metadata
configs:
- config_name: all
description: All puzzle types combined.
data_files:
- split: train
path: puzzle_all_train.jsonl
- split: test
path: puzzle_all_test.jsonl
- config_name: dots
description: Puzzles primarily featuring the dot mechanic.
data_files:
- split: train
path: puzzle_dots_train.jsonl
- split: test
path: puzzle_dots_test.jsonl
- config_name: dots_stars_polys
description: Puzzles combining dots, stars, and polyominoes.
data_files:
- split: train
path: puzzle_dots_stars_polys_train.jsonl
- split: test
path: puzzle_dots_stars_polys_test.jsonl
- config_name: gaps
description: Puzzles primarily featuring the line gap mechanic.
data_files:
- split: train
path: puzzle_gaps_train.jsonl
- split: test
path: puzzle_gaps_test.jsonl
- config_name: gaps_dots_triangles
description: Puzzles combining gaps, dots, and triangles.
data_files:
- split: train
path: puzzle_gaps_dots_triangles_train.jsonl
- split: test
path: puzzle_gaps_dots_triangles_test.jsonl
- config_name: polys
description: Puzzles primarily featuring polyomino shapes.
data_files:
- split: train
path: puzzle_polys_train.jsonl
- split: test
path: puzzle_polys_test.jsonl
- config_name: polys_ylops
description: Puzzles featuring polyomino shapes (reversed color logic - 'ylop').
data_files:
- split: train
path: puzzle_polys_ylops_train.jsonl
- split: test
path: puzzle_polys_ylops_test.jsonl
- config_name: stars
description: Puzzles primarily featuring the star mechanic.
data_files:
- split: train
path: puzzle_stars_train.jsonl
- split: test
path: puzzle_stars_test.jsonl
- config_name: stones
description: Puzzles primarily featuring the stone (separation) mechanic.
data_files:
- split: train
path: puzzle_stones_train.jsonl
- split: test
path: puzzle_stones_test.jsonl
- config_name: stones_stars
description: Puzzles combining stones and stars.
data_files:
- split: train
path: puzzle_stones_stars_train.jsonl
- split: test
path: puzzle_stones_stars_test.jsonl
- config_name: triangles
description: Puzzles primarily featuring the triangle mechanic.
data_files:
- split: train
path: puzzle_triangles_train.jsonl
- split: test
path: puzzle_triangles_test.jsonl
size_categories:
- 1K<n<10K
SPaRC Dataset
A grid-based puzzle dataset for benchmarking LLMs spatial reasoning capabilities.
Data Schema
Each record (JSON) includes:
id(string): unique puzzle identifierdifficulty_level(int) &difficulty_score(float)grid_size:{ "height": H, "width": W }polyshapes: JSON string mapping shape IDs to binary gridspuzzle_array: 2D array with cell codes (e.g.,S,E,+,P-O-112)solution_count(int) andsolutionslist (withindex,path,pathLength)text_visualization: YAML-style summary
Sample Entry
{
"id": "10e68dc3a6fbfcdf",
"difficulty_level": 3,
"difficulty_score": 2.3261,
"grid_size": {"height":3,"width":4},
"polyshapes":"{\"112\":[[0,1,...]]}",
"puzzle_array":[
["+","+","+","E"],
["+","P-O-112","+","o-O"],
["S","N","+","G"]
],
"solution_count": 10,
"solutions": [ { "index":0, "pathLength":34, ... } ],
"text_visualization": "..."
}
Citation Information
If you use the dataset in any way, please cite the following paper. Preprint: https://arxiv.org/abs/2505.16686
@article{kaesberg2025sparc,
title={SPaRC: A Spatial Pathfinding Reasoning Challenge},
author={Kaesberg, Lars Benedikt and Wahle, Jan Philip and Ruas, Terry and Gipp, Bela},
journal={arXiv preprint arXiv:2505.16686},
year={2025}
}