Addressing three main topics, this work begins by describing the general nature of non-literal language. Relatively obscure topics are defined, including metonymy and synesis. Secondly, the nature of metonymy and metaphor is investigated, along with related semantic phenomena, such as literalness, inconsistency, and lexical and case ambiguity. The final main topic is an approach to processing metonymy and metaphor, broken down into three parts: a model of language in which they are decomposed into simpler elements; an artificial intelligence theory called Collative Semantics (CS); and an implementation of CS in a computer program called MetaS, which recognizes metaphors, metonymies, and various nontropes in short English sentences.

Addressing three main topics, this work begins by describing the general nature of non-literal language. Relatively obscure topics are defined, including metonymy and synesis. Secondly, the nature of metonymy and metaphor is investigated, along with related semantic phenomena, such as literalness, inconsistency, and lexical and case ambiguity. The final main topic is an approach to processing metonymy and metaphor, broken down into three parts: a model of language in which they are decomposed into simpler elements; an artificial intelligence theory called Collative Semantics (CS); and an implementation of CS in a computer program called MetaS, which recognizes metaphors, metonymies, and various nontropes in short English sentences.