This paper presents a constructioninspecific model of multiword expression decomposability based on latent semantic analysis. We use latent semantic analysis to determine the similarity between a multiword expression and its constituent words, and claim that higher similarities indicate greater decomposability. We test the model over English noun-noun compounds and verb-particles, and evaluate its correlation with similarities and hyponymy values in WordNet. Based on mean hyponymy over partitions of data ranked on similarity, we furnish evidence for the calculated similarities being correlated with the semantic relational content of WordNet.
Baldwin et al. REF use Latent Semantic Analysis (LSA) to calculate the similarity between a phrase and its components, reasoning that higher similarity indicates higher compositionality.
An Empirical Model Of Multiword Expression Decomposability
Workshop On Multiword Expressions: Analysis, Acquisition And Treatment
Computer Science