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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.04395 |
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| _version_ | 1866909677131923456 |
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| author | Gao, Yingqiang Winiger, Fabian Montjourides, Patrick Shaitarova, Anastassia Gu, Nianlong Peng-Keller, Simon Schneider, Gerold |
| author_facet | Gao, Yingqiang Winiger, Fabian Montjourides, Patrick Shaitarova, Anastassia Gu, Nianlong Peng-Keller, Simon Schneider, Gerold |
| contents | Religion and spirituality (R/S) are complex and highly domain-dependent concepts which have long confounded researchers and policymakers. Due to their context-specificity, R/S are difficult to operationalize in conventional archival search strategies, particularly when datasets are very large, poorly accessible, and marked by information noise. As a result, considerable time investments and specialist knowledge is often needed to extract actionable insights related to R/S from general archival sources, increasing reliance on published literature and manual desk reviews. To address this challenge, we present SpiritRAG, an interactive Question Answering (Q&A) system based on Retrieval-Augmented Generation (RAG). Built using 7,500 United Nations (UN) resolution documents related to R/S in the domains of health and education, SpiritRAG allows researchers and policymakers to conduct complex, context-sensitive database searches of very large datasets using an easily accessible, chat-based web interface. SpiritRAG is lightweight to deploy and leverages both UN documents and user provided documents as source material. A pilot test and evaluation with domain experts on 100 manually composed questions demonstrates the practical value and usefulness of SpiritRAG. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_04395 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SpiritRAG: A Q&A System for Religion and Spirituality in the United Nations Archive Gao, Yingqiang Winiger, Fabian Montjourides, Patrick Shaitarova, Anastassia Gu, Nianlong Peng-Keller, Simon Schneider, Gerold Computation and Language Artificial Intelligence Religion and spirituality (R/S) are complex and highly domain-dependent concepts which have long confounded researchers and policymakers. Due to their context-specificity, R/S are difficult to operationalize in conventional archival search strategies, particularly when datasets are very large, poorly accessible, and marked by information noise. As a result, considerable time investments and specialist knowledge is often needed to extract actionable insights related to R/S from general archival sources, increasing reliance on published literature and manual desk reviews. To address this challenge, we present SpiritRAG, an interactive Question Answering (Q&A) system based on Retrieval-Augmented Generation (RAG). Built using 7,500 United Nations (UN) resolution documents related to R/S in the domains of health and education, SpiritRAG allows researchers and policymakers to conduct complex, context-sensitive database searches of very large datasets using an easily accessible, chat-based web interface. SpiritRAG is lightweight to deploy and leverages both UN documents and user provided documents as source material. A pilot test and evaluation with domain experts on 100 manually composed questions demonstrates the practical value and usefulness of SpiritRAG. |
| title | SpiritRAG: A Q&A System for Religion and Spirituality in the United Nations Archive |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2507.04395 |