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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.
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