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DRS Parsing

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.

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Papers

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Showing 1–13 of 13 papers

TitleStatusHype
MACT: Model-Agnostic Cross-Lingual Training for Discourse Representation Structure ParsingCode0
Pre-Trained Language-Meaning Models for Multilingual Parsing and GenerationCode0
DRS Parsing as Sequence Labeling—0
Adversarial Learning for Discourse Rhetorical Structure ParsingCode1
Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERTCode1
The First Shared Task on Discourse Representation Structure Parsing—0
A Top-Down Neural Architecture towards Text-Level Parsing of Discourse Rhetorical StructureCode1
Semantic Graph Parsing with Recurrent Neural Network DAG Grammars—0
Transition-based DRS Parsing Using Stack-LSTMs—0
Discourse Representation Structure Parsing with Recurrent Neural Networks and the Transformer Model—0
Linguistic Information in Neural Semantic Parsing with Multiple Encoders—0
Neural Boxer at the IWCS Shared Task on DRS Parsing—0
Exploring Neural Methods for Parsing Discourse Representation StructuresCode1
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