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<p>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.</p>

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Multilingual approaches to extractive question answering in political texts

  • 期刊论文

  • 发表日期：

    2025年10月30日

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  • Sultan Alsarra,
  • Mubarak Alrashoud,
  • Javier Osorio,
  • Vito D’Orazio,
  • Latifur Khan,
  • Patrick T. Brandt

摘要

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.