Title
Embeddings Of Label Components For Sequence Labeling: A Case Study Of Fine-Grained Named Entity Recognition
Abstract
In general, the labels used in sequence labeling consist of different types of elements. For example, I0H-format entity labels, such as B-Person and I-Person, can be decomposed into span (B and I) and type information (Person). However, while most sequence labeling models do not consider such label components, the shared components across labels, such as Person, can be beneficial for label prediction. In this work, we propose to integrate label component information as embeddings into models. Through experiments on English and Japanese fine-grained named entity recognition, we demonstrate that the proposed method improves performance, especially for instances with low-frequency labels.
Year
Venue
DocType
2020
ACL
Conference
Volume
Citations 
PageRank 
2020.acl-srw
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Kato Takuma100.34
Kaori Abe234.08
Hiroki Ouchi3188.08
Miyawaki Shumpei400.34
Jun Suzuki55510.39
Kentaro Inui61008120.35