Furthermore, each word is associated with a number of senses, the most plausible of which is selected dynamically during the composition process.
the results in table 1 show clearly that our model tends to group words that are both semantically and syntactically related; for example, and in contrast with the compared models which group words only at the semantic level, our model is able to retain tenses, numbers (singulars and plurals), and gerunds.