Layering Knowledge to Unpack the Layers of Meaning in Historical Texts
Year: 2025
Type: article
Abstract: Keynote given at Plate-Forme Intelligence Artificielle (PFIA 2025) - Conference Ingénerie des Connaissances / Journée Humanités Numeriques & IA on 4 July 2025. Title: Layering Knowledge to Unpack the Layers of Meaning in Historical Texts Abstract: Historical texts present computational analyses with many different challenges: digitisation artefacts, segmentation, language evolution, and changing societal values. In this talk, I will present various interdisciplinary projects that my team has worked and is working on that address these challenges. Our use cases range from government and company records, to literature, letters, newspapers, and cookbooks - all spanning centuries. The approaches we use depend on the best tool for the job: rules, machine learning, prompt engineering - but all informed by domain expertise leading to applications that are used by researchers and the general public to make sense of big historical data.
Author: van Erp, Marieke
Institution: KNAW Humanities Cluster
Language: English
Subfield: Literature and Literary Theory
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6949275249
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