---
tags:
- low-resource-language
pretty_name: Sinhala Perplexity Test Dataset
size_categories:
- n<1K
configs:
- config_name: default
  data_files:
  - split: data
    path: data/data-*
dataset_info:
  features:
  - name: sinhala_unicode
    dtype: string
  - name: sinhala_romanized
    dtype: string
  splits:
  - name: data
    num_bytes: 24794
    num_examples: 200
  download_size: 14779
  dataset_size: 24794
language:
- si
---
# Sinhala Perplexity Test Dataset

## Dataset Description

This dataset contains 500 sentence pairs in Sinhala, provided in two scripts: Unicode Sinhala and Romanized Sinhala. It is intended for evaluating perplexity and benchmarking language models on Sinhala text.

This dataset was introduced and used in the following benchmark study:

> Rajapakse, M., & Weerasinghe, R. (2025). *Script Sensitivity: Benchmarking Language Models on Unicode, Romanized and Mixed-Script Sinhala*. arXiv:2601.14958v2. https://arxiv.org/abs/2601.14958v2

If you use this dataset, please cite the above paper.

## Citation
```bibtex
@article{rajapakse2026comprehensive,
  title={A Comprehensive Benchmark of Language Models on Unicode and Romanized Sinhala},
  author={Rajapakse, Minuri and Weerasinghe, Ruvan},
  journal={arXiv preprint arXiv:2601.14958},
  year={2026}
}
```
## Dataset Structure

The dataset consists of two fields:

- `sinhala_unicode`: Sinhala sentences written in Unicode Sinhala script.
- `sinhala_romanized`: Corresponding sentences transliterated into Romanized Sinhala.

Each entry in the dataset corresponds to one pair of sentences.

## How to Use the Dataset

You can easily load the dataset using the `datasets` library:

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Minuri/sinhala-perplexity-test-dataset")

# Access the first example
example = dataset['data'][0]
print("Unicode Sentence:", example['sinhala_unicode'])
print("Romanized Sentence:", example['sinhala_romanized'])