Bilingual Rhetorical Structure Parsing with Large Parallel Annotations
<|reference_start|>Bilingual Rhetorical Structure Parsing with Large Parallel Annotations: 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.<|reference_end|>
@article{chistova2024bilingual,
    title={Bilingual Rhetorical Structure Parsing with Large Parallel Annotations},
    author={Elena Chistova},
    journal={Findings of the Association for Computational Linguistics ACL 2024},
    year={2024},
    doi={10.18653/v1/2024.findings-acl.577},
    archivePrefix={arXiv},
    eprint={2409.14969},
    primaryClass={cs.CL}
}