Datasets:

Modalities:
Text
Formats:
parquet
Languages:
English
ArXiv:
Libraries:
Datasets
pandas
License:
albertvillanova HF staff commited on
Commit
d972dc6
1 Parent(s): 3dfa861

Convert dataset to Parquet

Browse files

Convert dataset to Parquet.

README.md CHANGED
@@ -1,15 +1,14 @@
1
  ---
2
  annotations_creators:
3
  - crowdsourced
4
- language:
5
- - en
6
  language_creators:
7
  - found
 
 
8
  license:
9
  - cc-by-4.0
10
  multilinguality:
11
  - monolingual
12
- pretty_name: Question Answering via Sentence Composition (QASC)
13
  size_categories:
14
  - 1K<n<10K
15
  source_datasets:
@@ -21,6 +20,7 @@ task_ids:
21
  - extractive-qa
22
  - multiple-choice-qa
23
  paperswithcode_id: qasc
 
24
  dataset_info:
25
  features:
26
  - name: id
@@ -44,17 +44,26 @@ dataset_info:
44
  - name: formatted_question
45
  dtype: string
46
  splits:
47
- - name: test
48
- num_bytes: 393683
49
- num_examples: 920
50
  - name: train
51
- num_bytes: 4919377
52
  num_examples: 8134
 
 
 
53
  - name: validation
54
- num_bytes: 562352
55
  num_examples: 926
56
- download_size: 1616514
57
- dataset_size: 5875412
 
 
 
 
 
 
 
 
 
58
  ---
59
 
60
  # Dataset Card for "qasc"
 
1
  ---
2
  annotations_creators:
3
  - crowdsourced
 
 
4
  language_creators:
5
  - found
6
+ language:
7
+ - en
8
  license:
9
  - cc-by-4.0
10
  multilinguality:
11
  - monolingual
 
12
  size_categories:
13
  - 1K<n<10K
14
  source_datasets:
 
20
  - extractive-qa
21
  - multiple-choice-qa
22
  paperswithcode_id: qasc
23
+ pretty_name: Question Answering via Sentence Composition (QASC)
24
  dataset_info:
25
  features:
26
  - name: id
 
44
  - name: formatted_question
45
  dtype: string
46
  splits:
 
 
 
47
  - name: train
48
+ num_bytes: 4891878
49
  num_examples: 8134
50
+ - name: test
51
+ num_bytes: 390534
52
+ num_examples: 920
53
  - name: validation
54
+ num_bytes: 559180
55
  num_examples: 926
56
+ download_size: 2349698
57
+ dataset_size: 5841592
58
+ configs:
59
+ - config_name: default
60
+ data_files:
61
+ - split: train
62
+ path: data/train-*
63
+ - split: test
64
+ path: data/test-*
65
+ - split: validation
66
+ path: data/validation-*
67
  ---
68
 
69
  # Dataset Card for "qasc"
data/test-00000-of-00001.parquet ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:495cfbd17abc1720b54785cdce68825104aaf60d7b8bdb2acac62157a31eb517
3
+ size 158241
data/train-00000-of-00001.parquet ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b9a297b5ab55f1605c7682ffbb7042c26d7ecb9ff1e1aa5a820d4e791c8302d1
3
+ size 1967904
data/validation-00000-of-00001.parquet ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d1ae34ae13c5fce2c55305372c203c6cdb789728d0d7e5ea2956d55bc33f40ae
3
+ size 223553
dataset_infos.json CHANGED
@@ -1 +1,83 @@
1
- {"default": {"description": "\nQASC is a question-answering dataset with a focus on sentence composition. It consists of 9,980 8-way multiple-choice \nquestions about grade school science (8,134 train, 926 dev, 920 test), and comes with a corpus of 17M sentences.\n", "citation": "@article{allenai:qasc,\n author = {Tushar Khot and Peter Clark and Michal Guerquin and Peter Jansen and Ashish Sabharwal},\n title = {QASC: A Dataset for Question Answering via Sentence Composition},\n journal = {arXiv:1910.11473v2},\n year = {2020},\n}\n", "homepage": "https://allenai.org/data/qasc", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "choices": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "answerKey": {"dtype": "string", "id": null, "_type": "Value"}, "fact1": {"dtype": "string", "id": null, "_type": "Value"}, "fact2": {"dtype": "string", "id": null, "_type": "Value"}, "combinedfact": {"dtype": "string", "id": null, "_type": "Value"}, "formatted_question": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "qasc", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "datasets_version_to_prepare": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 393683, "num_examples": 920, "dataset_name": "qasc"}, "train": {"name": "train", "num_bytes": 4919377, "num_examples": 8134, "dataset_name": "qasc"}, "validation": {"name": "validation", "num_bytes": 562352, "num_examples": 926, "dataset_name": "qasc"}}, "download_checksums": {"http://data.allenai.org/downloads/qasc/qasc_dataset.tar.gz": {"num_bytes": 1616514, "checksum": "a7b3f2244f768974c609fd621346c931a72715609f171cb5544fc1da2a2ad55c"}}, "download_size": 1616514, "dataset_size": 5875412, "size_in_bytes": 7491926}}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "default": {
3
+ "description": "\nQASC is a question-answering dataset with a focus on sentence composition. It consists of 9,980 8-way multiple-choice\nquestions about grade school science (8,134 train, 926 dev, 920 test), and comes with a corpus of 17M sentences.\n",
4
+ "citation": "@article{allenai:qasc,\n author = {Tushar Khot and Peter Clark and Michal Guerquin and Peter Jansen and Ashish Sabharwal},\n title = {QASC: A Dataset for Question Answering via Sentence Composition},\n journal = {arXiv:1910.11473v2},\n year = {2020},\n}\n",
5
+ "homepage": "https://allenai.org/data/qasc",
6
+ "license": "",
7
+ "features": {
8
+ "id": {
9
+ "dtype": "string",
10
+ "_type": "Value"
11
+ },
12
+ "question": {
13
+ "dtype": "string",
14
+ "_type": "Value"
15
+ },
16
+ "choices": {
17
+ "feature": {
18
+ "text": {
19
+ "dtype": "string",
20
+ "_type": "Value"
21
+ },
22
+ "label": {
23
+ "dtype": "string",
24
+ "_type": "Value"
25
+ }
26
+ },
27
+ "_type": "Sequence"
28
+ },
29
+ "answerKey": {
30
+ "dtype": "string",
31
+ "_type": "Value"
32
+ },
33
+ "fact1": {
34
+ "dtype": "string",
35
+ "_type": "Value"
36
+ },
37
+ "fact2": {
38
+ "dtype": "string",
39
+ "_type": "Value"
40
+ },
41
+ "combinedfact": {
42
+ "dtype": "string",
43
+ "_type": "Value"
44
+ },
45
+ "formatted_question": {
46
+ "dtype": "string",
47
+ "_type": "Value"
48
+ }
49
+ },
50
+ "builder_name": "qasc",
51
+ "dataset_name": "qasc",
52
+ "config_name": "default",
53
+ "version": {
54
+ "version_str": "0.1.0",
55
+ "major": 0,
56
+ "minor": 1,
57
+ "patch": 0
58
+ },
59
+ "splits": {
60
+ "train": {
61
+ "name": "train",
62
+ "num_bytes": 4891878,
63
+ "num_examples": 8134,
64
+ "dataset_name": null
65
+ },
66
+ "test": {
67
+ "name": "test",
68
+ "num_bytes": 390534,
69
+ "num_examples": 920,
70
+ "dataset_name": null
71
+ },
72
+ "validation": {
73
+ "name": "validation",
74
+ "num_bytes": 559180,
75
+ "num_examples": 926,
76
+ "dataset_name": null
77
+ }
78
+ },
79
+ "download_size": 2349698,
80
+ "dataset_size": 5841592,
81
+ "size_in_bytes": 8191290
82
+ }
83
+ }