Datasets:
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license: cc-by-4.0
task_categories:
- text-generation
language:
- zh
size_categories:
- n<1K
tags:
- chinese
- math-word-problems
- true-false
- mathematical-reasoning
modalities:
- text
libraries:
- Datasets
---
## Introduction
MathToF is a Chinese mathematical reasoning dataset introduced in the paper **Teaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language Models.**
It contains **1,000 Chinese true-or-false math problems**, each annotated with a **binary label (True/False)** and a **detailed rationale**.
## Dataset Structure
### Data Fields
- `qtype`: question type. In MathToF, this is typically `"JUDGE"`.
- `quest_stem`: the main question content.
- `quest_stem.text`: the problem statement in Chinese.
- `quest_ref`: reference answers and explanations.
- `quest_ref.texts`: the ground-truth label(s), typically `"True"` or `"False"`.
- `quest_ref.analyses`: the explanation(s), stored as a list.
### Example
```json
{
"qtype": "JUDGE",
"quest_stem": {
"text": "三位数减三位数差一定是三位数。"
},
"quest_ref": {
"texts": [
"False"
],
"analyses": [
"如两个三位数分别为:150,100。则150-100=50,其差50是两位数,故题干描述错误。"
]
}
}
```
### Dataset Statistics
According to the paper, the question-type distribution of MathToF is:
- Arithmetic: 675
- Algebra: 61
- Geometry: 197
- Statistics: 37
- Reasoning: 13
- Others: 17
Total: 1,000 questions.
## Citation
If you use this dataset, please cite the following paper:
```
@inproceedings{tan-etal-2025-teaching,
title = {Teaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language Models},
author = {Tan, Wenting and Chen, Dongxiao and Xue, Jieting and Wang, Zihao and Chen, Taijie},
booktitle = {Proceedings of the 31st International Conference on Computational Linguistics: Industry Track},
pages = {827--839},
year = {2025},
publisher = {Association for Computational Linguistics}
}
``` |