  We propose a new word embedding model, called SPhrase, that incorporates
supervised phrase information. Our method modifies traditional word embeddings
by ensuring that all target words in a phrase have exactly the same context. We
demonstrate that including this information within a context window produces
superior embeddings for both intrinsic evaluation tasks and downstream
extrinsic tasks.
