MasakhaNER:Named Entity Recognition for African Languages

, Masakhane (2021) MasakhaNER:Named Entity Recognition for African Languages. Transactions of the Association for Computational Linguistics, 9. pp. 1116-1131. ISSN 2307-387X

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Abstract

We take a step towards addressing the under- representation 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 state- of-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

Item Type:
Journal Article
Journal or Publication Title:
Transactions of the Association for Computational Linguistics
ID Code:
161023
Deposited By:
Deposited On:
18 Oct 2021 14:40
Refereed?:
Yes
Published?:
Published
Last Modified:
19 Nov 2021 12:03