eRST: A Signaled Graph Theory of Discourse Relations and Organization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AC9PRDZAE" target="_blank" >RIV/00216208:11320/26:C9PRDZAE - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1162/coli_a_00538" target="_blank" >http://dx.doi.org/10.1162/coli_a_00538</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1162/coli_a_00538" target="_blank" >10.1162/coli_a_00538</a>

Jazyk výsledku

angličtina

Název v původním jazyce

eRST: A Signaled Graph Theory of Discourse Relations and Organization

Popis výsledku v původním jazyce

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. © 2024 Association for Computational Linguistics. Published under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.

Název v anglickém jazyce

eRST: A Signaled Graph Theory of Discourse Relations and Organization

Popis výsledku anglicky

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. © 2024 Association for Computational Linguistics. Published under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Computational Linguistics

ISSN

0891-2017

e-ISSN

—

Svazek periodika

51

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

50

Strana od-do

23-72

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-105010250227