Datasets:

Multilinguality:
multilingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
ArXiv:
License:
lhoestq HF staff commited on
Commit
0f037dc
1 Parent(s): 2e73d6a

add dataset_info in dataset metadata

Browse files
Files changed (1) hide show
  1. README.md +1080 -22
README.md CHANGED
@@ -5,29 +5,29 @@ annotations_creators:
5
  language_creators:
6
  - found
7
  language:
8
- - bg
9
- - cs
10
- - da
11
- - de
12
- - el
13
  - en
14
- - es
15
- - et
16
- - fi
17
- - fr
18
- - hr
19
- - hu
20
- - it
21
- - lt
22
- - lv
23
  - mt
24
- - nl
25
- - pl
26
- - pt
27
- - ro
28
- - sk
29
- - sl
30
- - sv
31
  license:
32
  - cc-by-sa-4.0
33
  multilinguality:
@@ -41,6 +41,1064 @@ task_categories:
41
  task_ids:
42
  - multi-label-classification
43
  - topic-classification
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
44
  ---
45
 
46
  # Dataset Card for "MultiEURLEX"
@@ -324,4 +1382,4 @@ Read more: https://eur-lex.europa.eu/content/help/faq/reuse-contents-eurlex.htm
324
 
325
  ### Contributions
326
 
327
- Thanks to [@iliaschalkidis](https://github.com/iliaschalkidis) for adding this dataset.
 
5
  language_creators:
6
  - found
7
  language:
8
+ - bg
9
+ - cs
10
+ - da
11
+ - de
12
+ - el
13
  - en
14
+ - es
15
+ - et
16
+ - fi
17
+ - fr
18
+ - hr
19
+ - hu
20
+ - it
21
+ - lt
22
+ - lv
23
  - mt
24
+ - nl
25
+ - pl
26
+ - pt
27
+ - ro
28
+ - sk
29
+ - sl
30
+ - sv
31
  license:
32
  - cc-by-sa-4.0
33
  multilinguality:
 
41
  task_ids:
42
  - multi-label-classification
43
  - topic-classification
44
+ dataset_info:
45
+ - config_name: en
46
+ features:
47
+ - name: celex_id
48
+ dtype: string
49
+ - name: text
50
+ dtype: string
51
+ - name: labels
52
+ sequence:
53
+ class_label:
54
+ names:
55
+ 0: '100149'
56
+ 1: '100160'
57
+ 2: '100148'
58
+ 3: '100147'
59
+ 4: '100152'
60
+ 5: '100143'
61
+ 6: '100156'
62
+ 7: '100158'
63
+ 8: '100154'
64
+ 9: '100153'
65
+ 10: '100142'
66
+ 11: '100145'
67
+ 12: '100150'
68
+ 13: '100162'
69
+ 14: '100159'
70
+ 15: '100144'
71
+ 16: '100151'
72
+ 17: '100157'
73
+ 18: '100161'
74
+ 19: '100146'
75
+ 20: '100155'
76
+ splits:
77
+ - name: test
78
+ num_bytes: 58966963
79
+ num_examples: 5000
80
+ - name: train
81
+ num_bytes: 389250183
82
+ num_examples: 55000
83
+ - name: validation
84
+ num_bytes: 41516165
85
+ num_examples: 5000
86
+ download_size: 2770050147
87
+ dataset_size: 489733311
88
+ - config_name: da
89
+ features:
90
+ - name: celex_id
91
+ dtype: string
92
+ - name: text
93
+ dtype: string
94
+ - name: labels
95
+ sequence:
96
+ class_label:
97
+ names:
98
+ 0: '100149'
99
+ 1: '100160'
100
+ 2: '100148'
101
+ 3: '100147'
102
+ 4: '100152'
103
+ 5: '100143'
104
+ 6: '100156'
105
+ 7: '100158'
106
+ 8: '100154'
107
+ 9: '100153'
108
+ 10: '100142'
109
+ 11: '100145'
110
+ 12: '100150'
111
+ 13: '100162'
112
+ 14: '100159'
113
+ 15: '100144'
114
+ 16: '100151'
115
+ 17: '100157'
116
+ 18: '100161'
117
+ 19: '100146'
118
+ 20: '100155'
119
+ splits:
120
+ - name: test
121
+ num_bytes: 60343696
122
+ num_examples: 5000
123
+ - name: train
124
+ num_bytes: 395774777
125
+ num_examples: 55000
126
+ - name: validation
127
+ num_bytes: 42366390
128
+ num_examples: 5000
129
+ download_size: 2770050147
130
+ dataset_size: 498484863
131
+ - config_name: de
132
+ features:
133
+ - name: celex_id
134
+ dtype: string
135
+ - name: text
136
+ dtype: string
137
+ - name: labels
138
+ sequence:
139
+ class_label:
140
+ names:
141
+ 0: '100149'
142
+ 1: '100160'
143
+ 2: '100148'
144
+ 3: '100147'
145
+ 4: '100152'
146
+ 5: '100143'
147
+ 6: '100156'
148
+ 7: '100158'
149
+ 8: '100154'
150
+ 9: '100153'
151
+ 10: '100142'
152
+ 11: '100145'
153
+ 12: '100150'
154
+ 13: '100162'
155
+ 14: '100159'
156
+ 15: '100144'
157
+ 16: '100151'
158
+ 17: '100157'
159
+ 18: '100161'
160
+ 19: '100146'
161
+ 20: '100155'
162
+ splits:
163
+ - name: test
164
+ num_bytes: 65739074
165
+ num_examples: 5000
166
+ - name: train
167
+ num_bytes: 425489905
168
+ num_examples: 55000
169
+ - name: validation
170
+ num_bytes: 46079574
171
+ num_examples: 5000
172
+ download_size: 2770050147
173
+ dataset_size: 537308553
174
+ - config_name: nl
175
+ features:
176
+ - name: celex_id
177
+ dtype: string
178
+ - name: text
179
+ dtype: string
180
+ - name: labels
181
+ sequence:
182
+ class_label:
183
+ names:
184
+ 0: '100149'
185
+ 1: '100160'
186
+ 2: '100148'
187
+ 3: '100147'
188
+ 4: '100152'
189
+ 5: '100143'
190
+ 6: '100156'
191
+ 7: '100158'
192
+ 8: '100154'
193
+ 9: '100153'
194
+ 10: '100142'
195
+ 11: '100145'
196
+ 12: '100150'
197
+ 13: '100162'
198
+ 14: '100159'
199
+ 15: '100144'
200
+ 16: '100151'
201
+ 17: '100157'
202
+ 18: '100161'
203
+ 19: '100146'
204
+ 20: '100155'
205
+ splits:
206
+ - name: test
207
+ num_bytes: 64728034
208
+ num_examples: 5000
209
+ - name: train
210
+ num_bytes: 430232783
211
+ num_examples: 55000
212
+ - name: validation
213
+ num_bytes: 45452550
214
+ num_examples: 5000
215
+ download_size: 2770050147
216
+ dataset_size: 540413367
217
+ - config_name: sv
218
+ features:
219
+ - name: celex_id
220
+ dtype: string
221
+ - name: text
222
+ dtype: string
223
+ - name: labels
224
+ sequence:
225
+ class_label:
226
+ names:
227
+ 0: '100149'
228
+ 1: '100160'
229
+ 2: '100148'
230
+ 3: '100147'
231
+ 4: '100152'
232
+ 5: '100143'
233
+ 6: '100156'
234
+ 7: '100158'
235
+ 8: '100154'
236
+ 9: '100153'
237
+ 10: '100142'
238
+ 11: '100145'
239
+ 12: '100150'
240
+ 13: '100162'
241
+ 14: '100159'
242
+ 15: '100144'
243
+ 16: '100151'
244
+ 17: '100157'
245
+ 18: '100161'
246
+ 19: '100146'
247
+ 20: '100155'
248
+ splits:
249
+ - name: test
250
+ num_bytes: 60602026
251
+ num_examples: 5000
252
+ - name: train
253
+ num_bytes: 329071297
254
+ num_examples: 42490
255
+ - name: validation
256
+ num_bytes: 42766067
257
+ num_examples: 5000
258
+ download_size: 2770050147
259
+ dataset_size: 432439390
260
+ - config_name: bg
261
+ features:
262
+ - name: celex_id
263
+ dtype: string
264
+ - name: text
265
+ dtype: string
266
+ - name: labels
267
+ sequence:
268
+ class_label:
269
+ names:
270
+ 0: '100149'
271
+ 1: '100160'
272
+ 2: '100148'
273
+ 3: '100147'
274
+ 4: '100152'
275
+ 5: '100143'
276
+ 6: '100156'
277
+ 7: '100158'
278
+ 8: '100154'
279
+ 9: '100153'
280
+ 10: '100142'
281
+ 11: '100145'
282
+ 12: '100150'
283
+ 13: '100162'
284
+ 14: '100159'
285
+ 15: '100144'
286
+ 16: '100151'
287
+ 17: '100157'
288
+ 18: '100161'
289
+ 19: '100146'
290
+ 20: '100155'
291
+ splits:
292
+ - name: test
293
+ num_bytes: 109874769
294
+ num_examples: 5000
295
+ - name: train
296
+ num_bytes: 273160256
297
+ num_examples: 15986
298
+ - name: validation
299
+ num_bytes: 76892281
300
+ num_examples: 5000
301
+ download_size: 2770050147
302
+ dataset_size: 459927306
303
+ - config_name: cs
304
+ features:
305
+ - name: celex_id
306
+ dtype: string
307
+ - name: text
308
+ dtype: string
309
+ - name: labels
310
+ sequence:
311
+ class_label:
312
+ names:
313
+ 0: '100149'
314
+ 1: '100160'
315
+ 2: '100148'
316
+ 3: '100147'
317
+ 4: '100152'
318
+ 5: '100143'
319
+ 6: '100156'
320
+ 7: '100158'
321
+ 8: '100154'
322
+ 9: '100153'
323
+ 10: '100142'
324
+ 11: '100145'
325
+ 12: '100150'
326
+ 13: '100162'
327
+ 14: '100159'
328
+ 15: '100144'
329
+ 16: '100151'
330
+ 17: '100157'
331
+ 18: '100161'
332
+ 19: '100146'
333
+ 20: '100155'
334
+ splits:
335
+ - name: test
336
+ num_bytes: 60702814
337
+ num_examples: 5000
338
+ - name: train
339
+ num_bytes: 189826410
340
+ num_examples: 23187
341
+ - name: validation
342
+ num_bytes: 42764243
343
+ num_examples: 5000
344
+ download_size: 2770050147
345
+ dataset_size: 293293467
346
+ - config_name: hr
347
+ features:
348
+ - name: celex_id
349
+ dtype: string
350
+ - name: text
351
+ dtype: string
352
+ - name: labels
353
+ sequence:
354
+ class_label:
355
+ names:
356
+ 0: '100149'
357
+ 1: '100160'
358
+ 2: '100148'
359
+ 3: '100147'
360
+ 4: '100152'
361
+ 5: '100143'
362
+ 6: '100156'
363
+ 7: '100158'
364
+ 8: '100154'
365
+ 9: '100153'
366
+ 10: '100142'
367
+ 11: '100145'
368
+ 12: '100150'
369
+ 13: '100162'
370
+ 14: '100159'
371
+ 15: '100144'
372
+ 16: '100151'
373
+ 17: '100157'
374
+ 18: '100161'
375
+ 19: '100146'
376
+ 20: '100155'
377
+ splits:
378
+ - name: test
379
+ num_bytes: 56790830
380
+ num_examples: 5000
381
+ - name: train
382
+ num_bytes: 80808173
383
+ num_examples: 7944
384
+ - name: validation
385
+ num_bytes: 23881832
386
+ num_examples: 2500
387
+ download_size: 2770050147
388
+ dataset_size: 161480835
389
+ - config_name: pl
390
+ features:
391
+ - name: celex_id
392
+ dtype: string
393
+ - name: text
394
+ dtype: string
395
+ - name: labels
396
+ sequence:
397
+ class_label:
398
+ names:
399
+ 0: '100149'
400
+ 1: '100160'
401
+ 2: '100148'
402
+ 3: '100147'
403
+ 4: '100152'
404
+ 5: '100143'
405
+ 6: '100156'
406
+ 7: '100158'
407
+ 8: '100154'
408
+ 9: '100153'
409
+ 10: '100142'
410
+ 11: '100145'
411
+ 12: '100150'
412
+ 13: '100162'
413
+ 14: '100159'
414
+ 15: '100144'
415
+ 16: '100151'
416
+ 17: '100157'
417
+ 18: '100161'
418
+ 19: '100146'
419
+ 20: '100155'
420
+ splits:
421
+ - name: test
422
+ num_bytes: 64654979
423
+ num_examples: 5000
424
+ - name: train
425
+ num_bytes: 202211478
426
+ num_examples: 23197
427
+ - name: validation
428
+ num_bytes: 45545517
429
+ num_examples: 5000
430
+ download_size: 2770050147
431
+ dataset_size: 312411974
432
+ - config_name: sk
433
+ features:
434
+ - name: celex_id
435
+ dtype: string
436
+ - name: text
437
+ dtype: string
438
+ - name: labels
439
+ sequence:
440
+ class_label:
441
+ names:
442
+ 0: '100149'
443
+ 1: '100160'
444
+ 2: '100148'
445
+ 3: '100147'
446
+ 4: '100152'
447
+ 5: '100143'
448
+ 6: '100156'
449
+ 7: '100158'
450
+ 8: '100154'
451
+ 9: '100153'
452
+ 10: '100142'
453
+ 11: '100145'
454
+ 12: '100150'
455
+ 13: '100162'
456
+ 14: '100159'
457
+ 15: '100144'
458
+ 16: '100151'
459
+ 17: '100157'
460
+ 18: '100161'
461
+ 19: '100146'
462
+ 20: '100155'
463
+ splits:
464
+ - name: test
465
+ num_bytes: 60922686
466
+ num_examples: 5000
467
+ - name: train
468
+ num_bytes: 188126769
469
+ num_examples: 22971
470
+ - name: validation
471
+ num_bytes: 42786793
472
+ num_examples: 5000
473
+ download_size: 2770050147
474
+ dataset_size: 291836248
475
+ - config_name: sl
476
+ features:
477
+ - name: celex_id
478
+ dtype: string
479
+ - name: text
480
+ dtype: string
481
+ - name: labels
482
+ sequence:
483
+ class_label:
484
+ names:
485
+ 0: '100149'
486
+ 1: '100160'
487
+ 2: '100148'
488
+ 3: '100147'
489
+ 4: '100152'
490
+ 5: '100143'
491
+ 6: '100156'
492
+ 7: '100158'
493
+ 8: '100154'
494
+ 9: '100153'
495
+ 10: '100142'
496
+ 11: '100145'
497
+ 12: '100150'
498
+ 13: '100162'
499
+ 14: '100159'
500
+ 15: '100144'
501
+ 16: '100151'
502
+ 17: '100157'
503
+ 18: '100161'
504
+ 19: '100146'
505
+ 20: '100155'
506
+ splits:
507
+ - name: test
508
+ num_bytes: 54552441
509
+ num_examples: 5000
510
+ - name: train
511
+ num_bytes: 170800933
512
+ num_examples: 23184
513
+ - name: validation
514
+ num_bytes: 38286422
515
+ num_examples: 5000
516
+ download_size: 2770050147
517
+ dataset_size: 263639796
518
+ - config_name: es
519
+ features:
520
+ - name: celex_id
521
+ dtype: string
522
+ - name: text
523
+ dtype: string
524
+ - name: labels
525
+ sequence:
526
+ class_label:
527
+ names:
528
+ 0: '100149'
529
+ 1: '100160'
530
+ 2: '100148'
531
+ 3: '100147'
532
+ 4: '100152'
533
+ 5: '100143'
534
+ 6: '100156'
535
+ 7: '100158'
536
+ 8: '100154'
537
+ 9: '100153'
538
+ 10: '100142'
539
+ 11: '100145'
540
+ 12: '100150'
541
+ 13: '100162'
542
+ 14: '100159'
543
+ 15: '100144'
544
+ 16: '100151'
545
+ 17: '100157'
546
+ 18: '100161'
547
+ 19: '100146'
548
+ 20: '100155'
549
+ splits:
550
+ - name: test
551
+ num_bytes: 66885004
552
+ num_examples: 5000
553
+ - name: train
554
+ num_bytes: 433955383
555
+ num_examples: 52785
556
+ - name: validation
557
+ num_bytes: 47178821
558
+ num_examples: 5000
559
+ download_size: 2770050147
560
+ dataset_size: 548019208
561
+ - config_name: fr
562
+ features:
563
+ - name: celex_id
564
+ dtype: string
565
+ - name: text
566
+ dtype: string
567
+ - name: labels
568
+ sequence:
569
+ class_label:
570
+ names:
571
+ 0: '100149'
572
+ 1: '100160'
573
+ 2: '100148'
574
+ 3: '100147'
575
+ 4: '100152'
576
+ 5: '100143'
577
+ 6: '100156'
578
+ 7: '100158'
579
+ 8: '100154'
580
+ 9: '100153'
581
+ 10: '100142'
582
+ 11: '100145'
583
+ 12: '100150'
584
+ 13: '100162'
585
+ 14: '100159'
586
+ 15: '100144'
587
+ 16: '100151'
588
+ 17: '100157'
589
+ 18: '100161'
590
+ 19: '100146'
591
+ 20: '100155'
592
+ splits:
593
+ - name: test
594
+ num_bytes: 68520127
595
+ num_examples: 5000
596
+ - name: train
597
+ num_bytes: 442358905
598
+ num_examples: 55000
599
+ - name: validation
600
+ num_bytes: 48408938
601
+ num_examples: 5000
602
+ download_size: 2770050147
603
+ dataset_size: 559287970
604
+ - config_name: it
605
+ features:
606
+ - name: celex_id
607
+ dtype: string
608
+ - name: text
609
+ dtype: string
610
+ - name: labels
611
+ sequence:
612
+ class_label:
613
+ names:
614
+ 0: '100149'
615
+ 1: '100160'
616
+ 2: '100148'
617
+ 3: '100147'
618
+ 4: '100152'
619
+ 5: '100143'
620
+ 6: '100156'
621
+ 7: '100158'
622
+ 8: '100154'
623
+ 9: '100153'
624
+ 10: '100142'
625
+ 11: '100145'
626
+ 12: '100150'
627
+ 13: '100162'
628
+ 14: '100159'
629
+ 15: '100144'
630
+ 16: '100151'
631
+ 17: '100157'
632
+ 18: '100161'
633
+ 19: '100146'
634
+ 20: '100155'
635
+ splits:
636
+ - name: test
637
+ num_bytes: 64731770
638
+ num_examples: 5000
639
+ - name: train
640
+ num_bytes: 429495813
641
+ num_examples: 55000
642
+ - name: validation
643
+ num_bytes: 45886537
644
+ num_examples: 5000
645
+ download_size: 2770050147
646
+ dataset_size: 540114120
647
+ - config_name: pt
648
+ features:
649
+ - name: celex_id
650
+ dtype: string
651
+ - name: text
652
+ dtype: string
653
+ - name: labels
654
+ sequence:
655
+ class_label:
656
+ names:
657
+ 0: '100149'
658
+ 1: '100160'
659
+ 2: '100148'
660
+ 3: '100147'
661
+ 4: '100152'
662
+ 5: '100143'
663
+ 6: '100156'
664
+ 7: '100158'
665
+ 8: '100154'
666
+ 9: '100153'
667
+ 10: '100142'
668
+ 11: '100145'
669
+ 12: '100150'
670
+ 13: '100162'
671
+ 14: '100159'
672
+ 15: '100144'
673
+ 16: '100151'
674
+ 17: '100157'
675
+ 18: '100161'
676
+ 19: '100146'
677
+ 20: '100155'
678
+ splits:
679
+ - name: test
680
+ num_bytes: 64771247
681
+ num_examples: 5000
682
+ - name: train
683
+ num_bytes: 419281927
684
+ num_examples: 52370
685
+ - name: validation
686
+ num_bytes: 45897231
687
+ num_examples: 5000
688
+ download_size: 2770050147
689
+ dataset_size: 529950405
690
+ - config_name: ro
691
+ features:
692
+ - name: celex_id
693
+ dtype: string
694
+ - name: text
695
+ dtype: string
696
+ - name: labels
697
+ sequence:
698
+ class_label:
699
+ names:
700
+ 0: '100149'
701
+ 1: '100160'
702
+ 2: '100148'
703
+ 3: '100147'
704
+ 4: '100152'
705
+ 5: '100143'
706
+ 6: '100156'
707
+ 7: '100158'
708
+ 8: '100154'
709
+ 9: '100153'
710
+ 10: '100142'
711
+ 11: '100145'
712
+ 12: '100150'
713
+ 13: '100162'
714
+ 14: '100159'
715
+ 15: '100144'
716
+ 16: '100151'
717
+ 17: '100157'
718
+ 18: '100161'
719
+ 19: '100146'
720
+ 20: '100155'
721
+ splits:
722
+ - name: test
723
+ num_bytes: 67248472
724
+ num_examples: 5000
725
+ - name: train
726
+ num_bytes: 164966676
727
+ num_examples: 15921
728
+ - name: validation
729
+ num_bytes: 46968070
730
+ num_examples: 5000
731
+ download_size: 2770050147
732
+ dataset_size: 279183218
733
+ - config_name: et
734
+ features:
735
+ - name: celex_id
736
+ dtype: string
737
+ - name: text
738
+ dtype: string
739
+ - name: labels
740
+ sequence:
741
+ class_label:
742
+ names:
743
+ 0: '100149'
744
+ 1: '100160'
745
+ 2: '100148'
746
+ 3: '100147'
747
+ 4: '100152'
748
+ 5: '100143'
749
+ 6: '100156'
750
+ 7: '100158'
751
+ 8: '100154'
752
+ 9: '100153'
753
+ 10: '100142'
754
+ 11: '100145'
755
+ 12: '100150'
756
+ 13: '100162'
757
+ 14: '100159'
758
+ 15: '100144'
759
+ 16: '100151'
760
+ 17: '100157'
761
+ 18: '100161'
762
+ 19: '100146'
763
+ 20: '100155'
764
+ splits:
765
+ - name: test
766
+ num_bytes: 56535287
767
+ num_examples: 5000
768
+ - name: train
769
+ num_bytes: 173878703
770
+ num_examples: 23126
771
+ - name: validation
772
+ num_bytes: 39580866
773
+ num_examples: 5000
774
+ download_size: 2770050147
775
+ dataset_size: 269994856
776
+ - config_name: fi
777
+ features:
778
+ - name: celex_id
779
+ dtype: string
780
+ - name: text
781
+ dtype: string
782
+ - name: labels
783
+ sequence:
784
+ class_label:
785
+ names:
786
+ 0: '100149'
787
+ 1: '100160'
788
+ 2: '100148'
789
+ 3: '100147'
790
+ 4: '100152'
791
+ 5: '100143'
792
+ 6: '100156'
793
+ 7: '100158'
794
+ 8: '100154'
795
+ 9: '100153'
796
+ 10: '100142'
797
+ 11: '100145'
798
+ 12: '100150'
799
+ 13: '100162'
800
+ 14: '100159'
801
+ 15: '100144'
802
+ 16: '100151'
803
+ 17: '100157'
804
+ 18: '100161'
805
+ 19: '100146'
806
+ 20: '100155'
807
+ splits:
808
+ - name: test
809
+ num_bytes: 63280920
810
+ num_examples: 5000
811
+ - name: train
812
+ num_bytes: 336145949
813
+ num_examples: 42497
814
+ - name: validation
815
+ num_bytes: 44500040
816
+ num_examples: 5000
817
+ download_size: 2770050147
818
+ dataset_size: 443926909
819
+ - config_name: hu
820
+ features:
821
+ - name: celex_id
822
+ dtype: string
823
+ - name: text
824
+ dtype: string
825
+ - name: labels
826
+ sequence:
827
+ class_label:
828
+ names:
829
+ 0: '100149'
830
+ 1: '100160'
831
+ 2: '100148'
832
+ 3: '100147'
833
+ 4: '100152'
834
+ 5: '100143'
835
+ 6: '100156'
836
+ 7: '100158'
837
+ 8: '100154'
838
+ 9: '100153'
839
+ 10: '100142'
840
+ 11: '100145'
841
+ 12: '100150'
842
+ 13: '100162'
843
+ 14: '100159'
844
+ 15: '100144'
845
+ 16: '100151'
846
+ 17: '100157'
847
+ 18: '100161'
848
+ 19: '100146'
849
+ 20: '100155'
850
+ splits:
851
+ - name: test
852
+ num_bytes: 68990666
853
+ num_examples: 5000
854
+ - name: train
855
+ num_bytes: 208805862
856
+ num_examples: 22664
857
+ - name: validation
858
+ num_bytes: 48101023
859
+ num_examples: 5000
860
+ download_size: 2770050147
861
+ dataset_size: 325897551
862
+ - config_name: lt
863
+ features:
864
+ - name: celex_id
865
+ dtype: string
866
+ - name: text
867
+ dtype: string
868
+ - name: labels
869
+ sequence:
870
+ class_label:
871
+ names:
872
+ 0: '100149'
873
+ 1: '100160'
874
+ 2: '100148'
875
+ 3: '100147'
876
+ 4: '100152'
877
+ 5: '100143'
878
+ 6: '100156'
879
+ 7: '100158'
880
+ 8: '100154'
881
+ 9: '100153'
882
+ 10: '100142'
883
+ 11: '100145'
884
+ 12: '100150'
885
+ 13: '100162'
886
+ 14: '100159'
887
+ 15: '100144'
888
+ 16: '100151'
889
+ 17: '100157'
890
+ 18: '100161'
891
+ 19: '100146'
892
+ 20: '100155'
893
+ splits:
894
+ - name: test
895
+ num_bytes: 59484711
896
+ num_examples: 5000
897
+ - name: train
898
+ num_bytes: 185211691
899
+ num_examples: 23188
900
+ - name: validation
901
+ num_bytes: 41841024
902
+ num_examples: 5000
903
+ download_size: 2770050147
904
+ dataset_size: 286537426
905
+ - config_name: lv
906
+ features:
907
+ - name: celex_id
908
+ dtype: string
909
+ - name: text
910
+ dtype: string
911
+ - name: labels
912
+ sequence:
913
+ class_label:
914
+ names:
915
+ 0: '100149'
916
+ 1: '100160'
917
+ 2: '100148'
918
+ 3: '100147'
919
+ 4: '100152'
920
+ 5: '100143'
921
+ 6: '100156'
922
+ 7: '100158'
923
+ 8: '100154'
924
+ 9: '100153'
925
+ 10: '100142'
926
+ 11: '100145'
927
+ 12: '100150'
928
+ 13: '100162'
929
+ 14: '100159'
930
+ 15: '100144'
931
+ 16: '100151'
932
+ 17: '100157'
933
+ 18: '100161'
934
+ 19: '100146'
935
+ 20: '100155'
936
+ splits:
937
+ - name: test
938
+ num_bytes: 59814093
939
+ num_examples: 5000
940
+ - name: train
941
+ num_bytes: 186396252
942
+ num_examples: 23208
943
+ - name: validation
944
+ num_bytes: 42002727
945
+ num_examples: 5000
946
+ download_size: 2770050147
947
+ dataset_size: 288213072
948
+ - config_name: el
949
+ features:
950
+ - name: celex_id
951
+ dtype: string
952
+ - name: text
953
+ dtype: string
954
+ - name: labels
955
+ sequence:
956
+ class_label:
957
+ names:
958
+ 0: '100149'
959
+ 1: '100160'
960
+ 2: '100148'
961
+ 3: '100147'
962
+ 4: '100152'
963
+ 5: '100143'
964
+ 6: '100156'
965
+ 7: '100158'
966
+ 8: '100154'
967
+ 9: '100153'
968
+ 10: '100142'
969
+ 11: '100145'
970
+ 12: '100150'
971
+ 13: '100162'
972
+ 14: '100159'
973
+ 15: '100144'
974
+ 16: '100151'
975
+ 17: '100157'
976
+ 18: '100161'
977
+ 19: '100146'
978
+ 20: '100155'
979
+ splits:
980
+ - name: test
981
+ num_bytes: 117209312
982
+ num_examples: 5000
983
+ - name: train
984
+ num_bytes: 768224743
985
+ num_examples: 55000
986
+ - name: validation
987
+ num_bytes: 81923366
988
+ num_examples: 5000
989
+ download_size: 2770050147
990
+ dataset_size: 967357421
991
+ - config_name: mt
992
+ features:
993
+ - name: celex_id
994
+ dtype: string
995
+ - name: text
996
+ dtype: string
997
+ - name: labels
998
+ sequence:
999
+ class_label:
1000
+ names:
1001
+ 0: '100149'
1002
+ 1: '100160'
1003
+ 2: '100148'
1004
+ 3: '100147'
1005
+ 4: '100152'
1006
+ 5: '100143'
1007
+ 6: '100156'
1008
+ 7: '100158'
1009
+ 8: '100154'
1010
+ 9: '100153'
1011
+ 10: '100142'
1012
+ 11: '100145'
1013
+ 12: '100150'
1014
+ 13: '100162'
1015
+ 14: '100159'
1016
+ 15: '100144'
1017
+ 16: '100151'
1018
+ 17: '100157'
1019
+ 18: '100161'
1020
+ 19: '100146'
1021
+ 20: '100155'
1022
+ splits:
1023
+ - name: test
1024
+ num_bytes: 65831230
1025
+ num_examples: 5000
1026
+ - name: train
1027
+ num_bytes: 179866781
1028
+ num_examples: 17521
1029
+ - name: validation
1030
+ num_bytes: 46737914
1031
+ num_examples: 5000
1032
+ download_size: 2770050147
1033
+ dataset_size: 292435925
1034
+ - config_name: all_languages
1035
+ features:
1036
+ - name: celex_id
1037
+ dtype: string
1038
+ - name: text
1039
+ dtype:
1040
+ translation:
1041
+ languages:
1042
+ - en
1043
+ - da
1044
+ - de
1045
+ - nl
1046
+ - sv
1047
+ - bg
1048
+ - cs
1049
+ - hr
1050
+ - pl
1051
+ - sk
1052
+ - sl
1053
+ - es
1054
+ - fr
1055
+ - it
1056
+ - pt
1057
+ - ro
1058
+ - et
1059
+ - fi
1060
+ - hu
1061
+ - lt
1062
+ - lv
1063
+ - el
1064
+ - mt
1065
+ - name: labels
1066
+ sequence:
1067
+ class_label:
1068
+ names:
1069
+ 0: '100149'
1070
+ 1: '100160'
1071
+ 2: '100148'
1072
+ 3: '100147'
1073
+ 4: '100152'
1074
+ 5: '100143'
1075
+ 6: '100156'
1076
+ 7: '100158'
1077
+ 8: '100154'
1078
+ 9: '100153'
1079
+ 10: '100142'
1080
+ 11: '100145'
1081
+ 12: '100150'
1082
+ 13: '100162'
1083
+ 14: '100159'
1084
+ 15: '100144'
1085
+ 16: '100151'
1086
+ 17: '100157'
1087
+ 18: '100161'
1088
+ 19: '100146'
1089
+ 20: '100155'
1090
+ splits:
1091
+ - name: test
1092
+ num_bytes: 1536038431
1093
+ num_examples: 5000
1094
+ - name: train
1095
+ num_bytes: 6971500859
1096
+ num_examples: 55000
1097
+ - name: validation
1098
+ num_bytes: 1062290624
1099
+ num_examples: 5000
1100
+ download_size: 2770050147
1101
+ dataset_size: 9569829914
1102
  ---
1103
 
1104
  # Dataset Card for "MultiEURLEX"
 
1382
 
1383
  ### Contributions
1384
 
1385
+ Thanks to [@iliaschalkidis](https://github.com/iliaschalkidis) for adding this dataset.