Automatic detection and interpretation of nominal metaphor based on the theory of meaning

摘要

Automatic processing of metaphors can be explicitly divided into two subtasks: recognition and interpretation. This paper presents an approach to recognize nominal metaphorical references and to interpret metaphors by exploiting distributional semantics word embedding techniques and calculating semantic relatedness. In terms of detection, our idea is that nominal metaphors consist of source and target domains and that domains present in metaphors will be less related than domains present in non-metaphors. We represent the meaning of the concept as a vector in high-dimensional conceptual space derived from the corpus and compute the relatedness between the vectors to complete the task of detection. Relatedness here is based on the semantics of concepts. Thus, the model we present deals with metaphors where target and source have the same direct ancestors, such as "A surgeon is a butcher".