---
license: mit
task_categories:
- text-classification
- question-answering
language:
- en
tags:
- system-one
- typed-decisions
- synthetic
- routing
size_categories:
- 10K<n<100K
pretty_name: systemone-lite-general
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
  - split: test_hard
    path: data/test_hard-*
  - split: all
    path: data/all-*
  - split: full
    path: data/full-*
dataset_info:
  features:
  - name: task
    dtype: string
  - name: state
    dtype: string
  - name: instructions
    dtype: string
  - name: criteria_keys
    list: string
  - name: criteria_values
    list: string
  - name: label_alias
    dtype: string
  - name: label_key
    dtype: string
  - name: meta
    dtype: string
  splits:
  - name: train
    num_bytes: 25088586
    num_examples: 32400
  - name: test
    num_bytes: 2793606
    num_examples: 3600
  - name: test_hard
    num_bytes: 4279035
    num_examples: 5400
  - name: full
    num_bytes: 27882192
    num_examples: 36000
  download_size: 16241205
  dataset_size: 60043419
---

# systemone-lite-general

Synthetic **System One–style** typed decision examples for
[`systemone-lite`](https://github.com/fritzprix/systemone-lite)
(local Jev-shaped `state + questions → probabilities` training).

**Not affiliated with TypeSafe AI / Jev.** Rule-based labels only.

## Splits

| Split | Rows |
|------|------|
| `train` | 16,200 |
| `test` | 1,800 |
| `all` | 18,000 |

## Gyms / tasks

- **TicketDungeon**: `ticket.route`, `ticket.needs_human`, `ticket.urgency`
- **ResourceAllocator**: `alloc.fund_next`, `alloc.can_fund_all`, `alloc.pressure`
- **DebateJudge**: `debate.winner`, `debate.enough_evidence`, `debate.confidence`

Noul/score are encoded as single-letter **choice** options (`criteria_keys` / `label_alias`)
for causal LM next-token SFT.

## Fields

| Field | Description |
|------|-------------|
| `task` | Task id |
| `state` | JSON string of application state |
| `instructions` | Question text |
| `criteria_keys` / `criteria_values` | Option aliases and descriptions |
| `label_alias` | Gold option letter (e.g. `A`) |
| `label_key` | Gold semantic key (e.g. `billing`) |
| `meta` | JSON string (gym, schema hints, …) |

## Load

```python
from datasets import load_dataset
import json

ds = load_dataset("dwidlee/systemone-lite-general")
row = ds["train"][0]
state = json.loads(row["state"])
criteria = dict(zip(row["criteria_keys"], row["criteria_values"]))
```

## Reproduce locally

```bash
git clone https://github.com/fritzprix/systemone-lite
cd systemone-lite
python scripts/build_general_distill.py --episodes 2000 --seed 0
```