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Can Large Language Models Revolutionalize Open Government Data Portals? A Case of Using ChatGPT in statistics.gov.scot

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Listed:
  • Mamalis, Marios
  • Kalampokis, Evangelos
  • Karamanou, Areti
  • Brimos, Petros
  • Tarabanis, Konstantinos

Abstract

Large language models possess tremendous natural language understanding and generation abilities. However, they often lack the ability to discern between fact and fiction, leading to factually incorrect responses. Open Government Data are repositories of, often times linked, information that is freely available to everyone. By combining these two technologies in a proof of concept designed application utilizing the GPT3.5 OpenAI model and the Scottish open statistics portal, we show that not only is it possible to augment the large language model's factuality of responses, but also propose a novel way to effectively access and retrieve statistical information from the data portal just through natural language querying. We anticipate that this paper will trigger a discussion regarding the transformation of Open Government Portals through large language models.

Suggested Citation

  • Mamalis, Marios & Kalampokis, Evangelos & Karamanou, Areti & Brimos, Petros & Tarabanis, Konstantinos, 2023. "Can Large Language Models Revolutionalize Open Government Data Portals? A Case of Using ChatGPT in statistics.gov.scot," OSF Preprints 9b35z, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:9b35z
    DOI: 10.31219/osf.io/9b35z
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    References listed on IDEAS

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    1. Shijie Wu & Ozan Irsoy & Steven Lu & Vadim Dabravolski & Mark Dredze & Sebastian Gehrmann & Prabhanjan Kambadur & David Rosenberg & Gideon Mann, 2023. "BloombergGPT: A Large Language Model for Finance," Papers 2303.17564, arXiv.org, revised Dec 2023.
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