---
license: mit
task_categories:
- question-answering
- multiple-choice
language:
- en
tags:
- decision-making
- calibration
- spatial-reasoning
- synthetic
- computed-ground-truth
size_categories:
- 1K<n<10K
configs:
- config_name: default
  data_files:
  - split: test
    path: test.jsonl
---

# spatial-decisions

7,305 multiple-choice decision questions over 6,525 distinct simulated states, in
15 families and two environments. **Every answer is computed from the simulator**, not
annotated by a person and not taken from a model. That is the point of the set: on a question whose
answer is derived from the rules of the environment, a disagreement is a mistake, and there is
nothing to argue about.

The set was built to replace a much narrower public artefact: a recording of 68 questions of a
single shape -- "can the agent step one cell north?" -- over 17 maze windows. That recording is
useful and tiny. This one keeps the computed-truth property and adds question types, environments,
renderings, option counts and answer types.

## What is in it

| field | meaning |
|---|---|
| `id` | stable identifier, `family-index` |
| `family` | which generator produced the item |
| `environment` | `maze` or `snake` |
| `state` | the rendered state shown to the system |
| `question` | the question text |
| `options` | the answer options, in canonical order |
| `answer_index` | index into `options` |
| `answer` | the option text itself |
| `answer_distribution` | the true distribution over `options`. One-hot for the deterministic families; for `stochastic` it is the probability the environment's transition rules define |
| `deterministic` | `false` only for `stochastic` |
| `seen_in_training` | whether a question of this shape appears in the authors' training mixture |
| `fingerprint` | sha256 over the rendered state, question and sorted options |

## Families

| family | env | n | options | majority label | question |
|---|---|---|---|---|---|
| `move_legal` | maze | 500 | 2 | 0.50 | Can the agent step one cell in a named direction? |
| `move_two_step` | maze | 500 | 2 | 0.50 | Are both steps of a two-move plan legal? |
| `open_count` | maze | 400 | 5 | 0.25 | How many of the four orthogonal neighbours are traversable? |
| `cell_kind` | maze | 498 | 3 | 0.33 | Is the agent on a dead end, a corridor, or a junction? |
| `only_way` | maze | 415 | 6 | 0.20 | Which single direction is open, if exactly one is? |
| `blocked_pair` | maze | 500 | 2 | 0.50 | Are two named directions both blocked? (a conjunction) |
| `onward` | maze | 500 | 2 | 0.50 | After a named move, is a further named move legal from the new cell? |
| `plan_survives` | maze | 500 | 4 | 0.25 | Does a three-step plan complete, and if not at which step does it fail? |
| `goal_bearing` | maze | 496 | 8 | 0.12 | In which of eight compass directions does the goal lie? |
| `reachable_within` | maze | 500 | 2 | 0.50 | Is the goal reachable within k moves? |
| `distance_band` | maze | 500 | 5 | 0.20 | Which band does the shortest-path distance fall in? |
| `first_move` | maze | 500 | 4 | 0.25 | Which single first move starts a shortest path? |
| `stochastic` | maze | 500 | 2 | 0.50 | Under a noisy actuator of stated reliability, will the executed move be safe? |
| `snake_safe` | snake | 500 | 2 | 0.50 | Does the snake survive the next move in a named direction? |
| `snake_food` | snake | 496 | 8 | 0.12 | In which of eight compass directions does the food lie? |

## Properties worth knowing before you use it

**Every family is exactly label-balanced by construction.** Items are bucketed by *answer* and the
same number is drawn from each bucket, so the majority-label column above equals one over the option
count in every row. A family whose rare answer is genuinely rare yields fewer questions rather than
being topped up from the common one. A constant answer scores chance, everywhere.

**One family has a real probability, not a label.** In `stochastic` the actuator executes the
intended move with probability rho and otherwise picks uniformly among the others, so the
probability that the executed move is safe follows from the transition rules. `answer_index` is a
single sampled outcome; `answer_distribution` is the analytic probability. Scoring accuracy against
the sample has a ceiling below 1 by construction; scoring distance to `answer_distribution` does
not, and is the more informative measurement.

**2,000 of 7,305 items are in families the authors' own models were trained on**, marked by
`seen_in_training`. Results should be reported for the two halves separately. A specialist model
beating a general one on a question shape it was trained for is a real product fact and a weak
scientific one; they are different claims and averaging them hides both.

**Contamination.** Every item was checked by fingerprint against the authors' training mixtures and
any verbatim match was discarded. The check is over the rendered state, question and option set.

## Limitations

- Synthetic. It measures spatial and procedural decision-making in two toy environments, and
  nothing about natural language, world knowledge or open-ended reasoning.
- The `maze` and `snake` simulators are small. A system that has seen a lot of grid puzzles may
  find the deterministic families easy; the `stochastic` family is the one that stays hard, because
  it asks for a number rather than a fact.
- The English is templated, with two or three phrasings per family. It is not a test of
  robustness to natural phrasing.

## Provenance and licence

The maze and snake simulators, and the noisy-actuator construction, derive from the open
[NanoJev](https://huggingface.co/C-Tianyu/NanoJev) project under the MIT licence; they are used as
published. The generators, the balancing, the contamination check and this dataset are released
under the MIT licence as well.