Cliff O'Reilly

Climax is a compound rhetorical figure, consisting of the trope, Crementum, and the scheme, Gradatio (itself a series of Anadiploses), a combination that results in compelling semiotic effects. The component figures impact the conveyed meaning independently and collectively, which we chart by way of the PATH image schema and the Gestalt Figure-Ground relation. These layers of meaning function in a similar fashion to the dual figure visual phenomenon examined by Koffka and Rubin. Key elements of our project include knowledge representation of Climax and component figures, a suite of ontologies that map the cognitive features supporting these complex structures and a base model of surface entities augmented with the related cognitive functions. Our ontologies are developed in the Web Ontology Language (OWL), validated for consistency and published online.

If phenomenal consciousness is illusory and reduces to a perceptual interface between a belief-driven ego system and a lattice platform of both singular and hybrid connectionally-constructed concepts where phenomena themselves are sensation- induced constructs of complexes of things in the world then in order to communicate in terms of true meanings we would require a translation system between the complexes of things that have importance for creatures of different biologies whether evolved or synthetic. In this paper I investigate and propose an ontological scheme that can act in some way to bridge this gap and potentially allow humans to talk with robots about themselves and the world.

There is a driving need computationally to interrogate large bodies of text for a range of non-denotative meaning (e.g., to plot chains of reasoning, detect sentiment, diagnose genre, and so forth). But such meaning has always proven computationally allusive. It is often implicit, ‘hidden’ meaning, evoked by linguistic cues, stylistic arrangement, or conceptual structure – features that have hitherto been difficult for Natural Language Processing systems to recognize and use. Non-denotative textual effects are the historical concern of rhetorical studies, and we have turned to rhetoric in order to find new ways to advance NLP, especially for sophisticated tasks like Argument Mining. This paper highlights certain rhetorical devices that encode levels of meaning that have been overlooked in Computational Linguistics generally and Argument Mining particularly, and yet lend themselves to automated detection. These devices are the linguistic configurations known as Rhetorical Figures. We argue for the importance of these devices for Argument Mining, especially in collocations, and we present an XML annotation scheme for Rhetorical Figures to make figuration more tractable for computational approaches, particularly with an eye on the improvements they offer Argument Mining. We also discuss the intellectual and technical challenges involved in figure annotation and the implications for Machine Learning.

This paper surveys ontological modeling of rhetorical concepts, developed for use in argument mining and other applications of computational rhetoric, projecting their future directions. We include ontological models of argument schemes applying Rhetorical Structure Theory (RST); the RhetFig proposal for modeling; the related RetFig Ontology of Rhetorical Figures for Serbian (developed by two of the authors); and the Lassoing Rhetoric project (developed by another of the authors). The Lassoing Rhetoric venture is interesting for its multifaceted approach to linguistic devices, prominently including rhetorical figures, but also RST relations and stylistic models, like the use of historic present. This application takes a natural language text input and uses syntactic parsing tools to produce a knowledge base of linguistic entities using references to an OWL ontological framework, locating these devices using Semantic Web Rule Language (SWRL) logic rules. The paper also reports on a similar approach in research into detecting ironic tweets in a Serbian twitter corpus. The rhetorical schemes used for argument mining are also presented, as well as some suggestions for novel argument schemes based on the ontological approach to rhetorical figuration.