As the only large human-annotated corpus for NLI currently available, the Stanford NLI Corpus (SNLI;Bowman et al., 2015) has enabled a good deal of progress on NLU, serving as a major benchmark for machine learning work on sentence understanding and spurring work on core representation learning techniques for NLU, such as attention (Wang and Jiang, 2016;Parikh et al., 2016), memory (Munkhdalai and Yu, 2017), and the use of parse structure (Mou et al., 2016b;Bowman et al., 2016;Chen et al., 2017).
sNLI falls short of providing a sufficient testing ground for machine learning models in two ways.