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Found 5 papers, 2 papers with code
OCHADAI at SMM4H-2021 Task 5: Classifying self-reporting tweets on potential cases of COVID-19 by ensembling pre-trained language models
Since the outbreak of coronavirus at the end of 2019, there have been numerous studies on coro- navirus in the NLP arena.
Bipartite Flat-Graph Network for Nested Named Entity Recognition
In this paper, we propose a novel bipartite flat-graph network (BiFlaG) for nested named entity recognition (NER), which contains two subgraph modules: a flat NER module for outermost entities and a graph module for all the entities located in inner layers.
Ranked #6 on
Nested Mention Recognition
on ACE 2005
Hierarchical Contextualized Representation for Named Entity Recognition
In this paper, we address these two deficiencies and propose a model augmented with hierarchical contextualized representation: sentence-level representation and document-level representation.
Ranked #13 on
Named Entity Recognition (NER)
on Ontonotes v5 (English)
(using extra training data)
Open Named Entity Modeling from Embedding Distribution
For monolingual cases, the proposed named entity model gives an open description of diverse named entity types and different languages.
Named Entity Recognition Only from Word Embeddings
Deep neural network models have helped named entity (NE) recognition achieve amazing performance without handcrafting features.
