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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