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from dataclasses import dataclass |
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import datasets |
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import pytorch_ie.data.builder |
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from pytorch_ie.annotations import LabeledSpan |
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from pytorch_ie.core import AnnotationList, annotation_field |
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from pytorch_ie.documents import TextDocument |
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from pytorch_ie.utils.span import tokens_and_tags_to_text_and_labeled_spans |
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class CoNLL2003Config(datasets.BuilderConfig): |
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"""BuilderConfig for CoNLL2003""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig for CoNLL2003. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super().__init__(**kwargs) |
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@dataclass |
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class CoNLL2003Document(TextDocument): |
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entities: AnnotationList[LabeledSpan] = annotation_field(target="text") |
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class Conll2003(pytorch_ie.data.builder.GeneratorBasedBuilder): |
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DOCUMENT_TYPE = CoNLL2003Document |
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BASE_DATASET_PATH = "conll2003" |
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BUILDER_CONFIGS = [ |
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CoNLL2003Config( |
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name="conll2003", version=datasets.Version("1.0.0"), description="CoNLL2003 dataset" |
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), |
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] |
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def _generate_document_kwargs(self, dataset): |
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return {"int_to_str": dataset.features["ner_tags"].feature.int2str} |
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def _generate_document(self, example, int_to_str): |
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doc_id = example["id"] |
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tokens = example["tokens"] |
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ner_tags = [int_to_str(tag) for tag in example["ner_tags"]] |
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text, ner_spans = tokens_and_tags_to_text_and_labeled_spans(tokens=tokens, tags=ner_tags) |
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document = CoNLL2003Document(text=text, id=doc_id) |
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for span in sorted(ner_spans, key=lambda span: span.start): |
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document.entities.append(span) |
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return document |
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