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"""The Yoruba Text C3 dataset.""" |
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from __future__ import absolute_import, division, print_function |
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import datasets |
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_DESCRIPTION = """\ |
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Yoruba Text C3 is the largest Yoruba texts collected and used to train FastText embeddings in the |
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YorubaTwi Embedding paper: https://www.aclweb.org/anthology/2020.lrec-1.335/ |
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""" |
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_CITATION = """\ |
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@inproceedings{alabi-etal-2020-massive, |
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title = "Massive vs. Curated Embeddings for Low-Resourced Languages: the Case of Yoruba and {T}wi", |
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author = "Alabi, Jesujoba and |
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Amponsah-Kaakyire, Kwabena and |
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Adelani, David and |
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Espa{\\~n}a-Bonet, Cristina", |
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booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference", |
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month = may, |
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year = "2020", |
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address = "Marseille, France", |
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publisher = "European Language Resources Association", |
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url = "https://www.aclweb.org/anthology/2020.lrec-1.335", |
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pages = "2754--2762", |
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language = "English", |
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ISBN = "979-10-95546-34-4", |
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} |
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""" |
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URL = "https://drive.google.com/uc?export=download&id=1Nug7-Sri50mkJL4GrWw6C2ZIbfeU-6Am" |
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class YorubaTextC3Config(datasets.BuilderConfig): |
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"""BuilderConfig for YorubaTextC3.""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig for BookCorpus. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(YorubaTextC3Config, self).__init__(**kwargs) |
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class YorubaTextC3(datasets.GeneratorBasedBuilder): |
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"""Yoruba Text C3 dataset.""" |
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BUILDER_CONFIGS = [ |
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YorubaTextC3Config( |
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name="yoruba_text_c3", |
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version=datasets.Version("1.0.0"), |
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description="Yoruba Texts C3 ", |
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) |
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] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"text": datasets.Value("string"), |
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} |
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), |
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supervised_keys=None, |
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homepage="https://www.aclweb.org/anthology/2020.lrec-1.335/", |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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arch_path = dl_manager.download_and_extract(URL) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": arch_path}), |
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] |
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def _generate_examples(self, filepath): |
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with open(filepath, mode="r", encoding="utf-8") as f: |
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lines = f.read().splitlines() |
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for id, line in enumerate(lines): |
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yield id, {"text": line.strip()} |
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