Browse State-of-the-Art › DRS Parsing
DRS Parsing
6 papers with code · 2 benchmarks · 0 datasets archive 2025-07-28
Discourse Representation Structures (DRS) are formal meaning representations introduced by Discourse Representation Theory. DRS parsing is a complex task, comprising other NLP tasks, such as semantic role labeling, word sense disambiguation, co-reference resolution and named entity tagging. Also, DRSs show explicit scope for certain operators, which allows for a more principled and linguistically motivated treatment of negation, modals and quantification, as has been advocated in formal semantics. Moreover, DRSs can be translated to formal logic, which allows for automatic forms of inference by third parties.
Description from NLP Progress
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| PMB-2.2.0 (6 rows) | Bi-LSTM seq2seq: BERT + characters in 1 encoder | Character-level Representations Improve DRS-based Semantic Parsing... | code | — | Compare |
| PMB-3.0.0 (3 rows) | Bi-LSTM seq2seq: BERT + characters in 1 encoder | Character-level Representations Improve DRS-based Semantic Parsing... | code | — | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
No dataset record in the archive lists this task.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
6 shown of 6 papers with code (13 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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9 Nov 2020 2 repositories listedWe combine character-level and contextual language model representations to improve performance on Discourse Representation Structure parsing.
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3 Jun 2024 1 repository listedThe experiments conducted on the standard benchmarks demonstrate that models trained using the cross-lingual training method exhibit significant improvements in DRS clause and graph parsing in English, German, Italian…
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31 May 2023 1 repository listedPre-trained language models (PLMs) have achieved great success in NLP and have recently been used for tasks in computational semantics.
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1 Aug 2021 1 repository listedText-level discourse rhetorical structure (DRS) parsing is known to be challenging due to the notorious lack of training data.
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6 May 2020 1 repository listedDue to its great importance in deep natural language understanding and various down-stream applications, text-level parsing of discourse rhetorical structure (DRS) has been drawing more and more attention in recent…
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30 Oct 2018 1 repository listedNeural methods have had several recent successes in semantic parsing, though they have yet to face the challenge of producing meaning representations based on formal semantics.
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