---
pretty_name: Indonesian ↔ Balinese ↔ Cirebonese Synthetic Corpus
license: mit
task_categories:
- text-classification
- text-generation
language:
- id
- ban
- jav
---

# Indonesian–Balinese–Cirebonese Synthetic Parallel Corpus

## Dataset Summary

This corpus is **fully synthetic** and targets two extremely low-resource languages:
- **Balinese** (ban)
- **Cirebonese** (often grouped under Javanese dialects)

Key facts:
- Seeded with 10k high-level topics generated by GPT-5.
- For each topic, gpt-oss-120b produced 30 subtopics and continued to generate 30
  question–answer pairs (≈9M Q&A pairs).
- Answers were translated into Balinese and Cirebonese by gpt-oss-120b while
  leveraging bilingual lexicons/dictionaries through prompting and in-context
  learning.
- The parallel corpus contains roughly **~1B tokens per low-resource language**
  (Balinese & Cirebonese) across all splits.

## Available Subsets

- `raw`: direct aggregation of every translated answer that passes structural
  validation (IDs and all three language fields present).
- `filtered_heuristic`: subset of `raw` that passes filtering based on heuristics
  including minimum length, repetition checks, and also GlotLID verification
  for Balinese and Cirebonese (cirebonese are referred to as "jav" in GlotLID).

## Citation

If you use this dataset (or derivatives), please cite:

```
@misc{scale-lowres-synth-2025,
  title        = {Scale Resources for Low-Resource Languages via Synthetic Data Generation},
  author       = {Faiz Ghifari Haznitrama and Najma Qalbi Dwiharani and Alice Oh},
  year         = {2025},
  howpublished = {\url{https://huggingface.co/datasets/haznitrama/idn-ban-cbn-synthetic}},
}
```

## Notes

- Dataset is synthetic; no human-written or human-translated text is included.
- Licensed under the permissive MIT terms to encourage downstream reuse.
- Please verify downstream safety/quality constraints that apply to your
  deployment scenario before production use.