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This study presents a study on the development of a Yorùbá Bible dataset aimed at enhancing Named Entity Recognition (NER) for Yorùbá, a low-resource language. It outlines the process of manually extracting and annotating phrases from key books of the Bible. The emphasis is on the dataset’s importance for future NER and Natural Language Processing (NLP) applications, especially in supporting languages with limited resources. The study covers dataset creation, annotation guidelines, challenges encountered due to the language’s tonal nature, and future directions for expanding the dataset and developing a NER model tailored to the Bible domain, with broader implications for indigenous language processing and preservation.

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Curation and Annotation of an Indigenous Bible Corpus for Named Entity Recognition Model

  • 会议论文

  • 发表日期：

    2026年

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  • Peace Busola Falola,
  • Biswajit Brahma,
  • Solomon Olalekan Akinola

摘要

This study presents a study on the development of a Yorùbá Bible dataset aimed at enhancing Named Entity Recognition (NER) for Yorùbá, a low-resource language. It outlines the process of manually extracting and annotating phrases from key books of the Bible. The emphasis is on the dataset’s importance for future NER and Natural Language Processing (NLP) applications, especially in supporting languages with limited resources. The study covers dataset creation, annotation guidelines, challenges encountered due to the language’s tonal nature, and future directions for expanding the dataset and developing a NER model tailored to the Bible domain, with broader implications for indigenous language processing and preservation.