File size: 29,320 Bytes
064fab9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
352f732
064fab9
 
 
 
 
 
 
 
 
 
 
352f732
064fab9
352f732
064fab9
 
 
352f732
064fab9
352f732
064fab9
 
 
352f732
064fab9
352f732
064fab9
 
352f732
 
 
064fab9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d3e022f
064fab9
 
 
 
 
 
 
 
 
 
 
d3e022f
064fab9
d3e022f
064fab9
 
 
d3e022f
064fab9
d3e022f
064fab9
 
 
d3e022f
064fab9
d3e022f
064fab9
 
d3e022f
 
 
064fab9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ffa3e5f
064fab9
 
 
 
 
 
 
 
 
 
 
ffa3e5f
064fab9
ffa3e5f
064fab9
 
 
ffa3e5f
064fab9
ffa3e5f
064fab9
 
 
ffa3e5f
064fab9
ffa3e5f
064fab9
 
ffa3e5f
 
 
064fab9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6af614c
064fab9
 
 
 
 
 
 
 
 
 
 
6af614c
064fab9
6af614c
064fab9
 
 
6af614c
064fab9
6af614c
064fab9
 
 
6af614c
064fab9
6af614c
064fab9
 
6af614c
 
 
064fab9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
b7b8b58
064fab9
 
 
 
 
 
 
 
 
 
 
b7b8b58
064fab9
b7b8b58
064fab9
 
 
b7b8b58
064fab9
b7b8b58
064fab9
 
 
b7b8b58
064fab9
b7b8b58
064fab9
 
b7b8b58
 
 
064fab9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
{
    "ecthr_a": {
        "description": "The European Court of Human Rights (ECtHR) hears allegations that a state has\nbreached human rights provisions of the European Convention of Human Rights (ECHR).\nFor each case, the dataset provides a list of factual paragraphs (facts) from the case description.\nEach case is mapped to articles of the ECHR that were violated (if any).",
        "citation": "@inproceedings{chalkidis-etal-2021-paragraph,\n    title = \"Paragraph-level Rationale Extraction through Regularization: A case study on {E}uropean Court of Human Rights Cases\",\n    author = \"Chalkidis, Ilias  and\n      Fergadiotis, Manos  and\n      Tsarapatsanis, Dimitrios  and\n      Aletras, Nikolaos  and\n      Androutsopoulos, Ion  and\n      Malakasiotis, Prodromos\",\n    booktitle = \"Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies\",\n    month = jun,\n    year = \"2021\",\n    address = \"Online\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2021.naacl-main.22\",\n    doi = \"10.18653/v1/2021.naacl-main.22\",\n    pages = \"226--241\",\n}\n}\n@article{chalkidis-etal-2021-lexglue,\n      title={{LexGLUE}: A Benchmark Dataset for Legal Language Understanding in English},\n      author={Chalkidis, Ilias and\n      Jana, Abhik and\n      Hartung, Dirk and\n      Bommarito, Michael and\n      Androutsopoulos, Ion and\n      Katz, Daniel Martin and\n      Aletras, Nikolaos},\n      year={2021},\n      eprint={2110.00976},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL},\n      note = {arXiv: 2110.00976},\n}",
        "homepage": "https://archive.org/details/ECtHR-NAACL2021",
        "license": "",
        "features": {
            "text": {
                "feature": {
                    "dtype": "string",
                    "_type": "Value"
                },
                "_type": "Sequence"
            },
            "labels": {
                "feature": {
                    "names": [
                        "2",
                        "3",
                        "5",
                        "6",
                        "8",
                        "9",
                        "10",
                        "11",
                        "14",
                        "P1-1"
                    ],
                    "_type": "ClassLabel"
                },
                "_type": "Sequence"
            }
        },
        "builder_name": "lex_glue",
        "dataset_name": "lex_glue",
        "config_name": "ecthr_a",
        "version": {
            "version_str": "1.0.0",
            "description": "",
            "major": 1,
            "minor": 0,
            "patch": 0
        },
        "splits": {
            "train": {
                "name": "train",
                "num_bytes": 89637449,
                "num_examples": 9000,
                "dataset_name": null
            },
            "test": {
                "name": "test",
                "num_bytes": 11884168,
                "num_examples": 1000,
                "dataset_name": null
            },
            "validation": {
                "name": "validation",
                "num_bytes": 10985168,
                "num_examples": 1000,
                "dataset_name": null
            }
        },
        "download_size": 53352586,
        "dataset_size": 112506785,
        "size_in_bytes": 165859371
    },
    "ecthr_b": {
        "description": "The European Court of Human Rights (ECtHR) hears allegations that a state has\nbreached human rights provisions of the European Convention of Human Rights (ECHR).\nFor each case, the dataset provides a list of factual paragraphs (facts) from the case description.\nEach case is mapped to articles of ECHR that were allegedly violated (considered by the court).",
        "citation": "@inproceedings{chalkidis-etal-2021-paragraph,\n    title = \"Paragraph-level Rationale Extraction through Regularization: A case study on {E}uropean Court of Human Rights Cases\",\n    author = \"Chalkidis, Ilias\n    and Fergadiotis, Manos\n    and Tsarapatsanis, Dimitrios\n    and  Aletras, Nikolaos\n    and Androutsopoulos, Ion\n    and Malakasiotis, Prodromos\",\n    booktitle = \"Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies\",\n    year = \"2021\",\n    address = \"Online\",\n    url = \"https://aclanthology.org/2021.naacl-main.22\",\n}\n}\n@article{chalkidis-etal-2021-lexglue,\n      title={{LexGLUE}: A Benchmark Dataset for Legal Language Understanding in English},\n      author={Chalkidis, Ilias and\n      Jana, Abhik and\n      Hartung, Dirk and\n      Bommarito, Michael and\n      Androutsopoulos, Ion and\n      Katz, Daniel Martin and\n      Aletras, Nikolaos},\n      year={2021},\n      eprint={2110.00976},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL},\n      note = {arXiv: 2110.00976},\n}",
        "homepage": "https://archive.org/details/ECtHR-NAACL2021",
        "license": "",
        "features": {
            "text": {
                "feature": {
                    "dtype": "string",
                    "_type": "Value"
                },
                "_type": "Sequence"
            },
            "labels": {
                "feature": {
                    "names": [
                        "2",
                        "3",
                        "5",
                        "6",
                        "8",
                        "9",
                        "10",
                        "11",
                        "14",
                        "P1-1"
                    ],
                    "_type": "ClassLabel"
                },
                "_type": "Sequence"
            }
        },
        "builder_name": "lex_glue",
        "dataset_name": "lex_glue",
        "config_name": "ecthr_b",
        "version": {
            "version_str": "1.0.0",
            "description": "",
            "major": 1,
            "minor": 0,
            "patch": 0
        },
        "splits": {
            "train": {
                "name": "train",
                "num_bytes": 89657649,
                "num_examples": 9000,
                "dataset_name": null
            },
            "test": {
                "name": "test",
                "num_bytes": 11886928,
                "num_examples": 1000,
                "dataset_name": null
            },
            "validation": {
                "name": "validation",
                "num_bytes": 10987816,
                "num_examples": 1000,
                "dataset_name": null
            }
        },
        "download_size": 53352494,
        "dataset_size": 112532393,
        "size_in_bytes": 165884887
    },
    "eurlex": {
        "description": "European Union (EU) legislation is published in EUR-Lex portal.\nAll EU laws are annotated by EU's Publications Office with multiple concepts from the EuroVoc thesaurus,\na multilingual thesaurus maintained by the Publications Office.\nThe current version of EuroVoc contains more than 7k concepts referring to various activities\nof the EU and its Member States (e.g., economics, health-care, trade).\nGiven a document, the task is to predict its EuroVoc labels (concepts).",
        "citation": "@inproceedings{chalkidis-etal-2021-multieurlex,\n  author = {Chalkidis, Ilias and\n  Fergadiotis, Manos and\n  Androutsopoulos, Ion},\n  title = {MultiEURLEX -- A multi-lingual and multi-label legal document\n               classification dataset for zero-shot cross-lingual transfer},\n  booktitle = {Proceedings of the 2021 Conference on Empirical Methods\n               in Natural Language Processing},\n  year = {2021},\n  location = {Punta Cana, Dominican Republic},\n}\n}\n@article{chalkidis-etal-2021-lexglue,\n      title={{LexGLUE}: A Benchmark Dataset for Legal Language Understanding in English},\n      author={Chalkidis, Ilias and\n      Jana, Abhik and\n      Hartung, Dirk and\n      Bommarito, Michael and\n      Androutsopoulos, Ion and\n      Katz, Daniel Martin and\n      Aletras, Nikolaos},\n      year={2021},\n      eprint={2110.00976},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL},\n      note = {arXiv: 2110.00976},\n}",
        "homepage": "https://zenodo.org/record/5363165#.YVJOAi8RqaA",
        "license": "",
        "features": {
            "text": {
                "dtype": "string",
                "_type": "Value"
            },
            "labels": {
                "feature": {
                    "names": [
                        "100163",
                        "100168",
                        "100169",
                        "100170",
                        "100171",
                        "100172",
                        "100173",
                        "100174",
                        "100175",
                        "100176",
                        "100177",
                        "100179",
                        "100180",
                        "100183",
                        "100184",
                        "100185",
                        "100186",
                        "100187",
                        "100189",
                        "100190",
                        "100191",
                        "100192",
                        "100193",
                        "100194",
                        "100195",
                        "100196",
                        "100197",
                        "100198",
                        "100199",
                        "100200",
                        "100201",
                        "100202",
                        "100204",
                        "100205",
                        "100206",
                        "100207",
                        "100212",
                        "100214",
                        "100215",
                        "100220",
                        "100221",
                        "100222",
                        "100223",
                        "100224",
                        "100226",
                        "100227",
                        "100229",
                        "100230",
                        "100231",
                        "100232",
                        "100233",
                        "100234",
                        "100235",
                        "100237",
                        "100238",
                        "100239",
                        "100240",
                        "100241",
                        "100242",
                        "100243",
                        "100244",
                        "100245",
                        "100246",
                        "100247",
                        "100248",
                        "100249",
                        "100250",
                        "100252",
                        "100253",
                        "100254",
                        "100255",
                        "100256",
                        "100257",
                        "100258",
                        "100259",
                        "100260",
                        "100261",
                        "100262",
                        "100263",
                        "100264",
                        "100265",
                        "100266",
                        "100268",
                        "100269",
                        "100270",
                        "100271",
                        "100272",
                        "100273",
                        "100274",
                        "100275",
                        "100276",
                        "100277",
                        "100278",
                        "100279",
                        "100280",
                        "100281",
                        "100282",
                        "100283",
                        "100284",
                        "100285"
                    ],
                    "_type": "ClassLabel"
                },
                "_type": "Sequence"
            }
        },
        "builder_name": "lex_glue",
        "dataset_name": "lex_glue",
        "config_name": "eurlex",
        "version": {
            "version_str": "1.0.0",
            "description": "",
            "major": 1,
            "minor": 0,
            "patch": 0
        },
        "splits": {
            "train": {
                "name": "train",
                "num_bytes": 390770241,
                "num_examples": 55000,
                "dataset_name": null
            },
            "test": {
                "name": "test",
                "num_bytes": 59739094,
                "num_examples": 5000,
                "dataset_name": null
            },
            "validation": {
                "name": "validation",
                "num_bytes": 41544476,
                "num_examples": 5000,
                "dataset_name": null
            }
        },
        "download_size": 208028049,
        "dataset_size": 492053811,
        "size_in_bytes": 700081860
    },
    "scotus": {
        "description": "The US Supreme Court  (SCOTUS) is the highest federal court in the United States of America\nand generally hears only the most controversial or otherwise complex cases which have not\nbeen sufficiently well solved by lower courts. This is a single-label multi-class classification\ntask, where given a document (court opinion), the task is to predict the relevant issue areas.\nThe 14 issue areas cluster 278 issues whose focus is on the subject matter of the controversy (dispute).",
        "citation": "@misc{spaeth2020,\n author = {Harold J. Spaeth and Lee Epstein and Andrew D. Martin, Jeffrey A. Segal\n and Theodore J. Ruger and Sara C. Benesh},\n year = {2020},\n title ={{Supreme Court Database, Version 2020 Release 01}},\n url= {http://Supremecourtdatabase.org},\n howpublished={Washington University Law}\n}\n@article{chalkidis-etal-2021-lexglue,\n      title={{LexGLUE}: A Benchmark Dataset for Legal Language Understanding in English},\n      author={Chalkidis, Ilias and\n      Jana, Abhik and\n      Hartung, Dirk and\n      Bommarito, Michael and\n      Androutsopoulos, Ion and\n      Katz, Daniel Martin and\n      Aletras, Nikolaos},\n      year={2021},\n      eprint={2110.00976},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL},\n      note = {arXiv: 2110.00976},\n}",
        "homepage": "http://scdb.wustl.edu/data.php",
        "license": "",
        "features": {
            "text": {
                "dtype": "string",
                "_type": "Value"
            },
            "label": {
                "names": [
                    "1",
                    "2",
                    "3",
                    "4",
                    "5",
                    "6",
                    "7",
                    "8",
                    "9",
                    "10",
                    "11",
                    "12",
                    "13"
                ],
                "_type": "ClassLabel"
            }
        },
        "builder_name": "lex_glue",
        "dataset_name": "lex_glue",
        "config_name": "scotus",
        "version": {
            "version_str": "1.0.0",
            "description": "",
            "major": 1,
            "minor": 0,
            "patch": 0
        },
        "splits": {
            "train": {
                "name": "train",
                "num_bytes": 178959316,
                "num_examples": 5000,
                "dataset_name": null
            },
            "test": {
                "name": "test",
                "num_bytes": 76213279,
                "num_examples": 1400,
                "dataset_name": null
            },
            "validation": {
                "name": "validation",
                "num_bytes": 75600243,
                "num_examples": 1400,
                "dataset_name": null
            }
        },
        "download_size": 173411399,
        "dataset_size": 330772838,
        "size_in_bytes": 504184237
    },
    "ledgar": {
        "description": "LEDGAR dataset aims contract provision (paragraph) classification.\nThe contract provisions come from contracts obtained from the US Securities and Exchange Commission (SEC)\nfilings, which are publicly available from EDGAR. Each label represents the single main topic\n(theme) of the corresponding contract provision.",
        "citation": "@inproceedings{tuggener-etal-2020-ledgar,\n    title = \"{LEDGAR}: A Large-Scale Multi-label Corpus for Text Classification of Legal Provisions in Contracts\",\n    author = {Tuggener, Don  and\n      von D{\"a}niken, Pius  and\n      Peetz, Thomas  and\n      Cieliebak, Mark},\n    booktitle = \"Proceedings of the 12th Language Resources and Evaluation Conference\",\n    year = \"2020\",\n    address = \"Marseille, France\",\n    url = \"https://aclanthology.org/2020.lrec-1.155\",\n}\n}\n@article{chalkidis-etal-2021-lexglue,\n      title={{LexGLUE}: A Benchmark Dataset for Legal Language Understanding in English},\n      author={Chalkidis, Ilias and\n      Jana, Abhik and\n      Hartung, Dirk and\n      Bommarito, Michael and\n      Androutsopoulos, Ion and\n      Katz, Daniel Martin and\n      Aletras, Nikolaos},\n      year={2021},\n      eprint={2110.00976},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL},\n      note = {arXiv: 2110.00976},\n}",
        "homepage": "https://metatext.io/datasets/ledgar",
        "license": "",
        "features": {
            "text": {
                "dtype": "string",
                "_type": "Value"
            },
            "label": {
                "names": [
                    "Adjustments",
                    "Agreements",
                    "Amendments",
                    "Anti-Corruption Laws",
                    "Applicable Laws",
                    "Approvals",
                    "Arbitration",
                    "Assignments",
                    "Assigns",
                    "Authority",
                    "Authorizations",
                    "Base Salary",
                    "Benefits",
                    "Binding Effects",
                    "Books",
                    "Brokers",
                    "Capitalization",
                    "Change In Control",
                    "Closings",
                    "Compliance With Laws",
                    "Confidentiality",
                    "Consent To Jurisdiction",
                    "Consents",
                    "Construction",
                    "Cooperation",
                    "Costs",
                    "Counterparts",
                    "Death",
                    "Defined Terms",
                    "Definitions",
                    "Disability",
                    "Disclosures",
                    "Duties",
                    "Effective Dates",
                    "Effectiveness",
                    "Employment",
                    "Enforceability",
                    "Enforcements",
                    "Entire Agreements",
                    "Erisa",
                    "Existence",
                    "Expenses",
                    "Fees",
                    "Financial Statements",
                    "Forfeitures",
                    "Further Assurances",
                    "General",
                    "Governing Laws",
                    "Headings",
                    "Indemnifications",
                    "Indemnity",
                    "Insurances",
                    "Integration",
                    "Intellectual Property",
                    "Interests",
                    "Interpretations",
                    "Jurisdictions",
                    "Liens",
                    "Litigations",
                    "Miscellaneous",
                    "Modifications",
                    "No Conflicts",
                    "No Defaults",
                    "No Waivers",
                    "Non-Disparagement",
                    "Notices",
                    "Organizations",
                    "Participations",
                    "Payments",
                    "Positions",
                    "Powers",
                    "Publicity",
                    "Qualifications",
                    "Records",
                    "Releases",
                    "Remedies",
                    "Representations",
                    "Sales",
                    "Sanctions",
                    "Severability",
                    "Solvency",
                    "Specific Performance",
                    "Submission To Jurisdiction",
                    "Subsidiaries",
                    "Successors",
                    "Survival",
                    "Tax Withholdings",
                    "Taxes",
                    "Terminations",
                    "Terms",
                    "Titles",
                    "Transactions With Affiliates",
                    "Use Of Proceeds",
                    "Vacations",
                    "Venues",
                    "Vesting",
                    "Waiver Of Jury Trials",
                    "Waivers",
                    "Warranties",
                    "Withholdings"
                ],
                "_type": "ClassLabel"
            }
        },
        "builder_name": "lex_glue",
        "dataset_name": "lex_glue",
        "config_name": "ledgar",
        "version": {
            "version_str": "1.0.0",
            "description": "",
            "major": 1,
            "minor": 0,
            "patch": 0
        },
        "splits": {
            "train": {
                "name": "train",
                "num_bytes": 43358291,
                "num_examples": 60000,
                "dataset_name": null
            },
            "test": {
                "name": "test",
                "num_bytes": 6845581,
                "num_examples": 10000,
                "dataset_name": null
            },
            "validation": {
                "name": "validation",
                "num_bytes": 7143588,
                "num_examples": 10000,
                "dataset_name": null
            }
        },
        "download_size": 27650585,
        "dataset_size": 57347460,
        "size_in_bytes": 84998045
    },
    "unfair_tos": {
        "description": "The UNFAIR-ToS dataset contains 50 Terms of Service (ToS) from on-line platforms (e.g., YouTube,\nEbay, Facebook, etc.). The dataset has been annotated on the sentence-level with 8 types of\nunfair contractual terms (sentences), meaning terms that potentially violate user rights\naccording to the European consumer law.",
        "citation": "@article{lippi-etal-2019-claudette,\n    title = \"{CLAUDETTE}: an automated detector of potentially unfair clauses in online terms of service\",\n    author = {Lippi, Marco\n    and Pa\u0142ka, Przemys\u0142aw\n    and Contissa, Giuseppe\n    and Lagioia, Francesca\n    and Micklitz, Hans-Wolfgang\n    and Sartor, Giovanni\n    and Torroni, Paolo},\n    journal = \"Artificial Intelligence and Law\",\n    year = \"2019\",\n    publisher = \"Springer\",\n    url = \"https://doi.org/10.1007/s10506-019-09243-2\",\n    pages = \"117--139\",\n}\n@article{chalkidis-etal-2021-lexglue,\n      title={{LexGLUE}: A Benchmark Dataset for Legal Language Understanding in English},\n      author={Chalkidis, Ilias and\n      Jana, Abhik and\n      Hartung, Dirk and\n      Bommarito, Michael and\n      Androutsopoulos, Ion and\n      Katz, Daniel Martin and\n      Aletras, Nikolaos},\n      year={2021},\n      eprint={2110.00976},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL},\n      note = {arXiv: 2110.00976},\n}",
        "homepage": "http://claudette.eui.eu",
        "license": "",
        "features": {
            "text": {
                "dtype": "string",
                "_type": "Value"
            },
            "labels": {
                "feature": {
                    "names": [
                        "Limitation of liability",
                        "Unilateral termination",
                        "Unilateral change",
                        "Content removal",
                        "Contract by using",
                        "Choice of law",
                        "Jurisdiction",
                        "Arbitration"
                    ],
                    "_type": "ClassLabel"
                },
                "_type": "Sequence"
            }
        },
        "builder_name": "lex_glue",
        "dataset_name": "lex_glue",
        "config_name": "unfair_tos",
        "version": {
            "version_str": "1.0.0",
            "description": "",
            "major": 1,
            "minor": 0,
            "patch": 0
        },
        "splits": {
            "train": {
                "name": "train",
                "num_bytes": 1041782,
                "num_examples": 5532,
                "dataset_name": null
            },
            "test": {
                "name": "test",
                "num_bytes": 303099,
                "num_examples": 1607,
                "dataset_name": null
            },
            "validation": {
                "name": "validation",
                "num_bytes": 452111,
                "num_examples": 2275,
                "dataset_name": null
            }
        },
        "download_size": 865604,
        "dataset_size": 1796992,
        "size_in_bytes": 2662596
    },
    "case_hold": {
        "description": "The CaseHOLD (Case Holdings on Legal Decisions) dataset contains approx. 53k multiple choice\nquestions about holdings of US court cases from the Harvard Law Library case law corpus.\nHoldings are short summaries of legal rulings accompany referenced decisions relevant for the present case.\nThe input consists of an excerpt (or prompt) from a court decision, containing a reference\nto a particular case, while the holding statement is masked out. The model must identify\nthe correct (masked) holding statement from a selection of five choices.",
        "citation": "@inproceedings{Zheng2021,\n  author    = {Lucia Zheng and\n               Neel Guha and\n               Brandon R. Anderson and\n               Peter Henderson and\n               Daniel E. Ho},\n  title     = {When Does Pretraining Help? Assessing Self-Supervised Learning for\n               Law and the CaseHOLD Dataset},\n  year      = {2021},\n  booktitle = {International Conference on Artificial Intelligence and Law},\n}\n@article{chalkidis-etal-2021-lexglue,\n      title={{LexGLUE}: A Benchmark Dataset for Legal Language Understanding in English},\n      author={Chalkidis, Ilias and\n      Jana, Abhik and\n      Hartung, Dirk and\n      Bommarito, Michael and\n      Androutsopoulos, Ion and\n      Katz, Daniel Martin and\n      Aletras, Nikolaos},\n      year={2021},\n      eprint={2110.00976},\n      archivePrefix={arXiv},\n      primaryClass={cs.CL},\n      note = {arXiv: 2110.00976},\n}",
        "homepage": "https://github.com/reglab/casehold",
        "license": "",
        "features": {
            "context": {
                "dtype": "string",
                "id": null,
                "_type": "Value"
            },
            "endings": {
                "feature": {
                    "dtype": "string",
                    "id": null,
                    "_type": "Value"
                },
                "length": -1,
                "id": null,
                "_type": "Sequence"
            },
            "label": {
                "num_classes": 5,
                "names": [
                    "0",
                    "1",
                    "2",
                    "3",
                    "4"
                ],
                "id": null,
                "_type": "ClassLabel"
            }
        },
        "post_processed": null,
        "supervised_keys": null,
        "task_templates": null,
        "builder_name": "lex_glue",
        "config_name": "case_hold",
        "version": {
            "version_str": "1.0.0",
            "description": "",
            "major": 1,
            "minor": 0,
            "patch": 0
        },
        "splits": {
            "train": {
                "name": "train",
                "num_bytes": 74781766,
                "num_examples": 45000,
                "dataset_name": "lex_glue"
            },
            "test": {
                "name": "test",
                "num_bytes": 5989964,
                "num_examples": 3600,
                "dataset_name": "lex_glue"
            },
            "validation": {
                "name": "validation",
                "num_bytes": 6474615,
                "num_examples": 3900,
                "dataset_name": "lex_glue"
            }
        },
        "download_checksums": {
            "https://zenodo.org/record/5532997/files/casehold.tar.gz": {
                "num_bytes": 30422703,
                "checksum": "728827dae0019880fe6be609e23f8c47fa2b49a2f0814a36687ace8db1c32d5e"
            }
        },
        "download_size": 30422703,
        "post_processing_size": null,
        "dataset_size": 87246345,
        "size_in_bytes": 117669048
    }
}