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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

Showing 11–20 of 38 papers

TitleStatusHype
Translation and Fusion Improves Zero-shot Cross-lingual Information ExtractionCode0
AUC Maximization for Low-Resource Named Entity Recognition—0
Prompt-based Text Entailment for Low-Resource Named Entity Recognition—0
SFE-AI at SemEval-2022 Task 11: Low-Resource Named Entity Recognition using Large Pre-trained Language Models—0
Using Domain Knowledge for Low Resource Named Entity Recognition—0
A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity Recognition—0
AutoTriggER: Named Entity Recognition with Auxiliary Trigger Extraction—0
Unsupervised Paraphrasing Consistency Training for Low Resource Named Entity Recognition—0
Low-Resource Named Entity Recognition Based on Multi-hop Dependency TriggerCode0
AutoTriggER: Label-Efficient and Robust Named Entity Recognition with Auxiliary Trigger Extraction—0
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