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import datasets |
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from tqdm import tqdm |
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_CITATION = """ |
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@inproceedings{balasuriya-etal-2009-named, |
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title = "Named Entity Recognition in Wikipedia", |
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author = "Balasuriya, Dominic and |
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Ringland, Nicky and |
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Nothman, Joel and |
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Murphy, Tara and |
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Curran, James R.", |
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booktitle = "Proceedings of the 2009 Workshop on The People{'}s Web Meets {NLP}: |
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Collaboratively Constructed Semantic Resources (People{'}s Web)", |
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month = aug, |
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year = "2009", |
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address = "Suntec, Singapore", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/W09-3302", |
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pages = "10--18", |
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} |
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""" |
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_LICENCE = "CC-BY 4.0" |
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_DESCRIPTION = """ |
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WikiGold dataset. |
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""" |
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_URL = ( |
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"https://github.com/juand-r/entity-recognition-datasets/raw/master/" |
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"data/wikigold/CONLL-format/data/wikigold.conll.txt" |
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) |
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NER_TAGS_DICT = { |
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"O": 0, |
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"PER": 1, |
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"LOC": 2, |
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"ORG": 3, |
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"MISC": 4, |
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} |
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NER_BIO_TAGS_DICT = { |
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"O": 0, |
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"B-PER": 1, |
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"I-PER": 2, |
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"B-LOC": 3, |
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"I-LOC": 4, |
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"B-ORG": 5, |
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"I-ORG": 6, |
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"B-MISC": 7, |
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"I-MISC": 8 |
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} |
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class WikiGoldConfig(datasets.BuilderConfig): |
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"""BuilderConfig for WikiGold""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig for WikiGold. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(WikiGoldConfig, self).__init__(**kwargs) |
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class WikiGold(datasets.GeneratorBasedBuilder): |
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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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"id": datasets.Value("string"), |
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"tokens": datasets.features.Sequence(datasets.Value("string")), |
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"ner_tags": datasets.features.Sequence( |
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datasets.features.ClassLabel( |
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names=["O", "PER", "LOC", "ORG", "MISC"] |
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) |
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), |
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"ner_bio_tags": datasets.features.Sequence( |
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datasets.features.ClassLabel( |
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names=["O", "B-PER", "I-PER", "B-LOC", "I-LOC", |
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"B-ORG", "I-ORG", "B-MISC", "I-MISC"] |
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) |
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), |
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} |
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), |
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supervised_keys=None, |
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citation=_CITATION, |
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license=_LICENCE, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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urls_to_download = dl_manager.download_and_extract(_URL) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"filepath": urls_to_download}, |
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), |
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] |
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def _generate_examples(self, filepath=None): |
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num_lines = sum(1 for _ in open(filepath)) |
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id = 0 |
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with open(filepath, "r") as f: |
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tokens, ner_tags, ner_bio_tags = [], [], [] |
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for line in tqdm(f, total=num_lines): |
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line = line.strip().split() |
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if line: |
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assert len(line) == 2 |
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token, ner_tag = line |
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if token == "-DOCSTART-": |
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continue |
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tokens.append(token) |
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ner_bio_tags.append(ner_tag) |
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if ner_tag != "O": |
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ner_tag = ner_tag.split("-")[1] |
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ner_tags.append(NER_TAGS_DICT[ner_tag]) |
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elif tokens: |
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record = { |
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"tokens": tokens, |
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"id": str(id), |
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"ner_tags": ner_tags, |
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"ner_bio_tags": ner_bio_tags, |
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} |
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tokens, ner_tags = [], [] |
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id += 1 |
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yield record["id"], record |
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if tokens: |
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record = { |
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"tokens": tokens, |
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"id": str(id), |
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"ner_tags": ner_tags, |
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"ner_bio_tags": ner_bio_tags, |
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} |
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yield record["id"], record |
