DiZiNER improves zero-shot NER by having multiple LLMs annotate texts and using a supervisor to refine instructions from their disagreements, reaching SOTA on 14 of 18 benchmarks with +8 F1 gains.
InProceedings of COLING 2016, the 26th international conference on compu- tational linguistics: Technical papers, pages 1169– 1179
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DiZiNER: Disagreement-guided Instruction Refinement via Pilot Annotation Simulation for Zero-shot Named Entity Recognition
DiZiNER improves zero-shot NER by having multiple LLMs annotate texts and using a supervisor to refine instructions from their disagreements, reaching SOTA on 14 of 18 benchmarks with +8 F1 gains.