Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
multi-label-classification
Languages:
English
Size:
10K - 100K
License:
| # coding=utf-8 | |
| # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| """EURLEX57K contains 57k legislative documents in English from EUR-Lex portal, annotated with EUROVOC concepts.""" | |
| import json | |
| import os | |
| import datasets | |
| _CITATION = """\ | |
| @inproceedings{chalkidis-etal-2019-large, | |
| title = "Large-Scale Multi-Label Text Classification on {EU} Legislation", | |
| author = "Chalkidis, Ilias and Fergadiotis, Emmanouil and Malakasiotis, Prodromos and Androutsopoulos, Ion", | |
| booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics", | |
| year = "2019", | |
| address = "Florence, Italy", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://www.aclweb.org/anthology/P19-1636", | |
| doi = "10.18653/v1/P19-1636", | |
| pages = "6314--6322" | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| EURLEX57K contains 57k legislative documents in English from EUR-Lex portal, annotated with EUROVOC concepts. | |
| """ | |
| _HOMEPAGE = "http://nlp.cs.aueb.gr/software_and_datasets/EURLEX57K/" | |
| _LICENSE = "CC BY-SA (Creative Commons / Attribution-ShareAlike)" | |
| _URLs = { | |
| "eurlex57k": "http://archive.org/download/EURLEX57K/dataset.zip", | |
| } | |
| class EURLEX(datasets.GeneratorBasedBuilder): | |
| """EURLEX57K contains 57k legislative documents in English from EUR-Lex portal, annotated with EUROVOC concepts.""" | |
| VERSION = datasets.Version("1.1.0") | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name="eurlex57k", version=VERSION, description="EURLEX57K: Legal Multi-label Text Classification" | |
| ), | |
| ] | |
| DEFAULT_CONFIG_NAME = "eurlex57k" | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "celex_id": datasets.Value("string"), | |
| "title": datasets.Value("string"), | |
| "text": datasets.Value("string"), | |
| "eurovoc_concepts": datasets.features.Sequence(datasets.Value("string")), | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| # This is the description that will appear on the datasets page. | |
| description=_DESCRIPTION, | |
| # This defines the different columns of the dataset and their types | |
| features=features, # Here we define them above because they are different between the two configurations | |
| # If there's a common (input, target) tuple from the features, | |
| # specify them here. They'll be used if as_supervised=True in | |
| # builder.as_dataset. | |
| supervised_keys=None, | |
| # Homepage of the dataset for documentation | |
| homepage=_HOMEPAGE, | |
| # License for the dataset if available | |
| license=_LICENSE, | |
| # Citation for the dataset | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| my_urls = _URLs[self.config.name] | |
| data_dir = dl_manager.download_and_extract(my_urls) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir, "train.jsonl"), | |
| "split": "train", | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={"filepath": os.path.join(data_dir, "test.jsonl"), "split": "test"}, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir, "dev.jsonl"), | |
| "split": "dev", | |
| }, | |
| ), | |
| ] | |
| def _generate_examples( | |
| self, filepath, split # method parameters are unpacked from `gen_kwargs` as given in `_split_generators` | |
| ): | |
| """Yields examples as (key, example) tuples.""" | |
| with open(filepath, encoding="utf-8") as f: | |
| for id_, row in enumerate(f): | |
| data = json.loads(row) | |
| yield id_, { | |
| "celex_id": data["celex_id"], | |
| "title": data["title"], | |
| "text": data["header"] + "\n" + data["recitals"], | |
| "eurovoc_concepts": data["eurovoc_concepts"], | |
| } | |