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---
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
```python
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:
```bibtex
@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
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