Representing words considering their context through fixed size dense vectors ( word embedding s ) has become one the most fundamental blocks in several NLP systems. an unsupervised disambiguation system uses the similarity between word senses in a fixed context window to select the most suitable word sense using a pre-trained word embedding model and WordNet .