Negation Scope Resolution
4 papers with code • 4 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Negation Scope Resolution
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Libraries
Use these libraries to find Negation Scope Resolution models and implementations
The BioScope Corpus
Latest papers with no code
No means ‘No’; a non-im-proper modeling approach, with embedded speculative context
Through this paper, we investigate various bio model’s embeddings(BioBERT, BioE- LECTRA, PubMedBERT) on their understanding of "negation and speculation context" wherein we found that these models were unable to differentiate "negated context" vs "non-negated context".
The Case of Imperfect Negation Cues: A Two-Step Approach for Automatic Negation Scope Resolution
Neural network-based methods are the state of the art in negation scope resolution.
Scope resolution of predicted negation cues: A two-step neural network-based approach
We advocate for more research into the application of deep learning on negation detection and the effect of imperfect information on scope resolution.
Negation typology and general representation models for cross-lingual zero-shot negation scope resolution in Russian, French, and Spanish.
Negation is a linguistic universal that poses difficulties for cognitive and computational processing.
Orthogonal Attention: A Cloze-Style Approach to Negation Scope Resolution
Negation Scope Resolution is an extensively researched problem, which is used to locate the words affected by a negation cue in a sentence.
