Comparer des méthodes

	Analyse rhétorique de la structure du discours	Extraction d'arguments
Domaine	Fouille de textes	Fouille de textes
Famille	Process / pipeline	Process / pipeline
Année d'origine	1988 (RST); 2008 (PDTB 2.0)	2016
Auteur d'origine	Mann & Thompson (RST); Prasad et al. (PDTB)	Lippi & Torroni (state-of-the-art survey)
Type	NLP discourse-structure analysis task	NLP information-extraction task
Source fondatrice	Mann, W. C. & Thompson, S. A. (1988). Rhetorical Structure Theory: Toward a functional theory of text organization. Text, 8(3), 243-281.	Lippi, M. & Torroni, P. (2016). Argumentation Mining: State of the Art and Emerging Trends. ACM Transactions on Internet Technology, 16(2), Article 10, 1-25.
Alias	rhetorical structure analysis, RST parsing, PDTB parsing, Söylem Ayrıştırma (Discourse Parsing)	argumentation mining, argument extraction, Argüman Madenciliği
Apparentées	3	4
Résumé	Discourse parsing is a natural-language-processing task that models the rhetorical relations between sentences and paragraphs of a text — relations such as cause, contrast, and elaboration — and represents them as a tree structure. It works within established frameworks, principally Rhetorical Structure Theory (RST), introduced by Mann and Thompson in 1988, and the Penn Discourse TreeBank (PDTB), released by Prasad and colleagues in 2008.	Argument mining is a natural-language-processing task that automatically detects claims, premises and the argumentative structures that link them within text. Consolidated as a field by Lippi and Torroni's 2016 state-of-the-art survey, it is applied to scientific writing, legal documents and debate analysis to turn free-form argumentation into structured, analysable units.