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A Multivariate Model for Representing Semantic Non-compositionality (1908.05490v1)

Published 15 Aug 2019 in cs.CL and cs.AI

Abstract: Semantically non-compositional phrases constitute an intriguing research topic in Natural Language Processing. Semantic non-compositionality --the situation when the meaning of a phrase cannot be derived from the meaning of its components, is the main characteristic of such phrases, however, they bear other characteristics such as high statistical association and non-substitutability. In this work, we present a model for identifying non-compositional phrases that takes into account all of these characteristics. We show that the presented model remarkably outperforms the existing models of identifying non-compositional phrases that mostly focus only on one of these characteristics.

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Authors (1)
  1. Meghdad Farahmand (1 paper)

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