GFNER: A Unified Global Feature-Aware Framework for Flat and Nested Named Entity Recognition

GFNER: A Unified Global Feature-Aware Framework for Flat and Nested Named Entity Recognition

Named Entity Recognition (NER) poses challenges for both flat and nested tasks, which require different paradigms. To overcome this issue, we present GFNER, a unified global feature-aware framework based on table filling, that can handle both types of tasks with low computational cost. While pretrai...

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Bibliographic Details
Main Authors: Jiayin Chen, Xi Chen, Shuai Pan, Wei Zhang
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Nested named entity recognition
unified framework
table filling module
global feature learning module
Online Access:https://ieeexplore.ieee.org/document/10141588/

Internet

https://ieeexplore.ieee.org/document/10141588/

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