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 292,517 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}.

本文介绍了一个大规模的英语作为第二语言句子填空（SC）数据集，名为 SC-Ques，由 292,517 个真实世界中标准化英语考试中的 SC 问题组成。除此数据集外，基于该数据集，建立了一个综合性评测模型，通过训练大规模预训练语言模型自动解决 SC 问题。文中对基线模型的性能、限制和权衡进行了详细的分析。

SC-Ques: 为英语作为第二语言学习者设计的句子填空问题数据集