---
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}
}
```