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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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@dataclass |
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class GermaNERDocument(TextDocument): |
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entities: AnnotationList[LabeledSpan] = annotation_field(target="text") |
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class GermaNER(pytorch_ie.data.builder.GeneratorBasedBuilder): |
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DOCUMENT_TYPE = GermaNERDocument |
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BASE_DATASET_PATH = "germaner" |
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VERSION = datasets.Version("0.9.1") |
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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 = GermaNERDocument(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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