Distributional models assume that the contexts of a linguistic unit (such as a word, a multi-word expression, a phrase, a sentence, etc.) provide information about the meaning of the linguistic unit (Firth, 1957; Harris, 1968). They have been widely applied in data-intensive lexical semantics (among other areas), and proven successful in diverse research issues, such as the representation and disambiguation of word senses (Schuetze, 1998; McCarthy et al., 2004; Springorum et al., 2013), selectional preference modelling (Herdagdelen and Baroni, 2009; Erk et al., 2010; Schulte im Walde, 2010), the compositionality of compounds and phrases (McCarthy et al., 2003; Reddy et al., 2011; Boleda et al., 2013), or as a general framework across semantic tasks ('distributional memory', cf. Baroni and Lenci, 2010; Pado and Utt, 2012), to name just a few examples.
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