A Danish Chatbot for Kaj Munk: Experiences in Developing a Chatbot for the Study of Kaj Munk’s Ordet

This study presents a pilot project developing a chatbot that is capable of conversing regarding Kaj Munk’s drama Ordet (The Word) within a Danish cultural framework. Building on the argument for a dedicated Danish language foundation model, the project explores both linguistic and cultural challenges in generating accurate and idiomatic Danish responses. Three systems based on LLaMA2 (with and without Danish fine-tuning) and LLaMA3 were compared through factual and interpretive dialogs with the play. By fine-tuning a Danish translation of the OASST2 dataset and applying retrieval-augmented generation (RAG) to the digital Kaj Munk archive, this study evaluates model performance based on correctness, fluency, and cultural adequacy. Results show significant improvements with RAG and fine-tuning yet persistent traces of English language structure and bias. Beyond linguistic accuracy, the analysis highlights the need for models trained on culturally grounded corpora that reflect Danish literary traditions shaped by authors such as Grundtvig and Munk. The findings illustrate both the potential and limitations of large language models as tools for literary interpretation and for sustaining national cultural identity in AI-mediated dialogs. Received: 14 January 2025 | Revised: 3 September 2025 | Accepted: 22 October 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The data that support the findings of this study are openly available in Figshare at http:doi.org/10.6084/m9.figshare.30250096. Author Contribution Statement David Jakobsen: Conceptualization, Methodology, Validation, Formal analysis, Resources, Writing – original draft, Writing – review & editing, Supervision, Project administration, Funding acquisition. Simon K. Pacis: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft. Sara F. Jalk: Validation, Formal analysis, Investigation, Data curation. Peter Øhrstrøm: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft.

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Journal
Artificial Intelligence and Applications
Published
2025-11-13
DOI
https://doi.org/10.47852/bonviewaia52025212
Primary Topic
AI in Service Interactions
Type
article
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0.00
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article

A Danish Chatbot for Kaj Munk: Experiences in Developing a Chatbot for the Study of Kaj Munk’s Ordet

Peter Øhrstrøm, Simon K. Pacis, David Jakobsen, Sara F. Jalk
Artificial Intelligence and Applications
AI in Service Interactions
article

A Danish Chatbot for Kaj Munk: Experiences in Developing a Chatbot for the Study of Kaj Munk’s Ordet

Peter Øhrstrøm, Simon K. Pacis, David Jakobsen, Sara F. Jalk
article en

Abstract

This study presents a pilot project developing a chatbot that is capable of conversing regarding Kaj Munk’s drama Ordet (The Word) within a Danish cultural framework. Building on the argument for a dedicated Danish language foundation model, the project explores both linguistic and cultural challenges in generating accurate and idiomatic Danish responses. Three systems based on LLaMA2 (with and without Danish fine-tuning) and LLaMA3 were compared through factual and interpretive dialogs with the play. By fine-tuning a Danish translation of the OASST2 dataset and applying retrieval-augmented generation (RAG) to the digital Kaj Munk archive, this study evaluates model performance based on correctness, fluency, and cultural adequacy. Results show significant improvements with RAG and fine-tuning yet persistent traces of English language structure and bias. Beyond linguistic accuracy, the analysis highlights the need for models trained on culturally grounded corpora that reflect Danish literary traditions shaped by authors such as Grundtvig and Munk. The findings illustrate both the potential and limitations of large language models as tools for literary interpretation and for sustaining national cultural identity in AI-mediated dialogs. Received: 14 January 2025 | Revised: 3 September 2025 | Accepted: 22 October 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The data that support the findings of this study are openly available in Figshare at http:doi.org/10.6084/m9.figshare.30250096. Author Contribution Statement David Jakobsen: Conceptualization, Methodology, Validation, Formal analysis, Resources, Writing – original draft, Writing – review & editing, Supervision, Project administration, Funding acquisition. Simon K. Pacis: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft. Sara F. Jalk: Validation, Formal analysis, Investigation, Data curation. Peter Øhrstrøm: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft.

Artificial Intelligence and Applications
Aalborg University (DK)
Quality Education
Openalex Percentile: Top 19%
AI in Service Interactions
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