The Knowledge-Based Machine Translation paradigm requires a comprehensive analysis of input texts into an unambiguous machine-tractable representation of the propositional and meta-propositional meaning of that text, for which we use a particular framework referred to as ontological semantics. The work presented here begins with a definition of a representation language for lexical semantic specification (and syntax/semantics interface) to support such an analysis, as well as a generalized algorithm for building the meaning representation from these lexical semantic specifications, utilizing the ontology and a syntactic parse as knowledge sources. The core of the algorithm is an algorithm for semantic constraint satisfaction and relaxation, involving finding the best path over the ontology between a candidate filler of a relation and semantic constraints on that relation. The ontology is viewed as a multi-dimensional graph, with distinct topologies in each dimension reflecting specific semantic relations between nodes (representing concepts) , where weights or arc distance reflects strength of semantic relatedness in context (where the path-so-far context is maintained in a state transition table).

This article proposes a new interpretation of the relationship between poetic form and literary interpretation in Rostand’s Cyrano de Bergerac, focusing on the special affordances of rhyme and meter in dramatic verse and on Rostand’s virtuosic exploitation of poetic blending possibilities in Cyrano. I claim that poetic blends play a thematically essential role in this work, at a level far beyond their thematic contribution to most verse drama. Such a reading of Cyrano may thus help to expose general aspects of poetic blending which may be less visibly present in other texts. It also has consequences for our understanding of verbal humor and irony. In the final section of the article, I propose an extension of my analysis of metric and rhyming blends to the beginnings of a cognitive poetic treatment of intertextuality as blending.