Vector space word representations learned using unsupervised algorithms are often effective features in supervised learning methods (Turian et al., 2010).
many such representations are designed to capture lexical semantic properties and are quite effective features in semantic processing, including named entity recognition (Turian et al., 2009), word sense disambiguation (Huang et al., 2012), and lexical entailment (Baroni et al., 2012).