  We present a large-scale dataset, ReCoRD, for machine reading comprehension
requiring commonsense reasoning. Experiments on this dataset demonstrate that
the performance of state-of-the-art MRC systems fall far behind human
performance. ReCoRD represents a challenge for future research to bridge the
gap between human and machine commonsense reading comprehension. ReCoRD is
available at http://nlp.jhu.edu/record.
