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Main Authors: Zeldes, Amir, Aoyama, Tatsuya, Liu, Yang Janet, Peng, Siyao, Das, Debopam, Gessler, Luke
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2403.13560
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author Zeldes, Amir
Aoyama, Tatsuya
Liu, Yang Janet
Peng, Siyao
Das, Debopam
Gessler, Luke
author_facet Zeldes, Amir
Aoyama, Tatsuya
Liu, Yang Janet
Peng, Siyao
Das, Debopam
Gessler, Luke
contents 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 (SDRT), the Penn Discourse Treebank (PDTB) 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.
format Preprint
id arxiv_https___arxiv_org_abs_2403_13560
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle eRST: A Signaled Graph Theory of Discourse Relations and Organization
Zeldes, Amir
Aoyama, Tatsuya
Liu, Yang Janet
Peng, Siyao
Das, Debopam
Gessler, Luke
Computation and Language
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 (SDRT), the Penn Discourse Treebank (PDTB) 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.
title eRST: A Signaled Graph Theory of Discourse Relations and Organization
topic Computation and Language
url https://arxiv.org/abs/2403.13560