
- year={2019},
16
- volume={abs/1904.04792}
17
- }
18
- """
19
-
20
- _DESCRIPTION = """
21
- The Qanta dataset is a question answering dataset based on the academic trivia game Quizbowl.
22
- """
23
-
24
-
25
- _QANTA_URL = "https://s3-us-west-2.amazonaws.com/pinafore-us-west-2/qanta-jmlr-datasets/qanta.mapped.2018.04.18.json"
26
- _TRICK_URL = "https://s3-us-west-2.amazonaws.com/pinafore-us-west-2/trick-tacl-datasets/qanta.tacl-trick.json"
27
- _VERSION = datasets.Version("2018.04.18")
28
- _FIRST = "first"
29
- _FULL = "full"
30
- _SENTENCES = "sentences"
31
- _RUNS = "runs"
32
- # Order matters, the first one is default
33
- _MODES = [_FULL, _FIRST, _SENTENCES, _RUNS]
34
- _DEFAULT_CHAR_SKIP = 25
35
-
36
-
37
- class QantaConfig(datasets.BuilderConfig):
38
- """BuilderConfig for Qanta."""
39
-
40
- def __init__(self, mode: str, char_skip: int, **kwargs):
41
- super(QantaConfig, self).__init__(version=_VERSION, **kwargs)
42
- self.mode = mode
43
- self.char_skip = char_skip
44
-
45
-
46
- def create_char_runs(text: str, char_skip: int) -> List[Tuple[str, int]]:
47
- """
48
- Returns runs of the question based on skipping char_skip characters at a time. Also returns the indices used
49
- q: name this first united states president.
50
- runs with char_skip=10:
51
- ['name this ',
52
- 'name this first unit',
53
- 'name this first united state p',
54
- 'name this first united state president.']
55
- :param char_skip: Number of characters to skip each time
56
- """
57
- char_indices = list(range(char_skip, len(text) + char_skip, char_skip))
58
- return [(text[:idx], idx) for idx in char_indices]
59
-
60
-
61
- def with_default(key, lookup, default):
62
- if key in lookup:
63
- value = lookup[key]
64
- if value is None:
65
- return default
66
- else:
67
- return value
68
- else:
69
- return default
70
-
71
-
72
- def question_to_examples(question, mode: str, char_skip: int):
73
- features = {
74
- "qanta_id": question["qanta_id"],
75
- "proto_id": with_default("proto_id", question, ""),
76
- "qdb_id": with_default("qdb_id", question, -1),
77
- # We refer to the actual answer as page, but this
78
- # may be misleading externally, so rename here to
79
- # be clearer
80
- "page": question["page"],
81
- "answer": question["page"],
82
- "raw_answer": question["answer"],
83
- "dataset": with_default("dataset", question, ""),
84
- "full_question": question["text"],
85
- "first_sentence": question["first_sentence"],
86
- "tokenizations": question["tokenizations"],
87
- "fold": question["fold"],
88
- "gameplay": question["gameplay"],
89
- "category": with_default("category", question, ""),
90
- "subcategory": with_default("subcategory", question, ""),
91
- "tournament": question["tournament"],
92
- "difficulty": with_default("difficulty", question, ""),
93
- "year": question["year"],
94
- "char_idx": -1,
95
- "sentence_idx": -1,
96
- }
97
- if mode == _FULL:
98
- yield {
99
- "text": question["text"],
100
- "id": str(question["qanta_id"]) + "-full",
101
- **features,
102
- }
103
- elif mode == _FIRST:
104
- yield {
105
- "text": question["first_sentence"],
106
- "id": str(question["qanta_id"]) + "-first",
107
- **features,
108
- }
109
- elif mode == _RUNS:
110
- text = question["text"]
111
- for text_run, char_idx in create_char_runs(text, char_skip):
112
- yield {
113
- "text": text_run,
114
- "char_idx": char_idx,
115
- "id": str(question["qanta_id"]) + "-char-" + str(char_idx),
116
- **features,
117
- }
118
- elif mode == _SENTENCES:
119
- for sentence_idx, (start, end) in enumerate(question["tokenizations"]):
120
- sentence = question["text"][start:end]
121
- yield {
122
- "text": sentence,
123
- "sentence_idx": sentence_idx,
124
- "id": str(question["qanta_id"]) + "-sentence-" + str(sentence_idx),
125
- **features,
126
- }
127
- else:
128
- raise ValueError(f"Invalid mode: {mode}")
129
-
130
-
131
- _FEATURES = {
132
- # Generated ID based modes set, unique
133
- "id": datasets.Value("string"),
134
- # Dataset defined IDs
135
- "qanta_id": datasets.Value("int32"),
136
- "proto_id": datasets.Value("string"),
137
- "qdb_id": datasets.Value("int32"),
138
- "dataset": datasets.Value("string"),
139
- # Inputs
140
- "text": datasets.Value("string"),
141
- "full_question": datasets.Value("string"),
142
- "first_sentence": datasets.Value("string"),
143
- "char_idx": datasets.Value("int32"),
144
- "sentence_idx": datasets.Value("int32"),
145
- # Character indices of sentences: List[Tuple[int, int]]
146
- "tokenizations": datasets.features.Sequence(datasets.features.Sequence(datasets.Value("int32"), length=2)),
147
- # Labels: Number is equal to number of unique pages across all folds
148
- "answer": datasets.Value("string"),
149
- "page": datasets.Value("string"),
150
- "raw_answer": datasets.Value("string"),
151
- # Meta Information
152
- "fold": datasets.Value("string"),
153
- "gameplay": datasets.Value("bool"),
154
- "category": datasets.Value("string"),
155
- "subcategory": datasets.Value("string"),
156
- "tournament": datasets.Value("string"),
157
- "difficulty": datasets.Value("string"),
158
- "year": datasets.Value("int32"),
159
- }
160
-
161
-
162
- class Qanta(datasets.GeneratorBasedBuilder):
163
- """The Qanta dataset is a question answering dataset based on the academic trivia game Quizbowl."""
164
-
165
- VERSION = _VERSION
166
- BUILDER_CONFIGS = [
167
- QantaConfig(
168
- name=f"mode={mode},char_skip={_DEFAULT_CHAR_SKIP}",
169
- description=f"Question format: {mode}, char_skip: {_DEFAULT_CHAR_SKIP}",
170
- mode=mode,
171
- char_skip=_DEFAULT_CHAR_SKIP,
172
- )
173
- for mode in _MODES
174
- ]
175
-
176
- def _info(self):
177
- return datasets.DatasetInfo(
178
- # This is the description that will appear on the datasets page.
179
- description=_DESCRIPTION,
180
- # datasets.features.FeatureConnectors
181
- features=datasets.Features(_FEATURES),
182
- # Number of classes is a function of the dataset, ClassLabel doesn't support dynamic
183
- # definition, so have to defer conversion to classes to later, so can't define
184
- # supervied keys
185
- supervised_keys=None,
186
- # Homepage of the dataset for documentation
187
- homepage="http://www.qanta.org/",
188
- citation=_CITATION,
189
- )
190
-
191
- def _split_generators(self, dl_manager):
192
- """Returns SplitGenerators."""
193
- qanta_path = dl_manager.download_and_extract(_QANTA_URL)
194
- trick_path = dl_manager.download_and_extract(_TRICK_URL)
195
- return [
196
- datasets.SplitGenerator(
197
- name=datasets.Split("guesstrain"),
198
- gen_kwargs={
199
- "qanta_filepath": qanta_path,
200
- "trick_filepath": trick_path,
201
- "fold": "guesstrain",
202
- "mode": self.config.mode,
203
- "char_skip": self.config.char_skip,
204
- },
205
- ),
206
- datasets.SplitGenerator(
207
- name=datasets.Split("buzztrain"),
208
- gen_kwargs={
209
- "qanta_filepath": qanta_path,
210
- "trick_filepath": trick_path,
211
- "fold": "buzztrain",
212
- "mode": self.config.mode,
213
- "char_skip": self.config.char_skip,
214
- },
215
- ),
216
- datasets.SplitGenerator(
217
- name=datasets.Split("guessdev"),
218
- gen_kwargs={
219
- "qanta_filepath": qanta_path,
220
- "trick_filepath": trick_path,
221
- "fold": "guessdev",
222
- "mode": self.config.mode,
223
- "char_skip": self.config.char_skip,
224
- },
225
- ),
226
- datasets.SplitGenerator(
227
- name=datasets.Split("buzzdev"),
228
- gen_kwargs={
229
- "qanta_filepath": qanta_path,
230
- "trick_filepath": trick_path,
231
- "fold": "buzzdev",
232
- "mode": self.config.mode,
233
- "char_skip": self.config.char_skip,
234
- },
235
- ),
236
- datasets.SplitGenerator(
237
- name=datasets.Split("guesstest"),
238
- gen_kwargs={
239
- "qanta_filepath": qanta_path,
240
- "trick_filepath": trick_path,
241
- "fold": "guesstest",
242
- "mode": self.config.mode,
243
- "char_skip": self.config.char_skip,
244
- },
245
- ),
246
- datasets.SplitGenerator(
247
- name=datasets.Split("buzztest"),
248
- gen_kwargs={
249
- "qanta_filepath": qanta_path,
250
- "trick_filepath": trick_path,
251
- "fold": "buzztest",
252
- "mode": self.config.mode,
253
- "char_skip": self.config.char_skip,
254
- },
255
- ),
256
- datasets.SplitGenerator(
257
- name=datasets.Split("adversarial"),
258
- gen_kwargs={
259
- "qanta_filepath": qanta_path,
260
- "trick_filepath": trick_path,
261
- "fold": "adversarial",
262
- "mode": self.config.mode,
263
- "char_skip": self.config.char_skip,
264
- },
265
- ),
266
- ]
267
-
268
- def _generate_examples(
269
- self,
270
- qanta_filepath: str,
271
- trick_filepath: str,
272
- fold: str,
273
- mode: str,
274
- char_skip: int,
275
- ):
276
- """Yields examples."""
277
- if mode not in _MODES:
278
- raise ValueError(f"Invalid mode: {mode}")
279
-
280
- if fold == "adversarial":
281
- path = trick_filepath
282
- else:
283
- path = qanta_filepath
284
- with open(path, encoding="utf-8") as f:
285
- questions = json.load(f)["questions"]
286
- for q in questions:
287
- if q["page"] is not None and q["fold"] == fold:
288
- for example in question_to_examples(q, mode, char_skip):
289
- yield example["id"], example