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Three Sentences Are All You Need: Local Path Enhanced Document Relation Extraction

Authors :
Huang, Quzhe
Zhu, Shengqi
Feng, Yansong
Ye, Yuan
Lai, Yuxuan
Zhao, Dongyan
Publication Year :
2021

Abstract

Document-level Relation Extraction (RE) is a more challenging task than sentence RE as it often requires reasoning over multiple sentences. Yet, human annotators usually use a small number of sentences to identify the relationship between a given entity pair. In this paper, we present an embarrassingly simple but effective method to heuristically select evidence sentences for document-level RE, which can be easily combined with BiLSTM to achieve good performance on benchmark datasets, even better than fancy graph neural network based methods. We have released our code at https://github.com/AndrewZhe/Three-Sentences-Are-All-You-Need.<br />Comment: ACL 2021

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2106.01793
Document Type :
Working Paper