LLMs for Ground Truth in Multilingual Historical NLP

This research explores a novel application of Large Language Models (LLMs) to generate ground truth data for historical Natural Language Processing (NLP) tasks across multiple languages. The paper's contribution lies in potentially accelerating historical text analysis and improving the accuracy of related NLP models.

• •LLMs are used to create ground truth data.
• •The research focuses on multilingual historical NLP.
• •Potentially improves accuracy of NLP models.