The paper introduces UES and NPE, a framework that treats unlabeled-entity and noisy-entity problems separately in distantly supervised NER, and reports average F1 gains over prior baselines.
Universalner: Targeted distillation from large language models for open named entity recognition,
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Towards DS-NER: Unveiling and Addressing Latent Noise in Distant Annotations
The paper introduces UES and NPE, a framework that treats unlabeled-entity and noisy-entity problems separately in distantly supervised NER, and reports average F1 gains over prior baselines.