datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
masakhaner2MasakhaNER 2.0 is the largest publicly available high-quality dataset for named entity recognition (NER) in 20 African languages.
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 20 African languages:
- Bambara (bam)
- Ghomala (bbj)
- Ewe (ewe)
- Fon (fon)
- Hausa (hau)
- Igbo (ibo)
- Kinyarwanda (kin)
- Luganda (lug)
- Dholuo (luo)
- Mossi (mos)
- Chichewa (nya)
- Nigerian Pidgin
- chShona (sna)
- Kiswahili (swą)
- Setswana (tsn)
- Twi (twi)
- Wolof (wol)
- isiXhosa (xho)
- Yorùbá (yor)
- isiZulu (zul)
The train/validation/test sets are available for all the ten languages.
For more details see https://arxiv.org/abs/2103.11811masakhaner-x-parquetmasakhaner2
MasakhaNER2
...
annotations_creators:
expert-generated
language:
bm
bbj
ee
fon
ha
ig
rw
lg
luo
mos
ny
pcm
sn
sw
tn
tw
wo
xh
yo
zu
language_creators:
expert-generated
license:
afl-3.0
multilinguality:
multilingual
pretty_name: masakhaner2.0
size_categories:
1K<n<10K
source_datasets:
original
tags:
ner
masakhaner
masakhane
task_categories:
token-classification
task_ids:
named-entity-recognition
Dataset Card for [Dataset Name]
Dataset Summary… See the full description on the dataset page: https://huggingface.co/datasets/Vibrant8849/masakhaner2.masakhaner