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Datasets:
iszhaoxin
/
MCEval8K

Tasks:
Multiple Choice
Question Answering
Text Classification
Modalities:
Tabular
Text
Formats:
json
Sub-tasks:
natural-language-inference
acceptability-classification
fact-checking
Languages:
multilingual
Size:
100K - 1M
Libraries:
Datasets
pandas
License:
Dataset card Viewer Files Community
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Files changed (10) hide show
  1. README copy.md +237 -0
  2. README.md +3 -195
  3. dataset_infos copy.json +130 -0
  4. dataset_infos.json +1 -109
  5. fact/commensenseqa/test.csv +0 -0
  6. fact/commensenseqa/test.json +0 -0
  7. fact/commensenseqa/train.csv +0 -0
  8. fact/commensenseqa/train.json +0 -0
  9. fact/commensenseqa/valid.csv +0 -0
  10. fact/commensenseqa/valid.json +0 -0
README copy.md ADDED
@@ -0,0 +1,237 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: cc-by-4.0
3
+
4
+ configs:
5
+ - config_name: chunking
6
+ data_files:
7
+ - split: train
8
+ path: "linguistic/chunking/train.csv"
9
+ - split: validation
10
+ path: "linguistic/chunking/valid.csv"
11
+ - split: test
12
+ path: "linguistic/chunking/test.csv"
13
+ dataset_info:
14
+ splits:
15
+ train:
16
+ num_examples: 6000
17
+ validation:
18
+ num_examples: 1000
19
+ test:
20
+ num_examples: 1000
21
+ - config_name: clang8
22
+ data_files:
23
+ - split: train
24
+ path: "linguistic/clang8/train.csv"
25
+ - split: validation
26
+ path: "linguistic/clang8/valid.csv"
27
+ - split: test
28
+ path: "linguistic/clang8/test.csv"
29
+ - config_name: ner
30
+ data_files:
31
+ - split: train
32
+ path: "linguistic/ner/train.csv"
33
+ - split: validation
34
+ path: "linguistic/ner/valid.csv"
35
+ - split: test
36
+ path: "linguistic/ner/test.csv"
37
+ - config_name: postag
38
+ data_files:
39
+ - split: train
40
+ path: "linguistic/postag/train.csv"
41
+ - split: validation
42
+ path: "linguistic/postag/valid.csv"
43
+ - split: test
44
+ path: "linguistic/postag/test.csv"
45
+
46
+ - config_name: agnews
47
+ data_files:
48
+ - split: train
49
+ path: "classification/agnews/train.csv"
50
+ - split: validation
51
+ path: "classification/agnews/valid.csv"
52
+ - split: test
53
+ path: "classification/agnews/test.csv"
54
+ dataset_info:
55
+ splits:
56
+ train:
57
+ num_examples: 6000
58
+ validation:
59
+ num_examples: 1000
60
+ test:
61
+ num_examples: 1000
62
+ - config_name: amazon-reviews
63
+ data_files:
64
+ - split: train
65
+ path: "classification/amazon-reviews/train.csv"
66
+ - split: validation
67
+ path: "classification/amazon-reviews/valid.csv"
68
+ - split: test
69
+ path: "classification/amazon-reviews/test.csv"
70
+ - config_name: imdb
71
+ data_files:
72
+ - split: train
73
+ path: "classification/imdb/train.csv"
74
+ - split: validation
75
+ path: "classification/imdb/valid.csv"
76
+ - split: test
77
+ path: "classification/imdb/test.csv"
78
+
79
+ - config_name: mnli
80
+ data_files:
81
+ - split: train
82
+ path: "nli/mnli/train.csv"
83
+ - split: validation
84
+ path: "nli/mnli/valid.csv"
85
+ - split: test
86
+ path: "nli/mnli/test.csv"
87
+ - config_name: paws
88
+ data_files:
89
+ - split: train
90
+ path: "nli/paws/train.csv"
91
+ - split: validation
92
+ path: "nli/paws/valid.csv"
93
+ - split: test
94
+ path: "nli/paws/test.csv"
95
+ - config_name: swag
96
+ data_files:
97
+ - split: train
98
+ path: "nli/swag/train.csv"
99
+ - split: validation
100
+ path: "nli/swag/valid.csv"
101
+ - split: test
102
+ path: "nli/swag/test.csv"
103
+
104
+ - config_name: fever
105
+ data_files:
106
+ - split: train
107
+ path: "fact/fever/train.csv"
108
+ - split: validation
109
+ path: "fact/fever/valid.csv"
110
+ - split: test
111
+ path: "fact/fever/test.csv"
112
+ - config_name: myriadlama
113
+ data_files:
114
+ - split: train
115
+ path: "fact/myriadlama/train.csv"
116
+ - split: validation
117
+ path: "fact/myriadlama/valid.csv"
118
+ - split: test
119
+ path: "fact/myriadlama/test.csv"
120
+ - config_name: commensenseqa
121
+ data_files:
122
+ - split: train
123
+ path: "fact/commensenseqa/train.csv"
124
+ - split: validation
125
+ path: "fact/commensenseqa/valid.csv"
126
+ - split: test
127
+ path: "fact/commensenseqa/test.csv"
128
+ - config_name: templama
129
+ data_files:
130
+ - split: train
131
+ path: "fact/templama/train.csv"
132
+ - split: validation
133
+ path: "fact/templama/valid.csv"
134
+ - split: test
135
+ path: "fact/templama/test.csv"
136
+
137
+
138
+ - config_name: halueval
139
+ data_files:
140
+ - split: train
141
+ path: "self-reflection/halueval/train.csv"
142
+ - split: validation
143
+ path: "self-reflection/halueval/valid.csv"
144
+ - split: test
145
+ path: "self-reflection/halueval/test.csv"
146
+ - config_name: stereoset
147
+ data_files:
148
+ - split: train
149
+ path: "self-reflection/stereoset/train.csv"
150
+ - split: validation
151
+ path: "self-reflection/stereoset/valid.csv"
152
+ - split: test
153
+ path: "self-reflection/stereoset/test.csv"
154
+ - config_name: toxicity
155
+ data_files:
156
+ - split: train
157
+ path: "self-reflection/toxicity/train.csv"
158
+ - split: validation
159
+ path: "self-reflection/toxicity/valid.csv"
160
+ - split: test
161
+ path: "self-reflection/toxicity/test.csv"
162
+
163
+
164
+ - config_name: lti
165
+ data_files:
166
+ - split: train
167
+ path: "multilingual/lti/train.csv"
168
+ - split: validation
169
+ path: "multilingual/lti/valid.csv"
170
+ - split: test
171
+ path: "multilingual/lti/test.csv"
172
+ - config_name: mpostag
173
+ data_files:
174
+ - split: train
175
+ path: "multilingual/mpostag/train.csv"
176
+ - split: validation
177
+ path: "multilingual/mpostag/valid.csv"
178
+ - split: test
179
+ path: "multilingual/mpostag/test.csv"
180
+ - config_name: amazon-review-multi
181
+ data_files:
182
+ - split: train
183
+ path: "multilingual/amazon-review-multi/train.csv"
184
+ - split: validation
185
+ path: "multilingual/amazon-review-multi/valid.csv"
186
+ - split: test
187
+ path: "multilingual/amazon-review-multi/test.csv"
188
+ - config_name: xnli
189
+ data_files:
190
+ - split: train
191
+ path: "multilingual/xnli/train.csv"
192
+ - split: validation
193
+ path: "multilingual/xnli/valid.csv"
194
+ - split: test
195
+ path: "multilingual/xnli/test.csv"
196
+ - config_name: mlama
197
+ data_files:
198
+ - split: train
199
+ path: "multilingual/mlama/train.csv"
200
+ - split: validation
201
+ path: "multilingual/mlama/valid.csv"
202
+ - split: test
203
+ path: "multilingual/mlama/test.csv"
204
+
205
+ annotations_creators:
206
+ - no-annotation
207
+ language_creators:
208
+ - found
209
+ language:
210
+ - multilingual
211
+ multilinguality:
212
+ - multilingual
213
+ size_categories:
214
+ - n<1M
215
+ task_categories:
216
+ - multiple-choice
217
+ - question-answering
218
+ - text-classification
219
+ task_ids:
220
+ - natural-language-inference
221
+ - acceptability-classification
222
+ - fact-checking
223
+ - intent-classification
224
+ - language-identification
225
+ - multi-label-classification
226
+ - sentiment-classification
227
+ - topic-classification
228
+ - sentiment-scoring
229
+ - hate-speech-detection
230
+ - named-entity-recognition
231
+ - part-of-speech
232
+ - parsing
233
+ - open-domain-qa
234
+ - document-question-answering
235
+ - multiple-choice-qa
236
+ paperswithcode_id: null
237
+ ---
README.md CHANGED
@@ -2,206 +2,14 @@
2
  license: cc-by-4.0
3
 
4
  configs:
5
- - config_name: chunking
6
- data_files:
7
- - split: train
8
- path: "linguistic/chunking/train.csv"
9
- - split: validation
10
- path: "linguistic/chunking/valid.csv"
11
- - split: test
12
- path: "linguistic/chunking/test.csv"
13
- dataset_info:
14
- splits:
15
- train:
16
- num_examples: 6000
17
- validation:
18
- num_examples: 1000
19
- test:
20
- num_examples: 1000
21
- - config_name: clang8
22
- data_files:
23
- - split: train
24
- path: "linguistic/clang8/train.csv"
25
- - split: validation
26
- path: "linguistic/clang8/valid.csv"
27
- - split: test
28
- path: "linguistic/clang8/test.csv"
29
- - config_name: ner
30
- data_files:
31
- - split: train
32
- path: "linguistic/ner/train.csv"
33
- - split: validation
34
- path: "linguistic/ner/valid.csv"
35
- - split: test
36
- path: "linguistic/ner/test.csv"
37
- - config_name: postag
38
- data_files:
39
- - split: train
40
- path: "linguistic/postag/train.csv"
41
- - split: validation
42
- path: "linguistic/postag/valid.csv"
43
- - split: test
44
- path: "linguistic/postag/test.csv"
45
-
46
- - config_name: agnews
47
- data_files:
48
- - split: train
49
- path: "classification/agnews/train.csv"
50
- - split: validation
51
- path: "classification/agnews/valid.csv"
52
- - split: test
53
- path: "classification/agnews/test.csv"
54
- dataset_info:
55
- splits:
56
- train:
57
- num_examples: 6000
58
- validation:
59
- num_examples: 1000
60
- test:
61
- num_examples: 1000
62
- - config_name: amazon-reviews
63
- data_files:
64
- - split: train
65
- path: "classification/amazon-reviews/train.csv"
66
- - split: validation
67
- path: "classification/amazon-reviews/valid.csv"
68
- - split: test
69
- path: "classification/amazon-reviews/test.csv"
70
- - config_name: imdb
71
- data_files:
72
- - split: train
73
- path: "classification/imdb/train.csv"
74
- - split: validation
75
- path: "classification/imdb/valid.csv"
76
- - split: test
77
- path: "classification/imdb/test.csv"
78
-
79
- - config_name: mnli
80
- data_files:
81
- - split: train
82
- path: "nli/mnli/train.csv"
83
- - split: validation
84
- path: "nli/mnli/valid.csv"
85
- - split: test
86
- path: "nli/mnli/test.csv"
87
- - config_name: paws
88
- data_files:
89
- - split: train
90
- path: "nli/paws/train.csv"
91
- - split: validation
92
- path: "nli/paws/valid.csv"
93
- - split: test
94
- path: "nli/paws/test.csv"
95
- - config_name: swag
96
- data_files:
97
- - split: train
98
- path: "nli/swag/train.csv"
99
- - split: validation
100
- path: "nli/swag/valid.csv"
101
- - split: test
102
- path: "nli/swag/test.csv"
103
-
104
- - config_name: fever
105
- data_files:
106
- - split: train
107
- path: "fact/fever/train.csv"
108
- - split: validation
109
- path: "fact/fever/valid.csv"
110
- - split: test
111
- path: "fact/fever/test.csv"
112
- - config_name: myriadlama
113
- data_files:
114
- - split: train
115
- path: "fact/myriadlama/train.csv"
116
- - split: validation
117
- path: "fact/myriadlama/valid.csv"
118
- - split: test
119
- path: "fact/myriadlama/test.csv"
120
  - config_name: commensenseqa
121
  data_files:
122
  - split: train
123
- path: "fact/commensenseqa/train.csv"
124
- - split: validation
125
- path: "fact/commensenseqa/valid.csv"
126
- - split: test
127
- path: "fact/commensenseqa/test.csv"
128
- - config_name: templama
129
- data_files:
130
- - split: train
131
- path: "fact/templama/train.csv"
132
- - split: validation
133
- path: "fact/templama/valid.csv"
134
- - split: test
135
- path: "fact/templama/test.csv"
136
-
137
-
138
- - config_name: halueval
139
- data_files:
140
- - split: train
141
- path: "self-reflection/halueval/train.csv"
142
- - split: validation
143
- path: "self-reflection/halueval/valid.csv"
144
- - split: test
145
- path: "self-reflection/halueval/test.csv"
146
- - config_name: stereoset
147
- data_files:
148
- - split: train
149
- path: "self-reflection/stereoset/train.csv"
150
- - split: validation
151
- path: "self-reflection/stereoset/valid.csv"
152
- - split: test
153
- path: "self-reflection/stereoset/test.csv"
154
- - config_name: toxicity
155
- data_files:
156
- - split: train
157
- path: "self-reflection/toxicity/train.csv"
158
  - split: validation
159
- path: "self-reflection/toxicity/valid.csv"
160
  - split: test
161
- path: "self-reflection/toxicity/test.csv"
162
-
163
-
164
- - config_name: lti
165
- data_files:
166
- - split: train
167
- path: "multilingual/lti/train.csv"
168
- - split: validation
169
- path: "multilingual/lti/valid.csv"
170
- - split: test
171
- path: "multilingual/lti/test.csv"
172
- - config_name: mpostag
173
- data_files:
174
- - split: train
175
- path: "multilingual/mpostag/train.csv"
176
- - split: validation
177
- path: "multilingual/mpostag/valid.csv"
178
- - split: test
179
- path: "multilingual/mpostag/test.csv"
180
- - config_name: amazon-review-multi
181
- data_files:
182
- - split: train
183
- path: "multilingual/amazon-review-multi/train.csv"
184
- - split: validation
185
- path: "multilingual/amazon-review-multi/valid.csv"
186
- - split: test
187
- path: "multilingual/amazon-review-multi/test.csv"
188
- - config_name: xnli
189
- data_files:
190
- - split: train
191
- path: "multilingual/xnli/train.csv"
192
- - split: validation
193
- path: "multilingual/xnli/valid.csv"
194
- - split: test
195
- path: "multilingual/xnli/test.csv"
196
- - config_name: mlama
197
- data_files:
198
- - split: train
199
- path: "multilingual/mlama/train.csv"
200
- - split: validation
201
- path: "multilingual/mlama/valid.csv"
202
- - split: test
203
- path: "multilingual/mlama/test.csv"
204
-
205
  annotations_creators:
206
  - no-annotation
207
  language_creators:
 
2
  license: cc-by-4.0
3
 
4
  configs:
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5
  - config_name: commensenseqa
6
  data_files:
7
  - split: train
8
+ path: "fact/commensenseqa/train.json"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9
  - split: validation
10
+ path: "fact/commensenseqa/valid.json"
11
  - split: test
12
+ path: "fact/commensenseqa/test.json"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
13
  annotations_creators:
14
  - no-annotation
15
  language_creators:
dataset_infos copy.json ADDED
@@ -0,0 +1,130 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "agnews": {
3
+ "features": {
4
+ "text": {
5
+ "_type": "Value",
6
+ "dtype": "string"
7
+ },
8
+ "label": {
9
+ "_type": "ClassLabel",
10
+ "names": [
11
+ "World",
12
+ "Sports",
13
+ "Business",
14
+ "Sci/Tech"
15
+ ]
16
+ }
17
+ },
18
+ "description": "Multi-choice, Topic classification task (Agnews)."
19
+ },
20
+ "amazon-reviews": {
21
+ "features": {
22
+ "text": {
23
+ "_type": "Value",
24
+ "dtype": "string"
25
+ },
26
+ "label": {
27
+ "_type": "Value",
28
+ "dtype": "int8"
29
+ }
30
+ },
31
+ "description": "Multi-choice, Sentiment classification task with numerical labels (Amazon-Review)."
32
+ },
33
+ "imdb": {
34
+ "features": {
35
+ "text": {
36
+ "_type": "Value",
37
+ "dtype": "string"
38
+ },
39
+ "label": {
40
+ "_type": "ClassLabel",
41
+ "names": [
42
+ "Negative",
43
+ "Positive"
44
+ ]
45
+ }
46
+ },
47
+ "description": "Binary sentiment classification (IMDB)."
48
+ },
49
+ "commensenseqa": {
50
+ "features": {
51
+ "text": {
52
+ "_type": "Value",
53
+ "dtype": "string"
54
+ },
55
+ "options": {
56
+ "feature": {
57
+ "_type": "Value",
58
+ "dtype": "string"
59
+ },
60
+ "length": 5,
61
+ "_type": "Sequence"
62
+ },
63
+ "label": {
64
+ "_type": "Value",
65
+ "dtype": "int8"
66
+ }
67
+ },
68
+ "description": "Multi-choice, Commense knowledge-answering datasets (CommensenseQA)."
69
+ },
70
+ "fever": {
71
+ "features": {
72
+ "text": {
73
+ "_type": "Value",
74
+ "dtype": "string"
75
+ },
76
+ "label": {
77
+ "_type": "ClassLabel",
78
+ "names": [
79
+ "Incorrect",
80
+ "Correct"
81
+ ]
82
+ }
83
+ },
84
+ "description": "Binary classification, fact-checking (FEVER)."
85
+ },
86
+ "myriadlama": {
87
+ "features": {
88
+ "text": {
89
+ "_type": "Value",
90
+ "dtype": "string"
91
+ },
92
+ "options": {
93
+ "feature": {
94
+ "dtype": "string",
95
+ "id": null,
96
+ "_type": "Value"
97
+ },
98
+ "length": 4,
99
+ "_type": "Sequence"
100
+ },
101
+ "label": {
102
+ "_type": "Value",
103
+ "dtype": "int8"
104
+ }
105
+ },
106
+ "description": "Multi-choice, open-domain knowledge question-answering (MyriadLAMA)."
107
+ },
108
+ "templama": {
109
+ "features": {
110
+ "text": {
111
+ "_type": "Value",
112
+ "dtype": "string"
113
+ },
114
+ "options": {
115
+ "feature": {
116
+ "dtype": "string",
117
+ "id": null,
118
+ "_type": "Value"
119
+ },
120
+ "length": 4,
121
+ "_type": "Sequence"
122
+ },
123
+ "label": {
124
+ "_type": "Value",
125
+ "dtype": "int8"
126
+ }
127
+ },
128
+ "description": "Multi-choice, open-domain temporary knowledge QA (TempLAMA)."
129
+ }
130
+ }
dataset_infos.json CHANGED
@@ -1,51 +1,4 @@
1
  {
2
- "agnews": {
3
- "features": {
4
- "text": {
5
- "_type": "Value",
6
- "dtype": "string"
7
- },
8
- "label": {
9
- "_type": "ClassLabel",
10
- "names": [
11
- "World",
12
- "Sports",
13
- "Business",
14
- "Sci/Tech"
15
- ]
16
- }
17
- },
18
- "description": "Multi-choice, Topic classification task (Agnews)."
19
- },
20
- "amazon-reviews": {
21
- "features": {
22
- "text": {
23
- "_type": "Value",
24
- "dtype": "string"
25
- },
26
- "label": {
27
- "_type": "Value",
28
- "dtype": "int8"
29
- }
30
- },
31
- "description": "Multi-choice, Sentiment classification task with numerical labels (Amazon-Review)."
32
- },
33
- "imdb": {
34
- "features": {
35
- "text": {
36
- "_type": "Value",
37
- "dtype": "string"
38
- },
39
- "label": {
40
- "_type": "ClassLabel",
41
- "names": [
42
- "Negative",
43
- "Positive"
44
- ]
45
- }
46
- },
47
- "description": "Binary sentiment classification (IMDB)."
48
- },
49
  "commensenseqa": {
50
  "features": {
51
  "text": {
@@ -55,8 +8,7 @@
55
  "options": {
56
  "feature": {
57
  "_type": "Value",
58
- "dtype": "string",
59
- "id": null
60
  },
61
  "length": 5,
62
  "_type": "Sequence"
@@ -67,65 +19,5 @@
67
  }
68
  },
69
  "description": "Multi-choice, Commense knowledge-answering datasets (CommensenseQA)."
70
- },
71
- "fever": {
72
- "features": {
73
- "text": {
74
- "_type": "Value",
75
- "dtype": "string"
76
- },
77
- "label": {
78
- "_type": "ClassLabel",
79
- "names": [
80
- "Incorrect",
81
- "Correct"
82
- ]
83
- }
84
- },
85
- "description": "Binary classification, fact-checking (FEVER)."
86
- },
87
- "myriadlama": {
88
- "features": {
89
- "text": {
90
- "_type": "Value",
91
- "dtype": "string"
92
- },
93
- "options": {
94
- "feature": {
95
- "dtype": "string",
96
- "id": null,
97
- "_type": "Value"
98
- },
99
- "length": 4,
100
- "_type": "Sequence"
101
- },
102
- "label": {
103
- "_type": "Value",
104
- "dtype": "int8"
105
- }
106
- },
107
- "description": "Multi-choice, open-domain knowledge question-answering (MyriadLAMA)."
108
- },
109
- "templama": {
110
- "features": {
111
- "text": {
112
- "_type": "Value",
113
- "dtype": "string"
114
- },
115
- "options": {
116
- "feature": {
117
- "dtype": "string",
118
- "id": null,
119
- "_type": "Value"
120
- },
121
- "length": 4,
122
- "_type": "Sequence"
123
- },
124
- "label": {
125
- "_type": "Value",
126
- "dtype": "int8"
127
- }
128
- },
129
- "description": "Multi-choice, open-domain temporary knowledge QA (TempLAMA)."
130
  }
131
  }
 
1
  {
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2
  "commensenseqa": {
3
  "features": {
4
  "text": {
 
8
  "options": {
9
  "feature": {
10
  "_type": "Value",
11
+ "dtype": "string"
 
12
  },
13
  "length": 5,
14
  "_type": "Sequence"
 
19
  }
20
  },
21
  "description": "Multi-choice, Commense knowledge-answering datasets (CommensenseQA)."
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
22
  }
23
  }
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