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    <titleInfo>
        <title>eRST: A Signaled Graph Theory of Discourse Relations and Organization</title>
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    <name type="personal">
        <namePart type="given">Amir</namePart>
        <namePart type="family">Zeldes</namePart>
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    <name type="personal">
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    <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.</abstract>
    <identifier type="citekey">zeldes-etal-2025-erst</identifier>
    <identifier type="doi">10.1162/coli_a_00538</identifier>
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        <date>2025-03</date>
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            <start>23</start>
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%0 Journal Article
%T eRST: A Signaled Graph Theory of Discourse Relations and Organization
%A Zeldes, Amir
%A Aoyama, Tatsuya
%A Liu, Yang Janet
%A Peng, Siyao
%A Das, Debopam
%A Gessler, Luke
%J Computational Linguistics
%D 2025
%8 March
%V 51
%N 1
%I MIT Press
%C Cambridge, MA
%F zeldes-etal-2025-erst
%X 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.
%R 10.1162/coli_a_00538
%U https://aclanthology.org/2025.cl-1.3/
%U https://doi.org/10.1162/coli_a_00538
%P 23-72

Markdown (Informal)

[eRST: A Signaled Graph Theory of Discourse Relations and Organization](https://aclanthology.org/2025.cl-1.3/) (Zeldes et al., CL 2025)

• eRST: A Signaled Graph Theory of Discourse Relations and Organization (Zeldes et al., CL 2025)

ACL

• Amir Zeldes, Tatsuya Aoyama, Yang Janet Liu, Siyao Peng, Debopam Das, and Luke Gessler. 2025. eRST: A Signaled Graph Theory of Discourse Relations and Organization. Computational Linguistics, 51(1):23–72.