Joint entity recognition and relation extraction as a multi-head selection problem

作者：

Highlights：

• We propose a new joint neural model for entity recognition and relation extraction.

• Our model does not rely on external NLP tools nor hand-crafted features.

• Entities and relations within the same sentence are extracted simultaneously.

• We experimentally evaluate extensively on four datasets (ACE04, CoNLL04, ADE, DREC).

• Our model achieves state-of-the-art performance in different contexts and languages.

摘要

•We propose a new joint neural model for entity recognition and relation extraction.•Our model does not rely on external NLP tools nor hand-crafted features.•Entities and relations within the same sentence are extracted simultaneously.•We experimentally evaluate extensively on four datasets (ACE04, CoNLL04, ADE, DREC).•Our model achieves state-of-the-art performance in different contexts and languages.

论文关键词：Entity recognition,Relation extraction,Multi-head selection,Joint model,Sequence labeling

论文评审过程：Received 20 April 2018, Revised 13 July 2018, Accepted 14 July 2018, Available online 17 July 2018, Version of Record 25 July 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.07.032