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Large Language Model for Querying Databases in Portuguese

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Progress in Artificial Intelligence (EPIA 2024)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14969))

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Abstract

This study introduces a system that helps non-expert users find information easily without knowing database languages or asking technicians for help. A specific domain is explored, focusing on a subscrip- tion-based sports facility, which serves as an open-source version of a real case study. Utilizing the star schema, the available data in the database is structured to provide accessibility through Portuguese Natural Language queries. Using a Large Language Model (LLM), SQL queries are generated based on the question and the provided star schema. We created a dataset with 115 highly challenging questions drawn from real-world usage scenarios to validate the correctness of the system. Challenges found during testing, like attribute value interpretation, out-of-scope questions, and temporal interval adequacy issues, highlight the insufficiency of the star schema alone in providing the needed context for generating accurate SQL queries by the LLM. Addressing these challenges through enhanced contextual information shows significant improvement in query correctness, with validation results increasing from 57.76% to 88.79%. This study shows the potential and limitations of LLMs in generating SQL queries from Portuguese Natural Language queries.

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Notes

  1. 1.

    https://platform.openai.com/docs/api-reference/chat/create.

  2. 2.

    https://platform.openai.com/docs/api-reference/chat/create.

  3. 3.

    Additional commented illustrative examples and the full set of questions are available at https://bit.ly/4bJ3cbs.

  4. 4.

    https://platform.openai.com/docs/models/continuous-model-upgrades.

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Author information

Authors and Affiliations

  1. Universidade Nova de Lisboa, FCT, Costa da Caparica, Portugal

    Lourenço Figueiredo & Nuno Marques

  2. CEDIS, Sintra, Portugal

    Paulo Pinheiro

  3. Universidade Aberta and Lasige, FCUL, Lisbon, Portugal

    Luís Cavique

  4. NOVA LINCS, NOVA School of Science and Technology, Costa da Caparica, Portugal

    Nuno Marques

Authors
  1. Lourenço Figueiredo
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  2. Paulo Pinheiro
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  3. Luís Cavique
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  4. Nuno Marques
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Corresponding author

Correspondence to Lourenço Figueiredo .

Editor information

Editors and Affiliations

  1. University of Minho, Braga, Portugal

    Manuel Filipe Santos

  2. University of Minho, Braga, Portugal

    José Machado

  3. University of Minho, Braga, Portugal

    Paulo Novais

  4. University of Minho, Braga, Portugal

    Paulo Cortez

  5. Polytechnic Institute of Viana do Castelo, Viana do Castelo, Portugal

    Pedro Miguel Moreira

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Figueiredo, L., Pinheiro, P., Cavique, L., Marques, N. (2025). Large Language Model for Querying Databases in Portuguese. In: Santos, M.F., Machado, J., Novais, P., Cortez, P., Moreira, P.M. (eds) Progress in Artificial Intelligence. EPIA 2024. Lecture Notes in Computer Science(), vol 14969. Springer, Cham. https://doi.org/10.1007/978-3-031-73503-5_1

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  • DOI: https://doi.org/10.1007/978-3-031-73503-5_1

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