Papers by Difeng Wang

1 papers
Global-to-Local Neural Networks for Document-Level Relation Extraction (2020.emnlp-main)

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Challenge: Relation extraction (RE) aims to identify the semantic relations between named entities in text.
Approach: They propose a novel relation extraction model that encodes document information in terms of entity global and local representations and context relation representations.
Outcome: The proposed model achieves superior performance on two public datasets for document-level RE.

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