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CodRED: A Cross-Document Relation Extraction Dataset for Acquiring Knowledge in the Wild

codred: مجموعة بيانات استخراج العلاقة بين المستندات للحصول على المعرفة في البرية

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 Publication date 2021
and research's language is English
 Created by Shamra Editor




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Existing relation extraction (RE) methods typically focus on extracting relational facts between entity pairs within single sentences or documents. However, a large quantity of relational facts in knowledge bases can only be inferred across documents in practice. In this work, we present the problem of cross-document RE, making an initial step towards knowledge acquisition in the wild. To facilitate the research, we construct the first human-annotated cross-document RE dataset CodRED. Compared to existing RE datasets, CodRED presents two key challenges: Given two entities, (1) it requires finding the relevant documents that can provide clues for identifying their relations; (2) it requires reasoning over multiple documents to extract the relational facts. We conduct comprehensive experiments to show that CodRED is challenging to existing RE methods including strong BERT-based models.



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