A novel end-to-end neural network for simultaneous filtering of task-unrelated named entities and fine-grained typing of task-related named entities
Recently, one emerging problem in Named Entity Typing (NET) is the fine-grained classification of task-related entities co-existing with task-unrelated entities. The traditional pipeline framework decomposes this problem into two sub-tasks. The first sub-task filters out the task-unrelated entities,...
Saved in:
Main Authors: | Li, Qi, Mao, Kezhi, Li, Pengfei, Xu, Yuecong, Lo, Edmond Yat Man |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Article |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/162082 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Enhancing HMM-based biomedical named entity recognition by studying special phenomena
by: Zhang, J., et al.
Published: (2013) -
A named entity recognizer for Filipino texts
by: Lim, Nathalie Rose T., et al.
Published: (2007) -
Make it easy: An effective end-to-end entity alignment framework
by: GE, Congcong, et al.
Published: (2021) -
Application of association rules mining to Named Entity Recognition and co-reference resolution for the Indonesian language
by: Budi, I., et al.
Published: (2013) -
Multi-criteria-based active learning for named entity recognition
by: SHEN DAN
Published: (2011)