YoNER: A New Yorùbá Multi-domain Named Entity Recognition Dataset
Named Entity Recognition (NER) is a foundational NLP task, yet research in Yorùbá has been constrained by limited and domain-specific resources. Existing resources, such as MasakhaNER (a manually annotated news-domain corpus) and WikiAnn (automatically created from Wikipedia), are valuable but restricted in domain coverage. To address this gap, we present YoNER, a new multidomain Yorùbá NER dataset that extends entity coverage beyond news and Wikipedia. The dataset comprises about 5,000 sentences and 100,000 tokens collected from five domains including Bible, Blogs, Movies, Radio broadcast and Wikipedia, and annotated with three entity types: Person (PER), Organization (ORG) and Location ...
| Authors | Peace Busola Falola, Jesujoba O. Alabi, Solomon O. Akinola et al. |
|---|---|
| Primary category | cs.CL |
| Published | 7 April 2026 |
| Last updated at source | 7 April 2026 |
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