CYUT Team Chinese Grammatical Error Diagnosis System Report in NLPTEA-2020 CGED Shared Task

Shih-Hung Wu, Junwei Wang


Abstract
This paper reports our Chinese Grammatical Error Diagnosis system in the NLPTEA-2020 CGED shared task. In 2020, we sent two runs with two approaches. The first one is a combination of conditional random fields (CRF) and a BERT model deep-learning approach. The second one is a BERT model deep-learning approach. The official results shows that our run1 achieved the highest precision rate 0.9875 with the lowest false positive rate 0.0163 on detection, while run2 gives a more balanced performance.
Anthology ID:
2020.nlptea-1.12
Volume:
Proceedings of the 6th Workshop on Natural Language Processing Techniques for Educational Applications
Month:
December
Year:
2020
Address:
Suzhou, China
Venue:
NLP-TEA
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
91–96
Language:
URL:
https://aclanthology.org/2020.nlptea-1.12
DOI:
Bibkey:
Cite (ACL):
Shih-Hung Wu and Junwei Wang. 2020. CYUT Team Chinese Grammatical Error Diagnosis System Report in NLPTEA-2020 CGED Shared Task. In Proceedings of the 6th Workshop on Natural Language Processing Techniques for Educational Applications, pages 91–96, Suzhou, China. Association for Computational Linguistics.
Cite (Informal):
CYUT Team Chinese Grammatical Error Diagnosis System Report in NLPTEA-2020 CGED Shared Task (Wu & Wang, NLP-TEA 2020)
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PDF:
https://aclanthology.org/2020.nlptea-1.12.pdf