---
license: mit
language:
- ja
- en
tags:
- mathematics
- synthetic
- japanese
- retrieval
task_categories:
- question-answering
pretty_name: LongBook Math 1M (JA synthetic)
size_categories:
- 100K<n<1M
---

# LongBook Math 1M (Japanese synthetic mathematics dataset)

1,000,000 deterministic synthetic Japanese mathematics documents for retrieval evaluation
and generic-model RAG, built for [LongBook](https://github.com/Summer110622/LongBook).

- Format: JSONL, one document per line: `{id, namespace, text, metadata{domain, difficulty, lang, kind, index}}`
- `id` = `math-{domain}-{index:07d}`, unique and sortable.
- `text` structure (Japanese): 【分野】/【問題 id】/【解法】/【答え】/【キーワード】/【確認】
- Answers are **computed in Python by the generator, not hallucinated**.
- 8 domains × 3 difficulties: `arithmetic / algebra / calculus / linear_algebra / probability / geometry / number_theory / logic_sets`
- Generator: `dataset/build_math_dataset.py` (`--seed 42`), FTS5 ingest via `dataset/bulk_ingest_math_dataset.py`.
- Reading guide for sub-agents: `dataset/MATH_SUBAGENT.md` (model-agnostic, default `Qwen/Qwen3.5-9B`).

## Usage (datasets)

```python
from datasets import load_dataset
ds = load_dataset("summerMC/LongBook-math-1M", split="train", data_files="math-*.jsonl")
print(ds[0])
```

## Usage (LongBook retrieval)

```bash
python3 dataset/ingest_math_dataset.py --input <downloaded dir> --namespace math --db ./data/longbook.sqlite3
curl http://127.0.0.1:30000/v1/longbook/search \
  -H 'Content-Type: application/json' \
  -d '{"query":"二次方程式 因数分解","namespace":"math","top_k":5}'
```