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Data · dataset · 2022

MasakhaNER

Listed in Hugging Face Datasets

MasakhaNER is the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages.

Description

Named entities are phrases that contain the names of persons, organizations, locations, times and quantities. Example: [PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] .

MasakhaNER is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for ten African languages: - Amharic - Hausa - Igbo - Kinyarwanda - Luganda - Luo - Nigerian-Pidgin - Swahili - Wolof - Yoruba The train/validation/test sets are available for all the ten languages. For more details see arxiv.org/abs/2103.11811

Links

Where it is published

Documentation and papers

Catalogue records · 1

Topics

Stated by source
token classification
Provenance · 1 source records, 9 field assertions
SourceKeyLast seenRaw
Hugging Face Datasetsmasakhane/masakhaner13 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[task].hf_task:token-classificationsource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
license_textsource · Hugging Faceconnector:huggingface@1.0.0
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0