Named Entity Recognition for Confidential and Military Texts in the Uzbek Language
Keywords:
Named Entity Recognition, Uzbek NLP, Military Text Processing, Information SecurityAbstract
This thesis presents a specialized Named Entity Recognition (NER) system for identifying sensitive entities in Uzbek confidential and military texts. By fine-tuning the bertbek-ner-uznews transformer model with domain-specific synthetic data, we achieved an F1-score of 89.6% across seven custom entity categories. The system addresses critical gaps in Uzbek NLP for security applications and provides a foundation for Data Loss Prevention (DLP) integration.
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References
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