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| """ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts""" |
|
|
|
|
| import csv |
| import os |
|
|
| import datasets |
|
|
|
|
| _CITATION = """\ |
| @inproceedings{soares-etal-2020-parapat, |
| title = "{P}ara{P}at: The Multi-Million Sentences Parallel Corpus of Patents Abstracts", |
| author = "Soares, Felipe and |
| Stevenson, Mark and |
| Bartolome, Diego and |
| Zaretskaya, Anna", |
| booktitle = "Proceedings of The 12th Language Resources and Evaluation Conference", |
| month = may, |
| year = "2020", |
| address = "Marseille, France", |
| publisher = "European Language Resources Association", |
| url = "https://www.aclweb.org/anthology/2020.lrec-1.465", |
| pages = "3769--3774", |
| language = "English", |
| ISBN = "979-10-95546-34-4", |
| } |
| """ |
|
|
| _DESCRIPTION = """\ |
| ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts |
| |
| This dataset contains the developed parallel corpus from the open access Google |
| Patents dataset in 74 language pairs, comprising more than 68 million sentences |
| and 800 million tokens. Sentences were automatically aligned using the Hunalign algorithm |
| for the largest 22 language pairs, while the others were abstract (i.e. paragraph) aligned. |
| |
| """ |
|
|
| _HOMEPAGE = ( |
| "https://figshare.com/articles/ParaPat_The_Multi-Million_Sentences_Parallel_Corpus_of_Patents_Abstracts/12627632" |
| ) |
|
|
| _LICENSE = "CC BY 4.0" |
|
|
| type1_datasets_file = ["el-en", "cs-en", "en-hu", "en-ro", "en-sk", "en-uk", "es-fr", "fr-ru"] |
| type2_datasets_file = [ |
| "de-fr", |
| "en-ja", |
| "en-es", |
| "en-fr", |
| "de-en", |
| "en-ko", |
| "fr-ja", |
| "en-zh", |
| "en-ru", |
| "fr-ko", |
| "ru-uk", |
| "en-pt", |
| ] |
|
|
| type1_datasets_features = [ |
| "el-en", |
| "cs-en", |
| "en-hu", |
| "en-ro", |
| "en-sk", |
| "en-uk", |
| "es-fr", |
| "fr-ru", |
| "fr-ko", |
| "ru-uk", |
| "en-pt", |
| ] |
| type2_datasets_features = ["de-fr", "en-ja", "en-es", "en-fr", "de-en", "en-ko", "fr-ja", "en-zh", "en-ru"] |
|
|
|
|
| class ParaPatConfig(datasets.BuilderConfig): |
| """BuilderConfig for ParaPat.""" |
|
|
| def __init__(self, language_pair=(None, None), url=None, **kwargs): |
| """BuilderConfig for ParaPat.""" |
| name = "%s-%s" % (language_pair[0], language_pair[1]) |
|
|
| description = ("Translation dataset from %s to %s") % (language_pair[0], language_pair[1]) |
|
|
| source, target = language_pair |
| super(ParaPatConfig, self).__init__( |
| name=name, |
| description=description, |
| version=datasets.Version("1.1.0", ""), |
| **kwargs, |
| ) |
|
|
| self.language_pair = language_pair |
| self.url = url |
|
|
|
|
| class ParaPat(datasets.GeneratorBasedBuilder): |
| """ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts""" |
|
|
| VERSION = datasets.Version("1.1.0") |
|
|
| BUILDER_CONFIGS = [ |
| ParaPatConfig( |
| language_pair=("el", "en"), |
| url="https://ndownloader.figshare.com/files/23748818", |
| ), |
| ParaPatConfig( |
| language_pair=("cs", "en"), |
| url="https://ndownloader.figshare.com/files/23748821", |
| ), |
| ParaPatConfig( |
| language_pair=("en", "hu"), |
| url="https://ndownloader.figshare.com/files/23748827", |
| ), |
| ParaPatConfig( |
| language_pair=("en", "ro"), |
| url="https://ndownloader.figshare.com/files/23748842", |
| ), |
| ParaPatConfig( |
| language_pair=("en", "sk"), |
| url="https://ndownloader.figshare.com/files/23748848", |
| ), |
| ParaPatConfig( |
| language_pair=("en", "uk"), |
| url="https://ndownloader.figshare.com/files/23748851", |
| ), |
| ParaPatConfig( |
| language_pair=("es", "fr"), |
| url="https://ndownloader.figshare.com/files/23748857", |
| ), |
| ParaPatConfig( |
| language_pair=("fr", "ru"), |
| url="https://ndownloader.figshare.com/files/23748863", |
| ), |
| ParaPatConfig( |
| language_pair=("de", "fr"), |
| url="https://ndownloader.figshare.com/files/23748872", |
| ), |
| ParaPatConfig( |
| language_pair=("en", "ja"), |
| url="https://ndownloader.figshare.com/files/23748626", |
| ), |
| ParaPatConfig( |
| language_pair=("en", "es"), |
| url="https://ndownloader.figshare.com/files/23748896", |
| ), |
| ParaPatConfig( |
| language_pair=("en", "fr"), |
| url="https://ndownloader.figshare.com/files/23748944", |
| ), |
| ParaPatConfig( |
| language_pair=("de", "en"), |
| url="https://ndownloader.figshare.com/files/23855657", |
| ), |
| ParaPatConfig( |
| language_pair=("en", "ko"), |
| url="https://ndownloader.figshare.com/files/23748689", |
| ), |
| ParaPatConfig( |
| language_pair=("fr", "ja"), |
| url="https://ndownloader.figshare.com/files/23748866", |
| ), |
| ParaPatConfig( |
| language_pair=("en", "zh"), |
| url="https://ndownloader.figshare.com/files/23748779", |
| ), |
| ParaPatConfig( |
| language_pair=("en", "ru"), |
| url="https://ndownloader.figshare.com/files/23748704", |
| ), |
| ParaPatConfig( |
| language_pair=("fr", "ko"), |
| url="https://ndownloader.figshare.com/files/23855408", |
| ), |
| ParaPatConfig( |
| language_pair=("ru", "uk"), |
| url="https://ndownloader.figshare.com/files/23855465", |
| ), |
| ParaPatConfig( |
| language_pair=("en", "pt"), |
| url="https://ndownloader.figshare.com/files/23855441", |
| ), |
| ] |
| BUILDER_CONFIG_CLASS = ParaPatConfig |
|
|
| def _info(self): |
| source, target = self.config.language_pair |
|
|
| if self.config.name in type1_datasets_features: |
| features = datasets.Features( |
| { |
| "index": datasets.Value("int32"), |
| "family_id": datasets.Value("int32"), |
| "translation": datasets.features.Translation(languages=(source, target)), |
| } |
| ) |
| elif self.config.name in type2_datasets_features: |
| features = datasets.Features( |
| { |
| "translation": datasets.features.Translation(languages=(source, target)), |
| } |
| ) |
| return datasets.DatasetInfo( |
| |
| description=_DESCRIPTION, |
| |
| features=features, |
| |
| |
| |
| supervised_keys=(source, target), |
| |
| homepage=_HOMEPAGE, |
| |
| license=_LICENSE, |
| |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| """Returns SplitGenerators.""" |
| source, target = self.config.language_pair |
|
|
| data_dir = dl_manager.download_and_extract(self.config.url) |
|
|
| if self.config.name in type1_datasets_file: |
| _TRAIN_FILE_NAME = data_dir |
| else: |
| name = self.config.name.replace("-", "_") |
| _TRAIN_FILE_NAME = os.path.join(data_dir, f"{name}.tsv") |
|
|
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| |
| gen_kwargs={ |
| "filepath": _TRAIN_FILE_NAME, |
| "split": "train", |
| }, |
| ), |
| ] |
|
|
| def _generate_examples(self, filepath, split): |
| """Yields examples.""" |
| source, target = self.config.language_pair |
| with open(filepath, encoding="utf-8") as f: |
| if self.config.name in type1_datasets_features: |
| data = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE) |
| for id_, row in enumerate(data): |
| if row["src_lang"] + "-" + row["tgt_lang"] != self.config.name: |
| continue |
| yield id_, { |
| "index": row["index"], |
| "family_id": row["family_id"], |
| "translation": {source: row["src_abs"], target: row["tgt_abs"]}, |
| } |
| else: |
| data = csv.reader(f, delimiter="\t", quoting=csv.QUOTE_NONE) |
| for id_, row in enumerate(data): |
| yield id_, { |
| "translation": {source: row[0], target: row[1]}, |
| } |
|
|