Datasets:
language:
- luo
- bxk
- lri
- rag
license: cc-by-4.0
task_categories:
- token-classification
tags:
- kenyan-languages
- dholuo
- lubukusu
- lumarachi
- lulogooli
- pos-tagging
- low-resource-languages
- african-languages
pretty_name: KenPOS
size_categories:
- 100K<n<1M
configs:
- config_name: dho
data_files: dho/*.parquet
- config_name: lbk
data_files: lbk/*.parquet
- config_name: lch
data_files: lch/*.parquet
- config_name: llg
data_files: llg/*.parquet
KenPOS: Kenyan Languages Part-of-Speech Tagged Dataset
Dataset Description
KenPOS is a part-of-speech (POS) tagged corpus for Kenyan languages, featuring 156,994 tokens across four languages. The dataset provides manually annotated POS tags for low-resource Kenyan languages, enabling NLP research and applications.
Dataset Statistics
| Language | Code | Tokens | Sentences | Files | Unique POS Tags |
|---|---|---|---|---|---|
| Dholuo | dho | 54,712 | 70 | 168 | 114 |
| Lubukusu | lbk | 51,900 | 154 | 62 | 97 |
| Lumarachi | lch | 25,917 | 27 | 212 | 78 |
| Lulogooli | llg | 24,465 | 290 | 121 | 75 |
| Total | 156,994 | 541 | 563 |
Languages & Codes
| Language / Dialect | Code | Family / Notes |
|---|---|---|
| Dholuo (Luo) | dho | Nilotic (western Kenya) |
| Lubukusu (Bukusu) | lbk | Bantu, Luhya dialect |
| Lumarachi (Marachi) | lch | Bantu, Luhya dialect |
| Lulogooli (Logooli) | llg | Bantu, Luhya dialect |
Dataset Format
The dataset is distributed as Parquet files for optimal performance and compatibility:
- Format: Apache Parquet (columnar storage)
- Encoding: UTF-8
- File naming:
{language}/train.parquet - Compatibility: Works with
datasets4.0.0+ without custom loading scripts
Data Fields
Each record in the dataset contains:
- token:
string- The word or token - pos_tag:
string- Part-of-speech tag (e.g., NN, V, ADJ, PUNCT) - sentence_id:
int- Unique identifier for the sentence - position:
int- Position of the token within the sentence (0-indexed) - filename:
string- Source filename from which the token was extracted
Example Record
{
'token': 'Kezia',
'pos_tag': 'NN',
'sentence_id': 0,
'position': 0,
'filename': '4411_dho_pos.csv'
}
Usage
Loading with 🤗 Datasets
Compatible with datasets 4.0.0+ (No trust_remote_code needed!)
from datasets import load_dataset
# Load Dholuo POS dataset
dho = load_dataset("Kencorpus/KenPOS", "dho")
# Load Lubukusu POS dataset
lbk = load_dataset("Kencorpus/KenPOS", "lbk")
# Load Lumarachi POS dataset
lch = load_dataset("Kencorpus/KenPOS", "lch")
# Load Lulogooli POS dataset
llg = load_dataset("Kencorpus/KenPOS", "llg")
# Access the data
print(dho['train'][0])
# Output: {'token': 'Kezia', 'pos_tag': 'NN', 'sentence_id': 0, 'position': 0, 'filename': '4411_dho_pos.csv'}
Reconstructing Sentences
from datasets import load_dataset
import pandas as pd
# Load dataset
dho = load_dataset("Kencorpus/KenPOS", "dho")
df = pd.DataFrame(dho['train'])
# Get first sentence
sentence_0 = df[df['sentence_id'] == 0].sort_values('position')
print(' '.join(sentence_0['token'].tolist()))
Analyzing POS Tags
from datasets import load_dataset
import pandas as pd
# Load dataset
dho = load_dataset("Kencorpus/KenPOS", "dho")
df = pd.DataFrame(dho['train'])
# Count POS tag frequencies
pos_counts = df['pos_tag'].value_counts()
print(pos_counts.head(10))
POS Tag Categories
The dataset uses a variety of POS tags including:
- NN - Noun
- V - Verb
- ADJ/Adj. - Adjective
- ADV/Adv - Adverb
- PRON - Pronoun
- ADP - Adposition (preposition/postposition)
- DET/Det. - Determiner
- CONJ/Conj. - Conjunction
- NUM - Numeral
- PUNCT/PUNC - Punctuation
- And many more fine-grained categories
Note: Tag naming conventions may vary slightly across files (e.g., PUNCT vs PUNC, ADJ vs Adj.).
Dataset Curators
- Florence Indede (Maseno University)
- Owen McOnyango (Maseno University)
- Lilian D.A. Wanzare (Maseno University)
- Barack Wanjawa (University of Nairobi)
- Edward Ombui (Africa Nazarene University)
- Lawrence Muchemi (University of Nairobi)
Citation
If you use this dataset in your research, please cite:
@article{wanjawa2022kencorpus,
title={Kencorpus: A Kenyan Language Corpus of Swahili, Dholuo and Luhya for Natural Language Processing Tasks},
author={Wanjawa, Barack W. and Wanzare, Lilian D. and Indede, Florence and McOnyango, Owen and Ombui, Edward and Muchemi, Lawrence},
journal={arXiv preprint arXiv:2208.12081},
year={2022}
}
Links
- Research Paper: https://arxiv.org/abs/2208.12081
- Dataverse: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/KLCKL5
- ResearchGate: https://www.researchgate.net/publication/371767223
- Semantic Scholar: https://www.semanticscholar.org/paper/8cf70c5cd8b195ed7a399ea2cdc0b0e8f08c61ce
License
This dataset is licensed under CC-BY-4.0.
Acknowledgments
This dataset is part of the Kencorpus project, which aims to create NLP resources for low-resource Kenyan languages.