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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 26–38 of 38 papers

TitleStatusHype
Low-resource named entity recognition via multi-source projection: Not quite there yet?—0
Low-Resource Named Entity Recognition with Cross-Lingual, Character-Level Neural Conditional Random Fields—0
Using Domain Knowledge for Low Resource Named Entity Recognition—0
Prompt-based Text Entailment for Low-Resource Named Entity Recognition—0
RoPDA: Robust Prompt-based Data Augmentation for Low-Resource Named Entity Recognition—0
AutoTriggER: Label-Efficient and Robust Named Entity Recognition with Auxiliary Trigger Extraction—0
Bayesian Modeling of Lexical Resources for Low-Resource Settings—0
SFE-AI at SemEval-2022 Task 11: Low-Resource Named Entity Recognition using Large Pre-trained Language Models—0
AUC Maximization for Low-Resource Named Entity Recognition—0
Building Low-Resource NER Models Using Non-Speaker Annotation—0
Building Low-Resource NER Models Using Non-Speaker Annotations—0
Constrained Labeled Data Generation for Low-Resource Named Entity Recognition—0
A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity Recognition—0
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