SC-Ques: A Sentence Completion Question Dataset for English as a Second Language Learners

• URL: http://arxiv.org/abs/2206.12036v2
• Date: Fri, 7 Apr 2023 11:55:04 GMT
• Title: SC-Ques: A Sentence Completion Question Dataset for English as a Second Language Learners
• Authors: Qiongqiong Liu, Yaying Huang, Zitao Liu, Shuyan Huang, Jiahao Chen, Xiangyu Zhao, Guimin Lin, Yuyu Zhou, Weiqi Luo
• Abstract summary: Sentence completion (SC) questions present a sentence with one or more blanks that need to be filled in, three to five possible words or phrases as options. We present a large-scale SC dataset, textscSC-Ques, which is made up of 289,148 ESL SC questions from real-world standardized English examinations.
• Score: 22.566710467490182
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Sentence completion (SC) questions present a sentence with one or more blanks that need to be filled in, three to five possible words or phrases as options. SC questions are widely used for students learning English as a Second Language (ESL). In this paper, we present a large-scale SC dataset, \textsc{SC-Ques}, which is made up of 289,148 ESL SC questions from real-world standardized English examinations. Furthermore, we build a comprehensive benchmark of automatically solving the SC questions by training the large-scale pre-trained language models on the proposed \textsc{SC-Ques} dataset. We conduct detailed analysis of the baseline models performance, limitations and trade-offs. The data and our code are available for research purposes from: \url{https://github.com/ai4ed/SC-Ques}.

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