eRST: A Signaled Graph Theory of Discourse Relations and Organization

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.

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Publication Details

Journal
Computational Linguistics
Published
2024-09-19
DOI
https://doi.org/10.1162/coli_a_00538
Citations
3
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
1.04
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article

eRST: A Signaled Graph Theory of Discourse Relations and Organization

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3 citations
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Semantic Web and Ontologies
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article

eRST: A Signaled Graph Theory of Discourse Relations and Organization

Tatsuya Aoyama, Siyao Peng, Yang Janet Liu, Luke Gessler, Debopam Das, Amir Zeldes
article en
3 citations

Abstract

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.

Computational LinguisticsVol. 51(1)
Butler University (US), Åbo Akademi University (FI), Georgetown University (US), LMU Klinikum (DE), Indiana University Bloomington (US), Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 19%
Semantic Web and Ontologies
1.04
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