@inproceedings{rao-etal-2017-ijcnlp,
title = "{IJCNLP}-2017 Task 1: {C}hinese Grammatical Error Diagnosis",
author = "Rao, Gaoqi and
Zhang, Baolin and
Xun, Endong and
Lee, Lung-Hao",
editor = "Liu, Chao-Hong and
Nakov, Preslav and
Xue, Nianwen",
booktitle = "Proceedings of the {IJCNLP} 2017, Shared Tasks",
month = dec,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/I17-4001",
pages = "1--8",
abstract = "This paper presents the IJCNLP 2017 shared task for Chinese grammatical error diagnosis (CGED) which seeks to identify grammatical error types and their range of occurrence within sentences written by learners of Chinese as foreign language. We describe the task definition, data preparation, performance metrics, and evaluation results. Of the 13 teams registered for this shared task, 5 teams developed the system and submitted a total of 13 runs. We expected this evaluation campaign could lead to the development of more advanced NLP techniques for educational applications, especially for Chinese error detection. All data sets with gold standards and scoring scripts are made publicly available to researchers.",
}
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%0 Conference Proceedings
%T IJCNLP-2017 Task 1: Chinese Grammatical Error Diagnosis
%A Rao, Gaoqi
%A Zhang, Baolin
%A Xun, Endong
%A Lee, Lung-Hao
%Y Liu, Chao-Hong
%Y Nakov, Preslav
%Y Xue, Nianwen
%S Proceedings of the IJCNLP 2017, Shared Tasks
%D 2017
%8 December
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F rao-etal-2017-ijcnlp
%X This paper presents the IJCNLP 2017 shared task for Chinese grammatical error diagnosis (CGED) which seeks to identify grammatical error types and their range of occurrence within sentences written by learners of Chinese as foreign language. We describe the task definition, data preparation, performance metrics, and evaluation results. Of the 13 teams registered for this shared task, 5 teams developed the system and submitted a total of 13 runs. We expected this evaluation campaign could lead to the development of more advanced NLP techniques for educational applications, especially for Chinese error detection. All data sets with gold standards and scoring scripts are made publicly available to researchers.
%U https://aclanthology.org/I17-4001
%P 1-8
Markdown (Informal)
[IJCNLP-2017 Task 1: Chinese Grammatical Error Diagnosis](https://aclanthology.org/I17-4001) (Rao et al., IJCNLP 2017)
ACL