CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 12456 > Article
Paper
30 November 2022 A segment labeling method for Chinese nested named entity recognition
Tianci Shang, Baosong Deng
Author Affiliations +
Proceedings Volume 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022); 1245628 (2022) https://doi.org/10.1117/12.2659316
Event: International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 2022, Qingdao, China
Abstract
Named entity recognition (NER) is one of the fundamental technologies in natural language processing. NER task extracts the entities such as location, person and organization from unstructured texts, which plays an important role in machine translation and other tasks. However, lacking of effective solutions of nested named entities to fuzzy boundary makes Chinese named entity recognition much harder than other languages. In order to solve the challenges brought by Chinese nested named entities, a segment labeling method for Chinese named nested entity recognition is proposed in this paper. Firstly, every entity is treated as several non-separable units to improve the labeling method. Secondly, each unit will be tagged differently according to its grammar and function in a particular sentence. Finally, every main entity in the recognition sequence is considered as a starting point, and merges each sub-entity into a complete nested entity after a candidate test. To verify the effectiveness of the method, a Chinese military corpus is collected to test the performance of this proposed method. The accuracy value, recall value and F1 value of this method are higher than those of the ordinary methods, which shows that this method can effectively improve the performance of Chinese named entity recognition.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Tianci Shang and Baosong Deng "A segment labeling method for Chinese nested named entity recognition", Proc. SPIE 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 1245628 (30 November 2022); https://doi.org/10.1117/12.2659316
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 8 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Performance modeling
Neural networks
Feature extraction
Machine learning
Transformers
Convolution
Data hiding
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top