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Journal Articles Transactions of the Association for Computational Linguistics Year : 2021

MasakhaNER: Named entity recognition for African languages

Stephen Mayhew
  • Function : Author
Catherine Gitau
  • Function : Author
Derguene Mbaye
  • Function : Author
Davis David
  • Function : Author
Samba Ngom
  • Function : Author
Paul Rayson
  • Function : Author
Mofetoluwa Adeyemi
  • Function : Author
Emmanuel Anebi
  • Function : Author
Samuel Oyerinde
  • Function : Author
Clemencia Siro
  • Function : Author
Temilola Oloyede
  • Function : Author
Yvonne Wambui
  • Function : Author
Victor Akinode
  • Function : Author
Mouhamadane Mboup
  • Function : Author
Henok Tilaye
  • Function : Author
Kelechi Nwaike
  • Function : Author
Degaga Wolde
  • Function : Author
Abdoulaye Faye
  • Function : Author
Ibrahima Thierno
  • Function : Author
Abdoulaye Diallo
  • Function : Author
Tendai Marengereke
  • Function : Author

Abstract

We take a step towards addressing the underrepresentation of the African continent in NLP research by bringing together different stakeholders to create the first large, publicly available, high-quality dataset for named entity recognition (NER) in ten African languages. We detail the characteristics of these languages to help researchers and practitioners better understand the challenges they pose for NER tasks. We analyze our datasets and conduct an extensive empirical evaluation of stateof-the-art methods across both supervised and transfer learning settings. Finally, we release the data, code, and models to inspire future research on African NLP. 1
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Dates and versions

hal-03350962 , version 1 (21-09-2021)

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David Ifeoluwa Adelani, Jade Abbott, Graham Neubig, Daniel d'Souza, Julia Kreutzer, et al.. MasakhaNER: Named entity recognition for African languages. Transactions of the Association for Computational Linguistics, 2021, ⟨10.1162/tacl⟩. ⟨hal-03350962⟩
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