---
license: apache-2.0
language:
  - en
  - lg
tags:
  - translation
  - parallel-corpus
  - low-resource
  - gemma
  - fine-tuning
size_categories:
  - 10K<n<100K
---

# English-Luganda Parallel Corpus for Translation

## Dataset Description
This dataset contains parallel sentences in English (en) and Luganda (lg), designed primarily for training and fine-tuning machine translation models. The data consists of sentence pairs extracted from a source document.

## Languages
*   **English (en)**
*   **Luganda (lg)** - ISO 639-1 code: lg

## Data Format
The dataset is provided in a format compatible with the Hugging Face `datasets` library. Each entry consists of a dictionary with the following keys:

*   `english`: (string) The sentence in English.
*   `luganda`: (string) The corresponding translation in Luganda.

Example:

```json
{
  "english": "Farmers should be encouraged to grow more coffee.",
  "luganda": "Abalimi balina okukubirizibwa okwongera okulima emmwanyi"
}
```

## Data Splits
The dataset contains a single split:

`train`: Contains all the extracted parallel sentences.

## Dataset Creation
The data was extracted from an Excel file containing two columns: one for English sentences and one for Luganda sentences. A Python script using pandas was used to read the Excel file and process the rows.

## Extraction Statistics:
- Total rows read from source Excel file: 25006
- Valid sentence pairs extracted: 25006
- Rows skipped (due to missing data or empty strings): 0
- All 25,006 valid pairs form the train split of this dataset.

## How to Use
You can load the dataset using the Hugging Face datasets library:

```python
from datasets import load_dataset

dataset_name = "kambale/luganda-english-parallel-corpus"
dataset = load_dataset(dataset_name)

# Access the training split
train_dataset = dataset['train']

# Print the first example
print(train_dataset[0])
# Expected Output:
# {'english': 'Some English sentence...', 'luganda': 'Some Luganda sentence...'}
```

## Licensing
The license for this dataset is Apache-2.0. Please ensure your use case complies with the license terms. The original source data from which this dataset was derived may have its own licensing conditions.

## Citation
If you use this dataset in your research, please consider citing it.
```bibtex
@misc{wesley_kambale_2025,
	author       = {Wesley Kambale},
	title        = {English-Luganda Parallel Corpus for Translation},
	year         = 2025,
	url          = {https://huggingface.co/datasets/kambale/luganda-english-parallel-corpus},
	doi          = {10.57967/hf/5246},
	publisher    = {Hugging Face}
}
```