KenPOS / README.md
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metadata
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 datasets 4.0.0+ 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


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.