Journal of Natural Language Processing
Online ISSN : 2185-8314
Print ISSN : 1340-7619
ISSN-L : 1340-7619
General Paper (Peer-Reviewed)
Nested Named Entity Recognition via Explicitly Excluding the Influence of the Best Path
Yiran WangHiroyuki ShindoYuji MatsumotoTaro Watanabe
Author information
JOURNAL FREE ACCESS

2022 Volume 29 Issue 1 Pages 23-52

Details
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, GENIA, and NNE datasets to show the effectiveness and efficiency of our proposed method.

Content from these authors
© 2022 The Association for Natural Language Processing
Previous article Next article
feedback
Top