Instead of optimising individual word embeddings, our model uses general-purpose embeddings and optimises a separate neural component to adapt these to the specific task.
our neural Supervised Directional Similarity Network (SDSN) dynamically produces task-specific embeddings optimised for scoring the asymmetric lexical entailment relation between any two words, regardless of their presence in the training resource.