Project description
Bridging AI-assisted analysis with mediaeval philology to study Germanic poetry
Computational research in the study of early Germanic literature is limited, largely due to the scarcity of annotated corpora and the complexities involved in creating them. Supported by the Marie Skłodowska-Curie Actions programme, the ADAPT project aims to bridge this gap by developing AI-driven methods for analysing translations of mediaeval Germanic poetry. Leveraging the capacity of large language models for recognising philological patterns, it will create a replicable methodology for AI-assisted textual analysis, reducing the need for advanced programming skills. It will then apply the methodology to translations of Latin poetry into Old Norse to investigate how mediaeval translators reinterpreted Latin sources within the Norse poetic system.
Objective
Despite the rapid advances and accessibility of digital technologies, computational research remains strikingly underdeveloped in the study of early Germanic cultural heritage – especially poetry. This is not due to a lack of interest or material, but to structural obstacles: annotated corpora are scarce, and building them is both time-consuming and undervalued in a field where publication pressure is high. On top of this, the technical complexity of digital methods – which involves, for example, learning Python-programming or XML-TEI markup – deters many scholars, discouraging the integration of computational approaches into mainstream philological research.
ADAPT addresses this bottleneck by harnessing AI technology – in particular large language models (LLMs). At their core, LLMs excel at identifying patterns, a capacity that mirrors a central task in philological inquiry: tracing correspondences and recurring features. On this basis, ADAPT will develop the first replicable workflow for AI-assisted textual analysis on pre-modern sources, drastically lowering the technical threshold for computational analysis and enabling scalable, rigorous exploration of historical texts without requiring advanced programming skills.
This workflow will then be tested on the only poetic translations from Latin into Old Norse to investigate how medieval translators retextualised Latin sources within the Norse poetic system. These unique case studies offer an exceptional opportunity to trace strategies of literary adaptation and cultural negotiation across traditions.
Hosted at the University of Bergen, with secondments at Ljubljana (AI4DH) and UC Berkeley, ADAPT combines philology, translation studies, and digital humanities. The project will promote the responsible integration of AI in the humanities, generating methodological innovation and insights into medieval translation practices, and providing a transferable model for future research on historical textual traditions.
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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(opens in new window) HORIZON-MSCA-2025-PF
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5020 Bergen
Norway
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