Despite the dynamic nature of language, current AI/human interaction is limited by a relatively narrow set of training data. This project develops artificial intelligence tools to identify grammatical structures, word meanings, and references to people and places in historical texts, making these materials accessible to scholars across disciplines. This project will create the largest annotated historical English corpus ever assembled, transforming how researchers study language change and early modern culture. By annotating 1.5 billion words of English texts with detailed linguistic information, this work enables discoveries about how English evolved into its modern form and provides novel insights into the dynamics of social networks, ideas, and cultural movements. The resulting resource will be integrated into EarlyPrint, an existing website for exploring these texts, which will provide students and researchers worldwide with powerful new tools for exploring the language, history, and culture of the English language. These resources will also be of great interest to artificial intelligence researchers working on language technology, who will use the corpus to train new and better models that can handle a wide variety of language and to compare performance of systems in open competitions. This project addresses a critical limitation in historical linguistics and digital humanities: the small size of existing annotated historical corpora limits the types and complexity o