  In this technical report we propose an algorithm, called Lex2vec, that
exploits lexical resources to inject information into word embeddings and name
the embedding dimensions by means of distant supervision. We evaluate the
optimal parameters to extract a number of informative labels that is readable
and has a good coverage for the embedding dimensions.
