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Making an Under-Resourced Language Available on the Wikidata Knowledge Graph: Quechua Language

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Information Management and Big Data (SIMBig 2024)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2496))

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Abstract

Knowledge Graphs (KGs) encode human knowledge in a structured format that can be used by Artificial Intelligence (AI) applications, such as Large Language Models, and Natural Language Processing. However, KGs are mainly built by harvesting the web data, which may over-represent certain viewpoints and languages, while Under-Resourced Language (URL) communities are not considered. As a result, AI applications may inherit these over-representation biases. Therefore, we research the holistic lifecycle of KGs to make the Quechua URL available as a KG. Specifically, we ingest Quechua lexical data into the Wikidata KG, then we explore Wikidata’s capabilities for a community-drive approach. Finally, we managed to add 1591 Quechua lexemes, their senses, forms, and pronunciation audio into Wikidata. Our approach demonstrates the feasibility and potential impact of bringing a URL into a KG, which can benefit a future where AI and its applications takes into account the languages and viewpoints of all.

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Notes

  1. 1.

    https://blog.google/products/search/introducing-knowledge-graph-things-not.

  2. 2.

    https://learn.microsoft.com/en-gb/graph/overview.

  3. 3.

    https://www.ethnologue.com.

  4. 4.

    https://wikidata.org.

  5. 5.

    https://qichwa.wikibase.cloud/.

  6. 6.

    https://developer.amazon.com/en-US/docs/alexa/custom-skills/develop-skills-in-multiple-languages.html.

  7. 7.

    https://support.google.com/googlenest/answer/7550584.

  8. 8.

    https://www.go-fair.org/fair-principles/.

  9. 9.

    https://linguistic-lod.org/.

  10. 10.

    https://www.ethnologue.com/language/que/.

  11. 11.

    https://glottolog.org/resource/languoid/id/quec1387.

  12. 12.

    https://iso639-3.sil.org/code/qxp.

  13. 13.

    https://wikipedia.org.

  14. 14.

    https://wikiba.se/.

  15. 15.

    https://runasimi.de.

  16. 16.

    https://www.wikidata.org/wiki/Wikidata:Lexicographical_data.

  17. 17.

    We define localization as the process of adapting or updating methods or tools for users or communities who speak other languages and have other needs.

  18. 18.

    https://qichwa.wikibase.cloud/.

  19. 19.

    https://www.wikibase.cloud/.

  20. 20.

    https://vrandezo.github.io/TheSurroundingOcean/?lid=L1322601.

  21. 21.

    https://www.wikidata.org/wiki/Wikidata:Tools/Lexicographical_data/en.

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Acknowledgments

We would like to thank: Maximilian Kristen (WikiMuc) and Hugo Lopez (LinguaLibre) for their technical support. Moreover, the research leading to these results has been supported by the Wikimedia Foundation (grant 22450106) and WikiTongues (grant 2024).

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Authors and Affiliations

  1. University of Innsbruck, Innsbruck, Austria

    Elwin Huaman

  2. National University of Altiplano Puno, Puno, Peru

    Wendi Huaman & Jorge Luis Huaman

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  1. Elwin Huaman
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  2. Wendi Huaman
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  3. Jorge Luis Huaman
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Correspondence to Elwin Huaman.

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Editors and Affiliations

  1. National Institutes of Health (NIH), Bethesda, MD, USA

    Juan Antonio Lossio-Ventura

  2. Eastern New Mexico University, Portales, NM, USA

    Eduardo Ceh-Varela

  3. Universidad Peruana de Ciencias Aplicadas, Lima, Peru

    Eduardo Díaz

  4. Pontificia Universidad Católica del Perú, Lima, Peru

    Freddy Paz Espinoza

  5. Mines ParisTech, Paris, France

    Claude Tadonki

  6. De Vinci Higher Education - De Vinci Research Center, Paris, France

    Hugo Alatrista-Salas

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Huaman, E., Huaman, W., Huaman, J.L. (2025). Making an Under-Resourced Language Available on the Wikidata Knowledge Graph: Quechua Language. In: Lossio-Ventura, J.A., Ceh-Varela, E., Díaz, E., Paz Espinoza, F., Tadonki, C., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2024. Communications in Computer and Information Science, vol 2496. Springer, Cham. https://doi.org/10.1007/978-3-031-91428-7_15

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