Ranging from count-based to predictive or task-based methods, in the past years, many approaches were developed to produce word embeddings, such as Neural Probabilistic Language Model [3] , Word2Vec [28] , GloVe [32] , and more recently ELMo <cite>[33]</cite> , to name a few.