  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}.
