Papers › Bilingual Rhetorical Structure Parsing with Large Parallel Annotations
Bilingual Rhetorical Structure Parsing with Large Parallel Annotations
Elena Chistova
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.
Code
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Tasks
Datasets
Introduced by this paper, per the archive.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Discourse Parsing | RST-DT | DMRST | Standard Parseval (Full) | 55.7 ± 0.3 | #5 of 40 | Archive leaderboard | report |
| Discourse Parsing | RST-DT | DMRST | Standard Parseval (Nuclearity) | 68.0 ± 0.6 | #5 of 40 | Archive leaderboard | report |
| Discourse Parsing | RST-DT | DMRST | Standard Parseval (Relation) | 57.3 ± 0.2 | #5 of 40 | Archive leaderboard | report |
| Discourse Parsing | RST-DT | DMRST | Standard Parseval (Span) | 78.7 ± 0.4 | #5 of 40 | Archive leaderboard | report |
| End-to-End RST Parsing | RST-DT | DMRST + ToNy + E-BiLSTM | Standard Parseval (Full) | 53.0 ± 0.7 | #1 of 4 | Archive leaderboard | report |
| End-to-End RST Parsing | RST-DT | DMRST + ToNy + E-BiLSTM | Standard Parseval (Nuclearity) | 64.5 ± 0.8 | #1 of 4 | Archive leaderboard | report |
| End-to-End RST Parsing | RST-DT | DMRST + ToNy + E-BiLSTM | Standard Parseval (Relation) | 54.5 ± 0.7 | #1 of 4 | Archive leaderboard | report |
| End-to-End RST Parsing | RST-DT | DMRST + ToNy + E-BiLSTM | Standard Parseval (Span) | 74.8 ± 0.5 | #1 of 4 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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