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:句子补全问题(SC)需要填写一个或多个空白的句子,提供三到五个可选的单词或短语。SC问题被广泛用于学习英语作为第二语言(ESL)的学生。本文介绍了一个大规模的SC数据集,SC-Ques,它由来自真实标准化英语考试的289,148个ESL SC问题组成。此外,我们通过在提出的SC-Ques数据集上训练大规模的预训练语言模型,构建了自动解决SC问题的全面基准测试。我们对基线模型的性能、局限性和权衡进行了详细的分析。数据和我们的代码可供研究目的从以下网址获取: \url{https://github.com/ai4ed/SC-Ques}。