ALLabel combines diversity, similarity, and uncertainty sampling to pick the most useful texts for human annotation, reaching near-full-data NER accuracy with 5-10% of labels.
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ALLabel: Three-stage Active Learning for LLM-based Entity Recognition using Demonstration Retrieval
ALLabel combines diversity, similarity, and uncertainty sampling to pick the most useful texts for human annotation, reaching near-full-data NER accuracy with 5-10% of labels.