eRST: A Signaled Graph Theory of Discourse Relations and Organization

Amir Zeldes*, Tatsuya Aoyama, Yang Janet Liu, Siyao Peng, Debopam Das, Luke Gessler

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

In this article we present Enhanced Rhetorical Structure Theory (eRST), a new theoretical framework for computational discourse analysis, based on an expansion of Rhetorical Structure Theory (RST). The framework encompasses discourse relation graphs with tree-breaking, non-projective and concurrent relations, as well as implicit and explicit signals which give explainable rationales to our analyses. We survey shortcomings of RST and other existing frameworks, such as Segmented Discourse Representation Theory, the Penn Discourse Treebank, and Discourse Dependencies, and address these using constructs in the proposed theory. We provide annotation, search, and visualization tools for data, and present and evaluate a freely available corpus of English annotated according to our framework, encompassing 12 spoken and written genres with over 200K tokens. Finally, we discuss automatic parsing, evaluation metrics, and applications for data in our framework.
Original languageEnglish
JournalComputational Linguistics
DOIs
Publication statusE-pub ahead of print - 15 Nov 2024
MoE publication typeA1 Journal article-refereed

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