belgeli

ds = tfds.load('huggingface:docred')

Multiple entities in a document generally exhibit complex inter-sentence relations, and cannot be well handled by existing relation extraction (RE) methods that typically focus on extracting intra-sentence relations for single entity pairs. In order to accelerate the research on document-level RE, we introduce DocRED, a new dataset constructed from Wikipedia and Wikidata with three features:
    - DocRED annotates both named entities and relations, and is the largest human-annotated dataset for document-level RE from plain text.
    - DocRED requires reading multiple sentences in a document to extract entities and infer their relations by synthesizing all information of the document.
    - Along with the human-annotated data, we also offer large-scale distantly supervised data, which enables DocRED to be adopted for both supervised and weakly supervised scenarios.

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    "vertexSet": [
        [
            {
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                "sent_id": {
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    "labels": {
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            "tail": {
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            "relation_id": {
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            "relation_text": {
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}