Bilingual Rhetorical Structure Parsing with Large Parallel Annotations
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arXiv
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866929512044822528 |
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| author | Chistova, Elena |
| author_facet | Chistova, Elena |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_14969 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Bilingual Rhetorical Structure Parsing with Large Parallel Annotations Chistova, Elena Computation and Language 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. |
| title | Bilingual Rhetorical Structure Parsing with Large Parallel Annotations |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2409.14969 |