Another direction we explore is when the semantic features are computed within a multi-layer architecture.
we use the trained WSD model described so far to disambiguate the context of the target words and compute priors on their senses (a related idea was exploited, for example, in (Khapra et al., 2010)), then we update the semantic features and train another model.