multi_eurlex / dataset_infos.json
system's picture
system HF staff
Update files from the datasets library (from 1.12.0)
bf4c71c
raw
history blame
57.7 kB
{"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}}