More interestingly, it is claimed that the relationship between vector spaces that represent different language word semantics can be captured by a linear transformation.
we propose to use word embedding vectors of translation word pairs to train a supervised classifier which can predict whether a new pair of words in two different languages can be under a translation relation, according to the regularities learned from a small training set.