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}.

翻译：句子完形填空（SC）题目给出一个包含一个或多个待填空格的句子，并附有三到五个单词或短语作为选项。这类题目广泛用于英语作为第二语言（ESL）的学习者。本文提出了一个大规模SC数据集\textsc{SC-Ques}，该数据集由来自真实标准化英语考试的289,148道ESL完形填空题目构成。此外，我们通过在所提出的\textsc{SC-Ques}数据集上训练大规模预训练语言模型，构建了自动解答SC题目的综合基准。我们对基线模型的性能、局限性及权衡进行了详细分析。相关数据及代码已面向研究目的开源：\url{https://github.com/ai4ed/SC-Ques}。