albertvillanova HF staff commited on
Commit
3a262e5
1 Parent(s): cd8d496

Host data file (#7)

Browse files

- Host data file (f5a458d814e4a58584ad994e036ddd2d29ec19a5)
- Update loading script (d994bd6d9b9cee51ccb8c595ed1b36e3d9c836eb)
- Update dataset card (8862d31f49b03c057dcf6e36f256d6789e798518)
- Delete legacy metadata JSON file (910d52545461e7651384222ef12a62fbf55563d1)

README.md CHANGED
@@ -1129,9 +1129,9 @@ dataset_info:
1129
 
1130
  ## Dataset Description
1131
 
1132
- - **Homepage:** https://github.com/nlpaueb/MultiEURLEX/
1133
  - **Repository:** https://github.com/nlpaueb/MultiEURLEX/
1134
  - **Paper:** https://arxiv.org/abs/2109.00904
 
1135
  - **Leaderboard:** N/A
1136
  - **Point of Contact:** [Ilias Chalkidis](mailto:ilias.chalkidis@di.ku.dk)
1137
 
1129
 
1130
  ## Dataset Description
1131
 
 
1132
  - **Repository:** https://github.com/nlpaueb/MultiEURLEX/
1133
  - **Paper:** https://arxiv.org/abs/2109.00904
1134
+ - **Data:** https://doi.org/10.5281/zenodo.5363165
1135
  - **Leaderboard:** N/A
1136
  - **Point of Contact:** [Ilias Chalkidis](mailto:ilias.chalkidis@di.ku.dk)
1137
 
data/multi_eurlex.tar.gz ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83
3
+ size 2770050147
dataset_infos.json DELETED
@@ -1 +0,0 @@
1
- {"en": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "en", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 389250183, "num_examples": 55000, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 58966963, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 41516165, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 489733311, "size_in_bytes": 3259783458}, "da": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "da", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 395774777, "num_examples": 55000, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 60343696, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 42366390, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 498484863, "size_in_bytes": 3268535010}, "de": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "de", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 425489905, "num_examples": 55000, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 65739074, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 46079574, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 537308553, "size_in_bytes": 3307358700}, "nl": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "nl", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 430232783, "num_examples": 55000, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 64728034, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 45452550, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 540413367, "size_in_bytes": 3310463514}, "sv": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "sv", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 329071297, "num_examples": 42490, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 60602026, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 42766067, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 432439390, "size_in_bytes": 3202489537}, "bg": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "bg", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 273160256, "num_examples": 15986, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 109874769, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 76892281, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 459927306, "size_in_bytes": 3229977453}, "cs": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "cs", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 189826410, "num_examples": 23187, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 60702814, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 42764243, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 293293467, "size_in_bytes": 3063343614}, "hr": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "hr", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 80808173, "num_examples": 7944, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 56790830, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 23881832, "num_examples": 2500, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 161480835, "size_in_bytes": 2931530982}, "pl": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "pl", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 202211478, "num_examples": 23197, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 64654979, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 45545517, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 312411974, "size_in_bytes": 3082462121}, "sk": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "sk", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 188126769, "num_examples": 22971, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 60922686, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 42786793, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 291836248, "size_in_bytes": 3061886395}, "sl": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "sl", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 170800933, "num_examples": 23184, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 54552441, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 38286422, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 263639796, "size_in_bytes": 3033689943}, "es": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "es", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 433955383, "num_examples": 52785, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 66885004, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 47178821, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 548019208, "size_in_bytes": 3318069355}, "fr": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "fr", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 442358905, "num_examples": 55000, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 68520127, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 48408938, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 559287970, "size_in_bytes": 3329338117}, "it": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "it", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 429495813, "num_examples": 55000, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 64731770, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 45886537, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 540114120, "size_in_bytes": 3310164267}, "pt": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "pt", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 419281927, "num_examples": 52370, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 64771247, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 45897231, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 529950405, "size_in_bytes": 3300000552}, "ro": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "ro", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 164966676, "num_examples": 15921, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 67248472, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 46968070, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 279183218, "size_in_bytes": 3049233365}, "et": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "et", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 173878703, "num_examples": 23126, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 56535287, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 39580866, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 269994856, "size_in_bytes": 3040045003}, "fi": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "fi", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 336145949, "num_examples": 42497, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 63280920, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 44500040, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 443926909, "size_in_bytes": 3213977056}, "hu": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "hu", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 208805862, "num_examples": 22664, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 68990666, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 48101023, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 325897551, "size_in_bytes": 3095947698}, "lt": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "lt", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 185211691, "num_examples": 23188, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 59484711, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 41841024, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 286537426, "size_in_bytes": 3056587573}, "lv": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "lv", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 186396252, "num_examples": 23208, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 59814093, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 42002727, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 288213072, "size_in_bytes": 3058263219}, "el": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "el", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 768224743, "num_examples": 55000, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 117209312, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 81923366, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 967357421, "size_in_bytes": 3737407568}, "mt": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "mt", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 179866781, "num_examples": 17521, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 65831230, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 46737914, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 292435925, "size_in_bytes": 3062486072}, "all_languages": {"description": "MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).\nEach EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.\nAs with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);\nthis is multi-label classification task (given the text, predict multiple labels).\n", "citation": "@InProceedings{chalkidis-etal-2021-multieurlex,\n author = {Chalkidis, Ilias\n and Fergadiotis, Manos\n and 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 publisher = {Association for Computational Linguistics},\n location = {Punta Cana, Dominican Republic},\n}", "homepage": "https://github.io/iliaschalkidis", "license": "", "features": {"celex_id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"languages": ["en", "da", "de", "nl", "sv", "bg", "cs", "hr", "pl", "sk", "sl", "es", "fr", "it", "pt", "ro", "et", "fi", "hu", "lt", "lv", "el", "mt"], "id": null, "_type": "Translation"}, "labels": {"feature": {"num_classes": 21, "names": ["100149", "100160", "100148", "100147", "100152", "100143", "100156", "100158", "100154", "100153", "100142", "100145", "100150", "100162", "100159", "100144", "100151", "100157", "100161", "100146", "100155"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "multi_eurlex", "config_name": "all_languages", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 6971500859, "num_examples": 55000, "dataset_name": "multi_eurlex"}, "test": {"name": "test", "num_bytes": 1536038431, "num_examples": 5000, "dataset_name": "multi_eurlex"}, "validation": {"name": "validation", "num_bytes": 1062290624, "num_examples": 5000, "dataset_name": "multi_eurlex"}}, "download_checksums": {"https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz": {"num_bytes": 2770050147, "checksum": "3a2195bc01c7aea0e302bc7af94f2f55f0c15cdeabfe4e086c083196069a2e83"}}, "download_size": 2770050147, "post_processing_size": null, "dataset_size": 9569829914, "size_in_bytes": 12339880061}}
 
multi_eurlex.py CHANGED
@@ -42,7 +42,8 @@ _CITATION = """\
42
  location = {Punta Cana, Dominican Republic},
43
  }"""
44
 
45
- DATA_URL = "https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz"
 
46
 
47
  _LANGUAGES = [
48
  "en",
42
  location = {Punta Cana, Dominican Republic},
43
  }"""
44
 
45
+ # Source data: "https://zenodo.org/record/5363165/files/multi_eurlex.tar.gz"
46
+ DATA_URL = "data/multi_eurlex.tar.gz"
47
 
48
  _LANGUAGES = [
49
  "en",