@inproceedings{rao-etal-2020-overview,
title = "Overview of {NLPTEA}-2020 Shared Task for {C}hinese Grammatical Error Diagnosis",
author = "Rao, Gaoqi and
Yang, Erhong and
Zhang, Baolin",
booktitle = "Proceedings of the 6th Workshop on Natural Language Processing Techniques for Educational Applications",
month = dec,
year = "2020",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.nlptea-1.4",
pages = "25--35",
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.",
}
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%0 Conference Proceedings
%T Overview of NLPTEA-2020 Shared Task for Chinese Grammatical Error Diagnosis
%A Rao, Gaoqi
%A Yang, Erhong
%A Zhang, Baolin
%S Proceedings of the 6th Workshop on Natural Language Processing Techniques for Educational Applications
%D 2020
%8 dec
%I Association for Computational Linguistics
%C Suzhou, China
%F rao-etal-2020-overview
%X 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.
%U https://aclanthology.org/2020.nlptea-1.4
%P 25-35
Markdown (Informal)
[Overview of NLPTEA-2020 Shared Task for Chinese Grammatical Error Diagnosis](https://aclanthology.org/2020.nlptea-1.4) (Rao et al., NLP-TEA 2020)
ACL