MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition
MasakhaNER 2.0 introduces the largest human-annotated named entity recognition dataset for 20 African languages and studies Africa-centric cross-lingual transfer learning. The paper reports that choosing the best transfer language improves zero-shot F1 by an average of 14 points across the 20 languages compared with transferring from English.
- Category
- Research
- Pricing
- Free / open
- Country
- 🌍 Pan-African
- Last verified
- 10 Oct 2026
{ "name": "MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition", "slug": "masakhaner-20-africa-centric-transfer-learning-for-named-entity-recognition", "category": "RESEARCH", "country": "Pan-African", "docs_status": "LIVE", "licensing_required": "NONE", "verified": false, "last_verified": "2026-10-10", "website": "https://arxiv.org/abs/2210.12391", "documentation_url": null}Verification history
- 10 Oct 2026 · live
- 7 Oct 2026 · live
- 4 Oct 2026 · live
- 1 Oct 2026 · live
- 28 Sept 2026 · live
- 25 Sept 2026 · live
- 22 Sept 2026 · live
- 22 Sept 2026 · live
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