Knowledge guided distance supervision for biomedical relation extraction in Chinese electronic medical records

作者：

Highlights：

• The entity-type alignment is first proposed for coarse-grained relation extraction.

• The relation embeddings are learned and used as knowledge-enhanced features.

• A novel word attention mechanism derived from the relation translation is given.

• A bootstrap learning process is presented for fine-grained relation disambiguation.

摘要

•The entity-type alignment is first proposed for coarse-grained relation extraction.•The relation embeddings are learned and used as knowledge-enhanced features.•A novel word attention mechanism derived from the relation translation is given.•A bootstrap learning process is presented for fine-grained relation disambiguation.

论文关键词：Distant supervision,Biomedical relation extraction,Entity-type alignment,Relation embedding

论文评审过程：Received 7 January 2022, Revised 14 April 2022, Accepted 15 May 2022, Available online 18 May 2022, Version of Record 25 May 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117606