Nested Named Entity Recognition via Explicitly Excluding the Influence of the Best Path

Yiran Wang, Hiroyuki Shindo, Yuji Matsumoto, Taro Watanabe


Abstract
This paper presents a novel method for nested named entity recognition. As a layered method, our method extends the prior second-best path recognition method by explicitly excluding the influence of the best path. Our method maintains a set of hidden states at each time step and selectively leverages them to build a different potential function for recognition at each level. In addition, we demonstrate that recognizing innermost entities first results in better performance than the conventional outermost entities first scheme. We provide extensive experimental results on ACE2004, ACE2005, and GENIA datasets to show the effectiveness and efficiency of our proposed method.
Anthology ID:
2021.acl-long.275
Volume:
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3547–3557
Language:
URL:
https://aclanthology.org/2021.acl-long.275
DOI:
10.18653/v1/2021.acl-long.275
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.acl-long.275.pdf