Overview of the ROCLING 2022 Shared Task for Chinese Healthcare Named Entity Recognition

Lung Hao Lee, Chao Yi Chen, Liang Chih Yu, Yuen Hsien Tseng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Scopus citations

Abstract

This paper describes the ROCLING-2022 shared task for Chinese healthcare named entity recognition, including task description, data preparation, performance metrics, and evaluation results. Among ten registered teams, seven participating teams submitted a total of 20 runs. This shared task reveals present NLP techniques for dealing with Chinese named entity recognition in the healthcare domain. All data sets with gold standards and evaluation scripts used in this shared task are publicly available for future research.

Original languageEnglish
Title of host publicationROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing
EditorsYung-Chun Chang, Yi-Chin Huang, Jheng-Long Wu, Ming-Hsiang Su, Hen-Hsen Huang, Yi-Fen Liu, Lung-Hao Lee, Chin-Hung Chou, Yuan-Fu Liao
PublisherThe Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
Pages363-368
Number of pages6
ISBN (Electronic)9789869576956
StatePublished - 2022
Event34th Conference on Computational Linguistics and Speech Processing, ROCLING 2022 - Taipei, Taiwan
Duration: 21 Nov 202222 Nov 2022

Publication series

NameROCLING 2022 - Proceedings of the 34th Conference on Computational Linguistics and Speech Processing

Conference

Conference34th Conference on Computational Linguistics and Speech Processing, ROCLING 2022
Country/TerritoryTaiwan
CityTaipei
Period21/11/2222/11/22

Keywords

  • Chinese language processing
  • health informatics
  • information extraction
  • named entity recognition

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