Language technology / named entity recognitionAfrican language technologyParticipation documented

MasakhaNER

Nairobi, Kenya

Repository states dataset annotation was performed by volunteers from the Masakhane community using participatory research design.

decolonizationparticipatory researchinclusive designdata collectionlabelingmodel trainingevaluation

Overview

Participation documentation

Participation mode: volunteer annotation + community co-creation
Participants: volunteer annotators; language experts; researchers
Methods: volunteer annotation; community coordination; open dataset building
AI lifecycle stages: data collection; labeling; model training; evaluation
Evidence summary: Repository states dataset annotation was performed by volunteers from the Masakhane community using participatory research design.
Atlas assessment: Core · High confidence · evidence grade A
Uncertainty: Public evidence indicates that stakeholders directly shaped AI design, data, deployment, evaluation, or oversight; residual uncertainty concerns the exact degree of shared decision power rather than project existence.