README.md

---
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

```python
{
  '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!)

```python
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

```python
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

```python
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:

```bibtex
@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.