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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.

Description from NLP Progress

Papers

Showing 1–10 of 13 papers

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