A Novel Distributional Approach to Multilingual Conceptual Metaphor Recognition

We present a novel approach to the problem of multilingual conceptual metaphor recognition. Our approach extends recent work in conceptual metaphor discovery by combining a complex methodology for facet-based concept induction with a distributional vector space model of linguistic and conceptual metaphor. In the evaluation of our system in English, Spanish, Russian, and Farsi, we experiment with several state-of-the-art vector space models and demonstrate a clear benefit to the fine-grained concept representation that forms the basis of our methodology for conceptual metaphor recognition.