Datasets:
Tasks:
Summarization
Languages:
French
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
ArXiv:
Tags:
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. | |
| """OrangeSum dataset""" | |
| import datasets | |
| _CITATION = """\ | |
| @article{eddine2020barthez, | |
| title={BARThez: a Skilled Pretrained French Sequence-to-Sequence Model}, | |
| author={Eddine, Moussa Kamal and Tixier, Antoine J-P and Vazirgiannis, Michalis}, | |
| journal={arXiv preprint arXiv:2010.12321}, | |
| year={2020} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| The OrangeSum dataset was inspired by the XSum dataset. It was created by scraping the "Orange Actu" website: https://actu.orange.fr/. Orange S.A. is a large French multinational telecommunications corporation, with 266M customers worldwide. Scraped pages cover almost a decade from Feb 2011 to Sep 2020. They belong to five main categories: France, world, politics, automotive, and society. The society category is itself divided into 8 subcategories: health, environment, people, culture, media, high-tech, unsual ("insolite" in French), and miscellaneous. | |
| Each article featured a single-sentence title as well as a very brief abstract, both professionally written by the author of the article. These two fields were extracted from each page, thus creating two summarization tasks: OrangeSum Title and OrangeSum Abstract. | |
| """ | |
| _URL_DATA = { | |
| "abstract": "https://raw.githubusercontent.com/Tixierae/OrangeSum/main/data/docs/splits/abstract.tgz", | |
| "title": "https://raw.githubusercontent.com/Tixierae/OrangeSum/main/data/docs/splits/title.tgz", | |
| } | |
| _DOCUMENT = "text" | |
| _SUMMARY = "summary" | |
| class OrangeSum(datasets.GeneratorBasedBuilder): | |
| """OrangeSum: a french abstractive summarization dataset""" | |
| VERSION = datasets.Version("1.1.0") | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig(name="abstract", description="Abstracts used as summaries", version=VERSION), | |
| datasets.BuilderConfig(name="title", description="Titles used as summaries", version=VERSION), | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| _DOCUMENT: datasets.Value("string"), | |
| _SUMMARY: datasets.Value("string"), | |
| } | |
| ), | |
| supervised_keys=(_DOCUMENT, _SUMMARY), | |
| homepage="https://github.com/Tixierae/OrangeSum/", | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| archive = dl_manager.download(_URL_DATA[self.config.name]) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "source_files": dl_manager.iter_archive(archive), | |
| "target_files": dl_manager.iter_archive(archive), | |
| "split": "train", | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "source_files": dl_manager.iter_archive(archive), | |
| "target_files": dl_manager.iter_archive(archive), | |
| "split": "test", | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "source_files": dl_manager.iter_archive(archive), | |
| "target_files": dl_manager.iter_archive(archive), | |
| "split": "valid", | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, source_files, target_files, split): | |
| """Yields examples.""" | |
| expected_source_path = f"{self.config.name}/{split}.source" | |
| expected_target_path = f"{self.config.name}/{split}.target" | |
| for source_path, f_source in source_files: | |
| if source_path == expected_source_path: | |
| for target_path, f_target in target_files: | |
| if target_path == expected_target_path: | |
| for idx, (document, summary) in enumerate(zip(f_source, f_target)): | |
| yield idx, {_DOCUMENT: document.decode("utf-8"), _SUMMARY: summary.decode("utf-8")} | |
| break | |
| break | |