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    <abstract>Discourse parsing is a crucial task in natural language processing that aims to reveal the higher-level relations in a text. Despite growing interest in cross-lingual discourse parsing, challenges persist due to limited parallel data and inconsistencies in the Rhetorical Structure Theory (RST) application across languages and corpora. To address this, we introduce a parallel Russian annotation for the large and diverse English GUM RST corpus. Leveraging recent advances, our end-to-end RST parser achieves state-of-the-art results on both English and Russian corpora. It demonstrates effectiveness in both monolingual and bilingual settings, successfully transferring even with limited second-language annotation. To the best of our knowledge, this work is the first to evaluate the potential of cross-lingual end-to-end RST parsing on a manually annotated parallel corpus.</abstract>
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%0 Conference Proceedings
%T Bilingual Rhetorical Structure Parsing with Large Parallel Annotations
%A Chistova, Elena
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Findings of the Association for Computational Linguistics: ACL 2024
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F chistova-2024-bilingual
%X Discourse parsing is a crucial task in natural language processing that aims to reveal the higher-level relations in a text. Despite growing interest in cross-lingual discourse parsing, challenges persist due to limited parallel data and inconsistencies in the Rhetorical Structure Theory (RST) application across languages and corpora. To address this, we introduce a parallel Russian annotation for the large and diverse English GUM RST corpus. Leveraging recent advances, our end-to-end RST parser achieves state-of-the-art results on both English and Russian corpora. It demonstrates effectiveness in both monolingual and bilingual settings, successfully transferring even with limited second-language annotation. To the best of our knowledge, this work is the first to evaluate the potential of cross-lingual end-to-end RST parsing on a manually annotated parallel corpus.
%R 10.18653/v1/2024.findings-acl.577
%U https://aclanthology.org/2024.findings-acl.577/
%U https://doi.org/10.18653/v1/2024.findings-acl.577
%P 9689-9706

Markdown (Informal)

[Bilingual Rhetorical Structure Parsing with Large Parallel Annotations](https://aclanthology.org/2024.findings-acl.577/) (Chistova, Findings 2024)

• Bilingual Rhetorical Structure Parsing with Large Parallel Annotations (Chistova, Findings 2024)

ACL

• Elena Chistova. 2024. Bilingual Rhetorical Structure Parsing with Large Parallel Annotations. In Findings of the Association for Computational Linguistics: ACL 2024, pages 9689–9706, Bangkok, Thailand. Association for Computational Linguistics.