AI RESEARCH
A Hybrid Method for Low-Resource Named Entity Recognition
arXiv CS.AI
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ArXi:2605.04489v1 Announce Type: cross Named Entity Recognition (NER) is a critical component of Natural Language Processing with diverse applications in information extraction and conversational AI. However, NER in specific domains for low-resource languages faces challenges such as limited annotated data and heterogeneous label sets. This study addresses these issues by proposing a hybrid neurosymbolic framework that integrates rule-based processing with deep learning models for Vietnamese