Digitale Geschichte und Historiographie

This article addresses the question of evaluating generative AI prompts designed for specific tasks such as linguistic linked open data modelling and refining of word embedding results.

This article proposes a linguistic linked open data model for diachronic analysis (LLODIA) that combines data derived from diachronic analysis of multilingual corpora with dictionary-based evidence.

This article proposes a small-scale investigation on the use of generative AI agents for post-OCR correction in historical datasets.

How can “transmedia” history be put into practice from both theoretical and empirical perspectives? The international conference “Transmedia History”—organised by the Impresso project and the University of Lausanne’s History Department—will gather scholars from various backgrounds around this question to exchange views on new prospects opened by digitisation and digital tools to carry out transmedia research.

LLODIA is a linguistic linked open data model for diachronic analysis.

Lecture by Dr. Inna Kizhner, C²DH visiting fellow in March-April 2024.

Can large language models (LLMs) and artificial intelligence (AI) unlock the secrets hidden within historical documents, such as showpeople periodicals? This question propelled researchers from the universities of Antwerp, Luxembourg, and Marburg to explore the potential of LLM/AI in a one-day workshop.