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Uzbek news corpus for named entity recognition.

We have presented a corpus of Uzbek news articles containing manually annotated named entities. The corpus comprises 500 articles (222,536 tokens) and three entity classes (person, location, organization) sourced from Qalampir, an online news source in Uzbekistan. This corpus can be used for develop...

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Publicado en:Language Resources & Evaluation Vol. 59; no. 3; pp. 3139 - 3153
Autores principales: Yusufu, Aizihaierjiang, Aziz, Kamran, Yusufu, Aizierguli, Ainiwaer, Abidan, Li, Fei, Ji, Donghong
Formato: Artículo
Publicado: Springer Nature Sep2025
Materias:
Natural language processing
Corpora
Turkic languages
Data mining
Uzbekistan
Acceso en línea:Ver este registro en EBSCOhost
Sumario:We have presented a corpus of Uzbek news articles containing manually annotated named entities. The corpus comprises 500 articles (222,536 tokens) and three entity classes (person, location, organization) sourced from Qalampir, an online news source in Uzbekistan. This corpus can be used for develop and evaluate natural language processing (NLP) models for Uzbek. We conducted a baseline experiment on the qalampir corpus using pre-trained models. The results showed that the pre-trained model CINO outperformed other multilingual models.