File size: 20,623 Bytes
ea7ef1c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5c4c929
0576443
 
 
5c4c929
 
 
 
 
 
 
7862326
0576443
 
 
 
 
 
5c4c929
7862326
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5c4c929
 
 
 
 
 
 
7862326
0576443
 
 
 
 
 
7862326
 
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5c4c929
 
 
 
 
7862326
0576443
 
 
 
 
 
 
 
 
7862326
 
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f064aae
0576443
 
 
5c4c929
 
 
 
 
7862326
0576443
 
 
 
 
 
f064aae
7862326
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5c4c929
 
 
 
7862326
0576443
 
 
 
 
 
7862326
 
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5c4c929
 
 
 
7862326
0576443
 
 
 
 
 
7862326
 
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
5db908a
0576443
 
 
5c4c929
 
7862326
0576443
 
 
 
 
 
5db908a
7862326
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5c4c929
 
7862326
0576443
 
 
 
 
 
7862326
 
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5c4c929
 
 
7862326
0576443
 
 
 
 
 
7862326
 
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
a106cbd
0576443
 
 
5c4c929
 
 
7862326
0576443
 
 
 
 
 
a106cbd
7862326
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5c4c929
 
7862326
0576443
 
 
 
 
 
7862326
 
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5c4c929
 
7862326
0576443
 
 
 
 
 
7862326
 
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
9d01d80
0576443
 
 
5c4c929
 
 
7862326
0576443
 
 
 
 
 
9d01d80
7862326
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5c4c929
 
 
7862326
0576443
 
 
 
 
 
7862326
 
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
5c4c929
 
 
 
 
7862326
0576443
 
 
 
 
 
7862326
 
ea7ef1c
7862326
0576443
 
 
 
 
 
 
 
 
 
 
 
 
 
5c4c929
 
 
 
 
7862326
0576443
 
 
 
 
 
7862326
 
5c4c929
 
 
 
 
 
 
f064aae
 
 
 
 
 
5db908a
 
 
 
 
 
a106cbd
 
 
 
 
 
9d01d80
 
 
 
 
 
ea7ef1c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0b61f4b
ebab8c1
0b61f4b
ea7ef1c
 
 
 
 
 
 
 
 
 
 
 
 
ebab8c1
0b61f4b
ea7ef1c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
---
annotations_creators:
- crowdsourced
language_creators:
- other
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<200K
source_datasets:
- extended|other
task_categories:
- text-classification
task_ids:
- natural-language-inference
- sentiment-analysis
- hate-speech-detection
paperswithcode_id: placeholder
pretty_name: TID-8
tags:
- tid8
- annotation disagreement
dataset_info:
- config_name: commitmentbank-ann
  features:
  - name: HitID
    dtype: string
  - name: Verb
    dtype: string
  - name: Context
    dtype: string
  - name: Prompt
    dtype: string
  - name: Target
    dtype: string
  - name: ModalType
    dtype: string
  - name: Embedding
    dtype: string
  - name: MatTense
    dtype: string
  - name: weak_labels
    sequence: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: answer_label
    dtype:
      class_label:
        names:
          '0': '0'
          '1': '1'
          '2': '2'
          '3': '3'
          '4': '-3'
          '5': '-1'
          '6': '-2'
  splits:
  - name: train
    num_bytes: 7153364
    num_examples: 7816
  - name: test
    num_bytes: 3353745
    num_examples: 3729
  download_size: 3278616
  dataset_size: 10507109
- config_name: commitmentbank-atr
  features:
  - name: HitID
    dtype: string
  - name: Verb
    dtype: string
  - name: Context
    dtype: string
  - name: Prompt
    dtype: string
  - name: Target
    dtype: string
  - name: ModalType
    dtype: string
  - name: Embedding
    dtype: string
  - name: MatTense
    dtype: string
  - name: weak_labels
    sequence: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': '0'
          '1': '1'
          '2': '2'
          '3': '3'
          '4': '-3'
          '5': '-1'
          '6': '-2'
  splits:
  - name: train
    num_bytes: 6636145
    num_examples: 7274
  - name: test
    num_bytes: 3870964
    num_examples: 4271
  download_size: 1942215
  dataset_size: 10507109
- config_name: friends_qia-ann
  features:
  - name: Season
    dtype: string
  - name: Episode
    dtype: string
  - name: Category
    dtype: string
  - name: Q_person
    dtype: string
  - name: A_person
    dtype: string
  - name: Q_original
    dtype: string
  - name: Q_modified
    dtype: string
  - name: A_modified
    dtype: string
  - name: Annotation_1
    dtype: string
  - name: Annotation_2
    dtype: string
  - name: Annotation_3
    dtype: string
  - name: Goldstandard
    dtype: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': '1'
          '1': '2'
          '2': '3'
          '3': '4'
          '4': '5'
  splits:
  - name: validation
    num_bytes: 687135
    num_examples: 1872
  - name: train
    num_bytes: 4870170
    num_examples: 13113
  - name: test
    num_bytes: 693033
    num_examples: 1872
  download_size: 818058
  dataset_size: 6250338
- config_name: friends_qia-atr
  features:
  - name: Season
    dtype: string
  - name: Episode
    dtype: string
  - name: Category
    dtype: string
  - name: Q_person
    dtype: string
  - name: A_person
    dtype: string
  - name: Q_original
    dtype: string
  - name: Q_modified
    dtype: string
  - name: A_modified
    dtype: string
  - name: Annotation_1
    dtype: string
  - name: Annotation_2
    dtype: string
  - name: Annotation_3
    dtype: string
  - name: Goldstandard
    dtype: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: answer_label
    dtype:
      class_label:
        names:
          '0': '1'
          '1': '2'
          '2': '3'
          '3': '4'
          '4': '5'
  splits:
  - name: train
    num_bytes: 4166892
    num_examples: 11238
  - name: test
    num_bytes: 2083446
    num_examples: 5619
  download_size: 3445839
  dataset_size: 6250338
- config_name: goemotions-ann
  features:
  - name: author
    dtype: string
  - name: subreddit
    dtype: string
  - name: link_id
    dtype: string
  - name: parent_id
    dtype: string
  - name: created_utc
    dtype: string
  - name: rater_id
    dtype: string
  - name: example_very_unclear
    dtype: string
  - name: admiration
    dtype: string
  - name: amusement
    dtype: string
  - name: anger
    dtype: string
  - name: annoyance
    dtype: string
  - name: approval
    dtype: string
  - name: caring
    dtype: string
  - name: confusion
    dtype: string
  - name: curiosity
    dtype: string
  - name: desire
    dtype: string
  - name: disappointment
    dtype: string
  - name: disapproval
    dtype: string
  - name: disgust
    dtype: string
  - name: embarrassment
    dtype: string
  - name: excitement
    dtype: string
  - name: fear
    dtype: string
  - name: gratitude
    dtype: string
  - name: grief
    dtype: string
  - name: joy
    dtype: string
  - name: love
    dtype: string
  - name: nervousness
    dtype: string
  - name: optimism
    dtype: string
  - name: pride
    dtype: string
  - name: realization
    dtype: string
  - name: relief
    dtype: string
  - name: remorse
    dtype: string
  - name: sadness
    dtype: string
  - name: surprise
    dtype: string
  - name: neutral
    dtype: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': positive
          '1': ambiguous
          '2': negative
          '3': neutral
  splits:
  - name: train
    num_bytes: 46277072
    num_examples: 135504
  - name: test
    num_bytes: 19831033
    num_examples: 58129
  download_size: 19388288
  dataset_size: 66108105
- config_name: goemotions-atr
  features:
  - name: author
    dtype: string
  - name: subreddit
    dtype: string
  - name: link_id
    dtype: string
  - name: parent_id
    dtype: string
  - name: created_utc
    dtype: string
  - name: rater_id
    dtype: string
  - name: example_very_unclear
    dtype: string
  - name: admiration
    dtype: string
  - name: amusement
    dtype: string
  - name: anger
    dtype: string
  - name: annoyance
    dtype: string
  - name: approval
    dtype: string
  - name: caring
    dtype: string
  - name: confusion
    dtype: string
  - name: curiosity
    dtype: string
  - name: desire
    dtype: string
  - name: disappointment
    dtype: string
  - name: disapproval
    dtype: string
  - name: disgust
    dtype: string
  - name: embarrassment
    dtype: string
  - name: excitement
    dtype: string
  - name: fear
    dtype: string
  - name: gratitude
    dtype: string
  - name: grief
    dtype: string
  - name: joy
    dtype: string
  - name: love
    dtype: string
  - name: nervousness
    dtype: string
  - name: optimism
    dtype: string
  - name: pride
    dtype: string
  - name: realization
    dtype: string
  - name: relief
    dtype: string
  - name: remorse
    dtype: string
  - name: sadness
    dtype: string
  - name: surprise
    dtype: string
  - name: neutral
    dtype: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': positive
          '1': ambiguous
          '2': negative
          '3': neutral
  splits:
  - name: train
    num_bytes: 44856233
    num_examples: 131395
  - name: test
    num_bytes: 21251872
    num_examples: 62238
  download_size: 19146912
  dataset_size: 66108105
- config_name: hs_brexit-ann
  features:
  - name: other annotations
    dtype: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: answer_label
    dtype:
      class_label:
        names:
          '0': hate_speech
          '1': not_hate_speech
  splits:
  - name: train
    num_bytes: 1039008
    num_examples: 4704
  - name: test
    num_bytes: 222026
    num_examples: 1008
  download_size: 144072
  dataset_size: 1261034
- config_name: hs_brexit-atr
  features:
  - name: other annotations
    dtype: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': hate_speech
          '1': not_hate_speech
  splits:
  - name: train
    num_bytes: 986132
    num_examples: 4480
  - name: test
    num_bytes: 495738
    num_examples: 2240
  download_size: 408475
  dataset_size: 1481870
- config_name: humor-ann
  features:
  - name: text_a
    dtype: string
  - name: text_b
    dtype: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': B
          '1': X
          '2': A
  splits:
  - name: train
    num_bytes: 28524839
    num_examples: 98735
  - name: test
    num_bytes: 12220621
    num_examples: 42315
  download_size: 10682583
  dataset_size: 40745460
- config_name: humor-atr
  features:
  - name: text_a
    dtype: string
  - name: text_b
    dtype: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: answer_label
    dtype:
      class_label:
        names:
          '0': B
          '1': X
          '2': A
  splits:
  - name: train
    num_bytes: 28161248
    num_examples: 97410
  - name: test
    num_bytes: 12584212
    num_examples: 43640
  download_size: 24099282
  dataset_size: 40745460
- config_name: md-agreement-ann
  features:
  - name: task
    dtype: string
  - name: original_id
    dtype: string
  - name: domain
    dtype: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': offensive_speech
          '1': not_offensive_speech
  splits:
  - name: train
    num_bytes: 7794988
    num_examples: 32960
  - name: test
    num_bytes: 2498445
    num_examples: 10553
  download_size: 1414114
  dataset_size: 10293433
- config_name: md-agreement-atr
  features:
  - name: task
    dtype: string
  - name: original_id
    dtype: string
  - name: domain
    dtype: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': offensive_speech
          '1': not_offensive_speech
  splits:
  - name: train
    num_bytes: 8777085
    num_examples: 37077
  - name: test
    num_bytes: 3957021
    num_examples: 16688
  download_size: 4121140
  dataset_size: 12734106
- config_name: pejorative-ann
  features:
  - name: pejor_word
    dtype: string
  - name: word_definition
    dtype: string
  - name: annotator-1
    dtype: string
  - name: annotator-2
    dtype: string
  - name: annotator-3
    dtype: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: answer_label
    dtype:
      class_label:
        names:
          '0': pejorative
          '1': non-pejorative
          '2': undecided
  splits:
  - name: train
    num_bytes: 350734
    num_examples: 1535
  - name: test
    num_bytes: 150894
    num_examples: 659
  download_size: 168346
  dataset_size: 501628
- config_name: pejorative-atr
  features:
  - name: pejor_word
    dtype: string
  - name: word_definition
    dtype: string
  - name: annotator-1
    dtype: string
  - name: annotator-2
    dtype: string
  - name: annotator-3
    dtype: string
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': pejorative
          '1': non-pejorative
          '2': undecided
  splits:
  - name: train
    num_bytes: 254138
    num_examples: 1112
  - name: test
    num_bytes: 247490
    num_examples: 1082
  download_size: 135023
  dataset_size: 501628
- config_name: sentiment-ann
  features:
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': Neutral
          '1': Somewhat positive
          '2': Very negative
          '3': Somewhat negative
          '4': Very positive
  splits:
  - name: train
    num_bytes: 9350333
    num_examples: 59235
  - name: test
    num_bytes: 235013
    num_examples: 1419
  download_size: 3371941
  dataset_size: 9585346
- config_name: sentiment-atr
  features:
  - name: question
    dtype: string
  - name: uid
    dtype: string
  - name: id
    dtype: int32
  - name: annotator_id
    dtype: string
  - name: answer
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': Neutral
          '1': Somewhat positive
          '2': Very negative
          '3': Somewhat negative
          '4': Very positive
  splits:
  - name: train
    num_bytes: 6712084
    num_examples: 42439
  - name: test
    num_bytes: 2873262
    num_examples: 18215
  download_size: 3352022
  dataset_size: 9585346
configs:
- config_name: commitmentbank-ann
  data_files:
  - split: train
    path: commitmentbank-ann/train-*
  - split: test
    path: commitmentbank-ann/test-*
- config_name: friends_qia-atr
  data_files:
  - split: train
    path: friends_qia-atr/train-*
  - split: test
    path: friends_qia-atr/test-*
- config_name: hs_brexit-ann
  data_files:
  - split: train
    path: hs_brexit-ann/train-*
  - split: test
    path: hs_brexit-ann/test-*
- config_name: humor-atr
  data_files:
  - split: train
    path: humor-atr/train-*
  - split: test
    path: humor-atr/test-*
- config_name: pejorative-ann
  data_files:
  - split: train
    path: pejorative-ann/train-*
  - split: test
    path: pejorative-ann/test-*
---

# Dataset Card for "TID-8"

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** placeholder
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Dataset Summary

TID-8 is a new benchmark focused on the task of letting models learn from data that has inherent disagreement.


*Annotation Split*

We split the annotations for each annotator into train and test set.

In other words, the same set of annotators appear in both train, (val),
and test sets.

For datasets that have splits originally, we follow the original split and remove
datapoints in test sets that are annotated by an annotator who is not in
the training set.

For datasets that do not have splits originally, we split the data into 
train and test set for convenience, you may further split the train set
into a train and val set.

*Annotator Split*

We split annotators into train and test set.

In other words, a different set of annotators would appear in train and test sets.

We split the data into train and test set for convenience, you may consider
further splitting the train set into a train and val set for performance validation.

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances


### Data Fields

The data fields are the same among all splits.
See aforementioned information.

### Data Splits

See aforementioned information.

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Citation Information

```
@inproceedings{deng2023tid8,
  title={You Are What You Annotate: Towards Better Models through Annotator Representations},
  author={Deng, Naihao and Liu, Siyang and Zhang, Frederick Xinliang and Wu, Winston and Wang, Lu and Mihalcea, Rada},
  booktitle={Findings of EMNLP 2023},
  year={2023}
}

Note that each TID-8 dataset has its own citation. Please see the source to
get the correct citation for each contained dataset.
```