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        <title>Detecting Grammatical Errors in the NTOU CGED System by Identifying Frequent Subsentences</title>
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            <namePart type="given">Yuen-Hsien</namePart>
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    <abstract>The main goal of Chinese grammatical error diagnosis task is to detect word er-rors in the sentences written by Chinese-learning students. Our previous system would generate error-corrected sentences as candidates and their sentence likeli-hood were measured based on a large scale Chinese n-gram dataset. This year we further tried to identify long frequent-ly-seen subsentences and label them as correct in order to avoid propose too many error candidates. Two new methods for suggesting missing and selection er-rors were also tested.</abstract>
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%0 Conference Proceedings
%T Detecting Grammatical Errors in the NTOU CGED System by Identifying Frequent Subsentences
%A Lin, Chuan-Jie
%A Chen, Shao-Heng
%Y Tseng, Yuen-Hsien
%Y Chen, Hsin-Hsi
%Y Ng, Vincent
%Y Komachi, Mamoru
%S Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F lin-chen-2018-detecting
%X The main goal of Chinese grammatical error diagnosis task is to detect word er-rors in the sentences written by Chinese-learning students. Our previous system would generate error-corrected sentences as candidates and their sentence likeli-hood were measured based on a large scale Chinese n-gram dataset. This year we further tried to identify long frequent-ly-seen subsentences and label them as correct in order to avoid propose too many error candidates. Two new methods for suggesting missing and selection er-rors were also tested.
%R 10.18653/v1/W18-3730
%U https://aclanthology.org/W18-3730/
%U https://doi.org/10.18653/v1/W18-3730
%P 203-206

Markdown (Informal)

[Detecting Grammatical Errors in the NTOU CGED System by Identifying Frequent Subsentences](https://aclanthology.org/W18-3730/) (Lin & Chen, NLP-TEA 2018)

• Detecting Grammatical Errors in the NTOU CGED System by Identifying Frequent Subsentences (Lin & Chen, NLP-TEA 2018)

ACL

• Chuan-Jie Lin and Shao-Heng Chen. 2018. Detecting Grammatical Errors in the NTOU CGED System by Identifying Frequent Subsentences. In Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications, pages 203–206, Melbourne, Australia. Association for Computational Linguistics.