Datasets:

YMinglai
/

GSM-DC-Dataset-Sample

license: mit
task_categories:
  - question-answering
  - text-generation
language:
  - en
tags:
  - math
  - reasoning
  - synthetic
size_categories:
  - 1K<n<10K

GSM-DC Test Dataset

This dataset contains the test set for GSM-DC (Grade School Math with Distractor Chains), a synthetic math reasoning dataset with controlled complexity.

Dataset Details

Total Problems: 6300
Operation Counts (OP): 16-22 (out-of-distribution test set)
Problem Types: Graph-based mathematical reasoning problems
Noise Levels: Light, Medium, Hard (distractor difficulty)

Dataset Structure

Each problem in all_problems.json contains:

problem_text: The problem statement with all variables and relationships
solution: Step-by-step ground truth solution
final_answer: The numerical answer
n_op: Number of operations (16-22)
noise_level: Distractor difficulty (light/medium/hard)
graph_structure: Internal graph representation
template_id: Problem template identifier

Usage

import json

# Load the dataset
with open('all_problems.json', 'r') as f:
    problems = json.load(f)

# Access a problem
problem = problems[0]
print(problem['problem_text'])
print(problem['solution'])
print(problem['final_answer'])

Citation

If you use this dataset, please cite:

@inproceedings{gsm-dc-2025,
    title={GSM-DC: Grade School Math with Distractor Chains},
    author={[Your Name]},
    booktitle={Proceedings of EMNLP 2025},
    year={2025}
}

Paper

Published at EMNLP 2025. [Paper Link]

License

MIT License