Datasets:
License:
| # coding=utf-8 | |
| # Copyright 2022 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. | |
| """ | |
| Parallel corpus of full-text articles in Portuguese, English and Spanish from SciELO. | |
| """ | |
| from typing import IO, Any, Generator, List, Optional, Tuple | |
| import datasets | |
| from .bigbiohub import text2text_features | |
| from .bigbiohub import BigBioConfig | |
| from .bigbiohub import Tasks | |
| _LANGUAGES = ['English', 'Spanish', 'Portuguese'] | |
| _PUBMED = False | |
| _LOCAL = False | |
| _CITATION = """\ | |
| @inproceedings{soares2018large, | |
| title = {A Large Parallel Corpus of Full-Text Scientific Articles}, | |
| author = {Soares, Felipe and Moreira, Viviane and Becker, Karin}, | |
| year = 2018, | |
| booktitle = { | |
| Proceedings of the Eleventh International Conference on Language Resources | |
| and Evaluation (LREC-2018) | |
| } | |
| } | |
| """ | |
| _DATASETNAME = "scielo" | |
| _DISPLAYNAME = "SciELO" | |
| _DESCRIPTION = """\ | |
| A parallel corpus of full-text scientific articles collected from Scielo \ | |
| database in the following languages: English, Portuguese and Spanish. The corpus \ | |
| is sentence aligned for all language pairs, as well as trilingual aligned for a \ | |
| small subset of sentences. Alignment was carried out using the Hunalign \ | |
| algorithm. | |
| """ | |
| _HOMEPAGE = "https://sites.google.com/view/felipe-soares/datasets#h.p_92uSCyAjWSRB" | |
| _LICENSE = 'Creative Commons Attribution 4.0 International' | |
| _URLS = { | |
| "en_es": "https://ndownloader.figstatic.com/files/14019287", | |
| "en_pt": "https://ndownloader.figstatic.com/files/14019308", | |
| "en_pt_es": "https://ndownloader.figstatic.com/files/14019293", | |
| } | |
| _SUPPORTED_TASKS = [Tasks.TRANSLATION] | |
| _SOURCE_VERSION = "1.0.0" | |
| _BIGBIO_VERSION = "1.0.0" | |
| class ScieloDataset(datasets.GeneratorBasedBuilder): | |
| """Parallel corpus of full-text articles in Portuguese, English and Spanish from SciELO.""" | |
| SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) | |
| BIGBIO_VERSION = datasets.Version(_BIGBIO_VERSION) | |
| # NOTE: bigbio_t2t schema doesn't allow only for more than two texts in text-to-text schema. | |
| # en-pt-es translation is not implemented using the bigbio schema | |
| BUILDER_CONFIGS = [ | |
| BigBioConfig( | |
| name="scielo_en_es_source", | |
| version=SOURCE_VERSION, | |
| description="English-Spanish", | |
| schema="source", | |
| subset_id="scielo_en_es", | |
| ), | |
| BigBioConfig( | |
| name="scielo_en_pt_source", | |
| version=SOURCE_VERSION, | |
| description="English-Portuguese", | |
| schema="source", | |
| subset_id="scielo_en_pt", | |
| ), | |
| BigBioConfig( | |
| name="scielo_en_pt_es_source", | |
| version=SOURCE_VERSION, | |
| description="English-Portuguese-Spanish", | |
| schema="source", | |
| subset_id="scielo_en_pt_es", | |
| ), | |
| BigBioConfig( | |
| name="scielo_en_es_bigbio_t2t", | |
| version=BIGBIO_VERSION, | |
| description="scielo BigBio schema English-Spanish", | |
| schema="bigbio_t2t", | |
| subset_id="scielo_en_es", | |
| ), | |
| BigBioConfig( | |
| name="scielo_en_pt_bigbio_t2t", | |
| version=BIGBIO_VERSION, | |
| description="scielo BigBio schema English-Portuguese", | |
| schema="bigbio_t2t", | |
| subset_id="scielo_en_pt", | |
| ), | |
| ] | |
| DEFAULT_CONFIG_NAME = "scielo_source_en_es" | |
| def _info(self) -> datasets.DatasetInfo: | |
| if self.config.schema == "source": | |
| lang_list: List[str] = self.config.subset_id.split("_")[1:] | |
| features = datasets.Features( | |
| {"translation": datasets.features.Translation(languages=lang_list)} | |
| ) | |
| elif self.config.schema == "bigbio_t2t": | |
| features = text2text_features | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| homepage=_HOMEPAGE, | |
| license=str(_LICENSE), | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager) -> List[datasets.SplitGenerator]: | |
| """Returns SplitGenerators.""" | |
| lang_list: List[str] = self.config.subset_id.split("_")[1:] | |
| languages = "_".join(lang_list) | |
| archive = dl_manager.download(_URLS[languages]) | |
| fname = languages | |
| if languages == "en_pt_es": | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "source_file": f"{fname}.en", | |
| "target_file": f"{fname}.pt", | |
| "target_file_2": f"{fname}.es", | |
| "files": dl_manager.iter_archive(archive), | |
| "languages": languages, | |
| "split": "train", | |
| }, | |
| ), | |
| ] | |
| else: | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "source_file": f"{fname}.{lang_list[0]}", | |
| "target_file": f"{fname}.{lang_list[1]}", | |
| "files": dl_manager.iter_archive(archive), | |
| "languages": languages, | |
| "split": "train", | |
| }, | |
| ), | |
| ] | |
| def _generate_examples( | |
| self, | |
| languages: str, | |
| split: str, | |
| source_file: str, | |
| target_file: str, | |
| files: Generator[Tuple[str, IO[bytes]], Any, None], | |
| target_file_2: Optional[str] = None, | |
| ) -> Tuple[int, dict]: | |
| if self.config.schema == "source": | |
| for path, f in files: | |
| if path == source_file: | |
| source_sentences = f.read().decode("utf-8").split("\n") | |
| elif path == target_file: | |
| target_sentences = f.read().decode("utf-8").split("\n") | |
| elif languages == "en_pt_es" and path == target_file_2: | |
| target_sentences_2 = f.read().decode("utf-8").split("\n") | |
| if languages == "en_pt_es": | |
| source, target, target_2 = tuple(languages.split("_")) | |
| for idx, (l1, l2, l3) in enumerate( | |
| zip(source_sentences, target_sentences, target_sentences_2) | |
| ): | |
| result = {"translation": {source: l1, target: l2, target_2: l3}} | |
| yield idx, result | |
| else: | |
| source, target = tuple(languages.split("_")) | |
| for idx, (l1, l2) in enumerate(zip(source_sentences, target_sentences)): | |
| result = {"translation": {source: l1, target: l2}} | |
| yield idx, result | |
| elif self.config.schema == "bigbio_t2t": | |
| for path, f in files: | |
| if path == source_file: | |
| source_sentences = f.read().decode("utf-8").split("\n") | |
| elif path == target_file: | |
| target_sentences = f.read().decode("utf-8").split("\n") | |
| uid = 0 | |
| source, target = tuple(languages.split("_")) | |
| for idx, (l1, l2) in enumerate(zip(source_sentences, target_sentences)): | |
| uid += 1 | |
| yield idx, { | |
| "id": str(uid), | |
| "document_id": str(idx), | |
| "text_1": l1, | |
| "text_2": l2, | |
| "text_1_name": source, | |
| "text_2_name": target, | |
| } | |