1. A method comprising: analyzing a first natural language corpus to generate a latent representation for words in the first natural language corpus; calculating, for each word in the latent representation, a Euclidian distance between a left context of the each word and a right context of the each word, to yield a centroid of latent vectors for each word in the latent representation; analyzing a second natural language corpus having a target word, the target word being a word that is not in the first natural language corpus; and predicting, via a processor, a label for the target word based on the latent representation and the centroid of latent vectors for each word in the latent representation.
8. The method of claim 1 , wherein the target word is a collection of target words.