中国EFL/ESL学习者的记分和纠错论文数据集

Kai Jin, Wuying Liu
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引用次数: 0

摘要

一定规模的EFL/ESL(英语作为外语或第二语言)学习者精细注释的论文数据集不仅是语言研究和教学的重要语言资源,也是语言相关计算科学的重要材料。遗憾的是,在互联网上公开的这类数据不仅数量少,而且质量参差不齐,尤其是中国学习者的数据。我们收集了147篇中国英语/ESL学习者的作文,由4位老师按照相同的标准进行评分,并由1位老师对主要错误进行批改,并在拼改评分系统中进行评分。然后,我们将分数文件、错误注释文件、论文文件与上下文信息结合起来,构建了中国英语/ESL学习者分数和错误注释论文数据集(SeedCel),该数据集在互联网上开放,并将逐步更新。本文解释了SeedCel是如何构建的,SeedCel的细节是什么,以及将在哪里使用SeedCel。
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Scored and Error-annotated Essay Dataset of Chinese EFL/ESL Learners
A certain scale of finely annotated essay dataset of EFL/ESL (English as a foreign language or the second language) learners is not only an important language resource for language research and teaching, but also contributing materials for language-related computing science. Unfortunately, this type of data open on the Internet are not only of small quantity but also of uneven quality, especially such data of Chinese learners. We collected 147 essays of Chinese EFL/ESL learners and had four teachers score them under the same criteria and one teacher annotate major errors, and have them scored in Pigai scoring system. We then structured the score file, error-annotated files, essay files together with context information, and built the Scored and Error-annotated Essay Dataset of Chinese EFL/ESL Learners (SeedCel) which is open on the Internet and will be incrementally updated. This paper explains how SeedCel is constructed, what the details of SeedCel are, and where SeedCel will be used.
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