通过识别频繁子句来检测nou CGED系统中的语法错误

NLP-TEA@ACL Pub Date : 1900-01-01 DOI:10.18653/v1/W18-3730
Chuan-Jie Lin, Shao-Heng Chen
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引用次数: 1

摘要

汉语语法错误诊断任务的主要目标是检测汉语学习者所写句子中的单词错误。我们之前的系统会生成纠错的句子作为候选,并且基于大规模的中文n-gram数据集来测量它们的句子可能性。今年,我们进一步尝试识别长而频繁出现的子句,并将其标记为正确的,以避免提出太多的错误候选者。还测试了两种新的提示缺失和选择错误的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting Grammatical Errors in the NTOU CGED System by Identifying Frequent Subsentences
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.
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