Abstract
This paper presents the NLPTEA 2020 shared task for Chinese Grammatical Error Diagnosis (CGED) which seeks to identify grammatical error types, their range of occurrence and recommended corrections within sentences written by learners of Chinese as a foreign language. We describe the task definition, data preparation, performance metrics, and evaluation results. Of the 30 teams registered for this shared task, 17 teams developed the system and submitted a total of 43 runs. System performances achieved a significant progress, reaching F1 of 91% in detection level, 40% in position level and 28% in correction level. All data sets with gold standards and scoring scripts are made publicly available to researchers.- Anthology ID:
- 2020.nlptea-1.4
- Volume:
- Proceedings of the 6th Workshop on Natural Language Processing Techniques for Educational Applications
- Month:
- December
- Year:
- 2020
- Address:
- Suzhou, China
- Editors:
- Erhong YANG, Endong XUN, Baolin ZHANG, Gaoqi RAO
- Venue:
- NLP-TEA
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 25–35
- Language:
- URL:
- https://aclanthology.org/2020.nlptea-1.4
- DOI:
- Cite (ACL):
- Gaoqi Rao, Erhong Yang, and Baolin Zhang. 2020. Overview of NLPTEA-2020 Shared Task for Chinese Grammatical Error Diagnosis. In Proceedings of the 6th Workshop on Natural Language Processing Techniques for Educational Applications, pages 25–35, Suzhou, China. Association for Computational Linguistics.
- Cite (Informal):
- Overview of NLPTEA-2020 Shared Task for Chinese Grammatical Error Diagnosis (Rao et al., NLP-TEA 2020)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2020.nlptea-1.4.pdf