GDPNet: Refining Latent Multi-View Graph for Relation Extraction

@inproceedings{Xue2021GDPNetRL,
  title={GDPNet: Refining Latent Multi-View Graph for Relation Extraction},
  author={Fuzhao Xue and Aixin Sun and Hao Zhang and Eng Siong Chng},
  booktitle={AAAI},
  year={2021}
}
Relation Extraction (RE) is to predict the relation type of two entities that are mentioned in a piece of text, e.g., a sentence or a dialogue. When the given text is long, it is challenging to identify indicative words for the relation prediction. Recent advances on RE task are from BERT-based sequence modeling and graph-based modeling of relationships among the tokens in the sequence. In this paper, we propose to construct a latent multi-view graph to capture various possible relationships… 
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TLDR
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TLDR
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