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Multilingual approaches to extractive question answering in political texts

Author

Listed:
  • Sultan Alsarra

    (King Saud University, Department of Software Engineering, College of Computer and Information Sciences)

  • Mubarak Alrashoud

    (King Saud University, Department of Software Engineering, College of Computer and Information Sciences)

  • Javier Osorio

    (University of Arizona, School of Government and Public Policy)

  • Vito D’Orazio

    (West Virginia University, Department of Political Science)

  • Latifur Khan

    (University of Texas at Dallas, Department of Computer Science, Erik Jonsson School of Engineering and Computer Science)

  • Patrick T. Brandt

    (University of Texas at Dallas, School of Economic, Political and Policy Sciences)

Abstract

This work contributes to multilingual extractive question answering (QA) by presenting QA-specialized versions of ConfliBERT for English, Spanish, and Arabic, language models designed for analyzing political conflict and violence. A cross-lingual QA framework is proposed, including curated datasets and the Spanish translation of an English QA corpus to mitigate the scarcity of annotated resources for low-resource languages. The models are fine-tuned specifically for extractive QA and benchmarked against general-purpose BERT variants, showing consistent gains across all target languages. By addressing language gaps in high-stakes domains, the study underscores the potential of multilingual QA systems to support both research and decision-making in political contexts.

Suggested Citation

  • Sultan Alsarra & Mubarak Alrashoud & Javier Osorio & Vito D’Orazio & Latifur Khan & Patrick T. Brandt, 2025. "Multilingual approaches to extractive question answering in political texts," Computational and Mathematical Organization Theory, Springer, vol. 31(4), pages 299-322, December.
    • Handle: RePEc:spr:comaot:v:31:y:2025:i:4:d:10.1007_s10588-025-09408-2
    DOI: 10.1007/s10588-025-09408-2
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