no code implementations • NAACL (SMM4H) 2021 • Ying Luo, Lis Pereira, Kobayashi Ichiro
Since the outbreak of coronavirus at the end of 2019, there have been numerous studies on coro- navirus in the NLP arena.
1 code implementation • ACL 2020 • Ying Luo, Hai Zhao
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
1 code implementation • 6 Nov 2019 • Ying Luo, Fengshun Xiao, Hai Zhao
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)
no code implementations • 31 Aug 2019 • Ying Luo, Hai Zhao, Zhuosheng Zhang, Bingjie Tang
For monolingual cases, the proposed named entity model gives an open description of diverse named entity types and different languages.
no code implementations • EMNLP 2020 • Ying Luo, Hai Zhao, Junlang Zhan
Deep neural network models have helped named entity (NE) recognition achieve amazing performance without handcrafting features.