As demonstrated by  and Nickel and Kiela (2017), standard general-purpose representation models trained in an unsupervised way purely on distributional information are unfit for this task and unable to surpass the performance of simple frequency baselines (see also Table 1).
in what follows, we describe a novel supervised framework for constructing task-specific word embeddings, optimised for the graded entailment task at hand.