An annotation scheme for Rhetorical Figures

Abstract

Abstract. 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 structurefeatures 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.

Recognizing rhetoric in science policy arguments

“…In our analysis, we identified occurrences of two of the proleptic rhetorical argument strategies she describes: Protocatalepsis and Prolepsis as Presage. The rhetorical figure annotation system proposed in [9] accommodates the description of compound rhetorical figures, where multiple figures overlap within the same span of text, which were found in our analyses.…”

“…2 Until we had done these analyses, we had no idea of the range of types and density of figures that would need to be accommodated. Furthermore, the analyses thoroughly demonstrated the need to use an annotation scheme such as described in [9] capable of handling compound rhetorical figures. We plan to use the corpus for research on automatic figure detection.…”

“…Note that RhetFig [8] does not provide a corpus of annotated full-text articles; instead the goal was to provide multiple examples of each figure from a variety of sources. A limited amount of research has been done on automatic detection of rhetorical schemes and tropes; for surveys see in [9,13]. Researchers have begun to investigate how automatically detected rhetorical figures could be used for argument mining [13].…”

Harnessing rhetorical figures for argument mining

“…3, we can see that the thickly bordered I-nodes corresponding to the figure are once again in a sibling relationship. 20 While this constellation is similar to that in Example (2) of Epanaphora, the annotation shows the I-nodes as elements of a rephrase relation rather than support and they are therefore not identified as part of the support and conflict relations that we are focusing on.…”

“…Although no single figure discussed here comprises a substantial proportion of the entire text, combined these eight figures (selected out of the hundreds catalogued in the rhetorical tradition) cover almost fifteen percent of the entire corpus. Rather than used intentionally to engender some particular rhetorical effect, we can in part see the figures as reflective of cognitive predispositions and functional imperatives [20] -extending the suggested distinction between deliberate and non-deliberate metaphors to all figures [42]. The kind of corpus and approach we use in this pilot study provide an important testing ground in this respect.…”