Lexico-Semantic Multiword Expression Extraction
Tim Van de Cruys, M.B. Villada Moirón, Ineke Schuurman, V. Vandeghinste, F. Van Eynde, P.D. Dirix · University of Groningen research database (University of Groningen / Centre for Information Technology) · 2007
This paper describes a fully unsupervised and automated method for the large-scale extraction of multiword expressions (MWEs) from large corpora. The method takes into account the non-compositionality of MWEs; the intuition is that a noun within a MWE cannot easily be replaced by a semantically similar noun. To implement this intuition, a noun clustering is automatically extracted (using distributional similarity measures), which gives us clusters of semantically related nouns. Next, a number of statistical measures – based on selectional preferences – is developed that formalize the intuition of non-compositionality. The ratio of individual noun preference over cluster preference shows how likely a particular expression is to be a MWE (i.e. whether or not an individual noun accounts for all the preference of a certain cluster). Our approach has been tested on Dutch, and has been both manually and automatically evaluated. 1