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Low Resource Named Entity Recognition

Low resource named entity recognition is the task of using data and models available for one language for which ample such resources are available (e.g., English) to solve named entity recognition tasks in another, commonly more low-resource, language.

Papers

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Showing 11–20 of 38 papers

TitleStatusHype
Distant Supervision and Noisy Label Learning for Low Resource Named Entity Recognition: A Study on Hausa and Yorùbá—0
Dual Adversarial Neural Transfer for Low-Resource Named Entity Recognition—0
A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity Recognition—0
AUC Maximization for Low-Resource Named Entity Recognition—0
AutoTriggER: Label-Efficient and Robust Named Entity Recognition with Auxiliary Trigger Extraction—0
AutoTriggER: Named Entity Recognition with Auxiliary Trigger Extraction—0
Converse Attention Knowledge Transfer for Low-Resource Named Entity Recognition—0
Bayesian Modeling of Lexical Resources for Low-Resource Settings—0
Building Low-Resource NER Models Using Non-Speaker Annotation—0
Low-resource named entity recognition via multi-source projection: Not quite there yet?—0
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