CMMC-BDRC Solution to the NLP-TEA-2018 Chinese Grammatical Error Diagnosis Task

NLP-TEA@ACL Pub Date : 1900-01-01 DOI:10.18653/v1/W18-3726
Yongwei Zhang, Q. Hu, Fang Liu, Yueguo Gu
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引用次数: 2

Abstract

Chinese grammatical error diagnosis is an important natural language processing (NLP) task, which is also an important application using artificial intelligence technology in language education. This paper introduces a system developed by the Chinese Multilingual & Multimodal Corpus and Big Data Research Center for the NLP-TEA shared task, named Chinese Grammar Error Diagnosis (CGED). This system regards diagnosing errors task as a sequence tagging problem, while takes correction task as a text classification problem. Finally, in the 12 teams, this system gets the highest F1 score in the detection task and the second highest F1 score in mean in the identification task, position task and the correction task.
cmc - bdrc解决NLP-TEA-2018汉语语法错误诊断任务
汉语语法错误诊断是一项重要的自然语言处理(NLP)任务,也是人工智能技术在语言教育中的重要应用。本文介绍了汉语多语多模态语料库与大数据研究中心为NLP-TEA共享任务开发的汉语语法错误诊断系统(CGED)。该系统将错误诊断任务视为序列标注问题,而将纠错任务视为文本分类问题。最终,在12支队伍中,本系统在检测任务中F1得分最高,在识别任务、定位任务和纠正任务中F1得分均值第二高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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