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We test and evaluate a context-based method for MWEs compositionality detection that utilizes word embeddings. Embeddings for individual words are used to get representations of target expressions and their context. In making a judgement on compositionality/idiomaticity of an expression, our algorithm relies on the expectation that when a MWE is used literally constituents retain their original meanings and are semantically related to surrounding context words, which is not normally true of idiomatic usage. Context is the only factor that decision about compositionality of an expression is based on, which adds to simplicity and universality of the method. We test the recently introduced idea of applying Principal Component Analysis to represent semantic composition and argue that its performance is at least as good as the state of the art.

Teasing Apart Russian Idioms And Homonymic Compositional Expressions: A Word Embedding Approach