In the future, we plan to discover new conceptual primitives in a more automatic and scalable way by means of dependency-based word embeddings.
we will exploit the internally-learned context embeddings of the skip-gram model in conjunction with the standard target word embeddings, to weigh context compatibility together with word similarity.