SOURCE-LINKED INTELLIGENCE

AI-Assisted Pattern Detection for the Analysis of Medieval Poetic Translations

CORDIS · observation · Publication date unknown

kup – 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

Read original source ↗ Open in workspace

recordType

award

status

SIGNED

region

EU

value

267418.56

unit

EUR