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Compositionality modelling and non-compositionality detection with distributional semantics

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If you have a question about this talk, please contact Ekaterina Kochmar.

Distributional similarity has been used as a proxy for modelling lexical semantics for nearly two decades. There is now a significant and growing interest in moving these models from lexical to phrasal semantics. For just under one decade, many computational linguistics researchers have applied distributional semantics to the task of detecting non-compositionality of candidate multiwords. In this talk, I will give an overview of my work in this area. I will focus on the more recent work I have collaborated on, with Siva Reddy and colleagues, which borrows techniques from the state-of-the-art compositional distributional models for non-compositionality detection. Ultimately, these distributional models of phrasal semantics will need to be extended to incorporate non-compositionality.

This talk is part of the NLIP Seminar Series series.

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