But such meaning has always proven computationally allusive. 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.
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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.
Rhetorical Figures are cognitively moulded linguistic devices that serve functional, mnemonic, and aesthetic purposes. Take the famous maxim from John F.
Ask not what your country can do for you. Ask what you can do for your country. The cognitive affinities explain its mnemonic and aesthetic effects, but its tight form-functional correlation, studied in an approach known as Figural Logic , is what makes it so interesting for the computational modeling of natural argumentation.
The form is tractable for automatic detection. The function gives us its rhetorical purpose. There is a growing interest in the convergence of rhetoric, argumentation, and Advanced Natural Language Processing ANLP — that is, in the new field of Computational Rhetoric — sparked by such works as [ 10 , 21 — 24 , 53 , 61 , 62 ]. Our work addresses this surprising omission [ 2 , 3 , 19 , 20 , 28 — 30 , 49 , 50 , 54 , 60 ]. Meanwhile, over in Computational Linguistics, there is an equally surprising omission. Computational Linguists have had success at detecting some Rhetorical Figures, but have shown little interest in the Rhetorical Functions those figures serve.
We are building an approach to Computational Rhetoric that combines the insights of Figural Logic with the goals of Argument Mining — namely, finding patterns of reasoning in texts — which promises equally rich payoffs for both computer science specifically, in Argument Mining and Computational Linguistics and for rhetorical theory specifically, the understanding of Rhetorical Figures.
Serious challenges need to be resolved in Computational Rhetoric for us to reach the Argument Mining pot of gold. Our approach involves a more sophisticated conception of Rhetorical Figures than has been adopted heretofore — in computational approaches, but also in humanistic and social science approaches. Our research operates at layers of formal and functional abstraction that have not been previously explored though see [ 37 ] for promising new advances.
It depends fundamentally on an annotation format for Rhetorical Figures, which we report in this paper. In this paper, we argue for the importance of Rhetorical Figures for ANLP generally and Argument Mining specifically; we identify the challenges and opportunities of integrating a rich knowledge of Rhetorical Figures into ANLP; and, most specifically, we offer an eXtensible Markup Language XML annotation scheme for Rhetorical Figures that meets some of these challenges and therefore opens up new opportunities for Argument Mining and Computational Linguistics, especially in concert with ML.
Computationally, Rhetorical Figures are critical to the understanding of natural language for three central reasons. First, they are endemic to human language. This fact is established beyond dispute for a few tropes, such as metaphor, which is a central focus of Cognitive Linguistics and deeply entrenched in ontologies like FrameNet and WordNet.
But it is equally true of literally a word we do not use lightly hundreds of other figures.
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If we want to develop language-perceptive algorithms, they must have knowledge of the figurative dimensions of language. Again, this is well understood for metaphor and simile, though it gets much less overt attention , which epitomize analogic argumentation, but is largely unrecognized for most figures. It has positionally bonded repetitions: position and identity are a snap for text algorithms. The contemporary scholar most responsible for the claim that Rhetorical Figures are constructions with especially tight couplings of form and function is Jeanne Fahnestock, whose Figural Logic is brilliantly articulated in Rhetorical Figures in Scientific Argumentation [ 17 ] see also [ 63 ]—85, [ 26 ].
Fahnestock charts Rhetorical Figures for the way they epitomize lines of argument, relying almost exclusively for her data on a domain with particularly rigorous standards of argumentation, the natural sciences. As she shows, the Figural-Logic view actually goes back at least to Aristotle, who links specific figures directly to specific lines of argument that is, to topoi , and it occupies a significant place in the rhetorical tradition as late as the 19th century.
But, aside from a very few exceptions, such as Perleman and Olbrecht-Tyteca [ 51 ], this view was largely forgotten in modern rhetoric, with figures coming to be associated with style, and style coming to be associated with aesthetics, aesthetics with superficiality. Rhetorical Figures are not without their computational challenges, of course. Metaphor remains elusive, for instance, despite all the attention it has attracted in Cognitive Science, Artificial Intelligence AI , and linguistics, including Computational Linguistics, over the last several decades.
Metaphor is a type of figure known as a trope , which depends on semantic features in a kind of constrained and harmonious conflict with each other.
We are not yet successful enough with straight-line semantics to get very far with these kinds of semantic turns. Some tropes such as oxymoron, which is a juxtaposition of antonymic terms, such as square circle or deafening silence can be reliably detected [ 19 ]. The young would choose an exciting life; the old a happy death. Like tropes, schemes are pervasive in ordinary language, and like tropes they occur in novel configurations that stand out against a ground of conventionality.
Consider rhyme, a prototypical scheme in which syllables repeat at the ends of words. If you press a stone with your finger, the finger is also pressed by the stone. Gay rights are human rights, and human rights are gay rights. A place for everything, and everything in its place. A fourth Rhetorical Function of the antimetabole is to convey Irrelevance-of-Order, well known from algebra and predicate calculus:. We have built a curated list of over antimetaboles illustrating these functions, but only have space for a few more representative examples:.
A corollary of PHC [the Principle of Hierarchical Coincidence] is that resources flow toward political power, and political power flows toward resources; or, the power of state and of capital typically appear in conjunction and are mutually reinforcing. Women are changing the universities and the universities are changing women. The negation of a conjunction is the disjunction of the negations and the negation of a disjunction is the conjunction of the negations.
Anger and depression, the pop-psych books tell us, are two sides of the same coin: depression is anger suppressed, anger is depression liberated. I meant what I said and I said what I meant. Whether we bring our enemies to justice or bring justice to our enemies, justice will be done.
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It is such clearly identifiable Rhetorical Functions as these, coupled with the relative ease of rhetorical-scheme detection, that make Rhetorical Figures so promising for computational tasks in which comprehension is central, like Argument Mining and text summarization. Again, however, there are challenges. They are not as thorny as the challenges of most tropes because they concern formal surfaces, not semantic depths.
But they exist. In particular, figures rarely come in isolation. Take an example like Plymouth Rock landed on us. But often the combinatorics of Rhetorical Figures work the other way; in such cases, which are frequent, they reinforce and constrain each other in predictable ways.
In some combinations of Rhetorical Figures these effects lead to clearer, even monovalent Rhetorical Functions; often, they aggregate into robust nuggets that offer particularly rich rewards for Argument Mining. When this happens — in figural collocations — the functions of two or more figures work in concert to narrow the range of meaning. Thirdly, it instances mesodiplosis clause-medial repetition; here, can do occurs between the relevant terms of both clauses. Figural collocations present a technical challenge that has not been met, but which strikes us as quite soluble, and they present rich opportunities.
The challenge is to detect multiple overlapping figures; so far, researchers have only detected individual figures. The opportunities arise because Rhetorical Functions are often enhanced and stabilized under the combinatorics of collocation; some collocations are much more common than others, because of their cognitive similarities and functional implications. When two or more figures combine in certain recurrent collocations, the functions they convey tend to be highly consistent.
Collocations, that is, often lead to functional conspiracies. For instance, when antimetabole collocates with mesodiplosis and antithesis, the combined function is primarily to reject the negated predication utterly and replace it with the positive predication. Reject—Replace We see inescapably now, too, that mesodiplosis is central to the Rhetorical Functions of 4, 5, and 7— The precise way in which figural bundles and grammatical features like transitivity or copular predication constrain meaning remains to be explored, but they work closely together in at least some cases, to enact quite specific Rhetorical Functions.
As one last example of Rhetorical Figure combinatorics, sticking with the same set of figures and features, consider what happens when antithesis collocates with antimetabole in its Reciprocal Specification function. We get the very specific Subclassification function, as in Examples 19 and 20, which say, respectively, that ultrabooks are a class of laptop, and compounds are a class of molecules:.
Subclassification Ultrabooks are laptops after all, but not all laptops are ultrabooks. All compounds are molecules since compounds consist of two or more atoms , but not all molecules are compounds since some molecules contain only atoms of the same element. We do not pretend to have a full and complete mapping of form to function, nor a chart of Rhetorical Figure combinatorics. This work is still in the very early stages, but these examples show that it holds considerable promise, and we believe ML corpus studies can be extremely helpful, especially for figural collocation.
Figural collocation, as we come to understand the functional combinatorics better, holds perhaps the greatest promise of Rhetorical Figures for computational understanding of natural language. Our paradigm example 1 , a collocation of the schemes antimetabole and mesodiplosis with the trope antithesis provides a pitch-perfect example of the Rhetorical Function, Reject—Replace. We can, and should, rely on rhetoricians to guide us in the functions of certain figures and certain figure-bundles, at least in these early stages.
But the rhetorical tradition is haphazard at best, and too frequently conflictual. The terminology alone is forbidding, not just because of its Greek and Latin roots but because of its historical inconsistency. As much as Computational Argumentation studies can benefit from a better understanding of Rhetorical Figures, Rhetorical Figure theories can benefit from computational studies of form and meaning. And, yes, that sentence was an antimetabole, bundled with mesodiplosis; the Rhetorical Function is Reciprocal Force, modulated by the possibility-modality of can.
We can discover the proportionality of certain collocations observationally, both antithesis and mesodiplosis seem strongly to co-occur with antimetabole , and the correlation of the collocations with the Rhetorical Functions as sketched above, on the basis of limited and anecdotal research. At its best, this work can revolutionize Computational Argumentation studies and rhetoric in the way corpus linguistics revolutionized lexicography and generated ontologies like WordNet and FrameNet. Linguists have a role to play here as well.
We have seen that grammatical features such as transitivity and copularity interact with Rhetorical Figures to determine their Rhetorical Functions, but Grammatical Constructions also interact with Rhetorical Figures intriguingly [ 6 ]— For instance, the well-known chiastic Easier-to-take-the-A-out-of-B-than-the-B-out-of-A catchphrase clearly fits the criteria of Construction Grammarians [ 32 ]: It was much easier to take Kuhn out of Harvard than Harvard out of Kuhn.
It was found easier to take the evacuee out of the slum than to take the slum out of the evacuee.
After twenty-five years in the field. The change did not come easily for me. Some of the more common techniques are described in the next chapter. When you recognize these fallacies, you should question the credibility of the speaker and the legitimacy of the argument. If you use these when making your own arguments, be aware that they may undermine or even destroy your credibility. Choose an article from the links provided below.
Preview your chosen text, and then read through it, paying special attention to how the writer tries to establish an ethical appeal. When a writer establishes an effective pathetic appeal , she makes the audience care about what she is saying.