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The rapid proliferation of information in the digital era underscores theimportance of accurate historical representation and interpretation. Whileartificial intelligence has shown promise in various fields, its potential forhistorical fact-checking and gap-filling remains largely untapped. This studyevaluates the performance of three large language models LLMs GPT 3.5, GPT 4,and GoogleBARD in the context of predicting and verifying historical eventsbased on given data. A novel metric, Distance to Reality (DTR), is introducedto assess the models' outputs against established historical facts. The resultsreveal a substantial potential for AI in historical studies, with GPT 4demonstrating superior performance. This paper underscores the need for furtherresearch into AI's role in enriching our understanding of the past and bridginghistorical knowledge gaps.

Bridging History with AI A Comparative Evaluation of GPT 3.5, GPT4, and GoogleBARD in Predictive Accuracy and Fact Checking