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---
license: mit
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
splits:
- name: task1
num_bytes: 100788
num_examples: 250
- name: task2
num_bytes: 42363
num_examples: 250
- name: task3
num_bytes: 67642
num_examples: 250
- name: task4
num_bytes: 146014
num_examples: 250
- name: task5
num_bytes: 22327
num_examples: 100
- name: task6
num_bytes: 27509
num_examples: 100
download_size: 55342
dataset_size: 406643
configs:
- config_name: default
data_files:
- split: task1
path: data/task1-*
- split: task2
path: data/task2-*
- split: task3
path: data/task3-*
- split: task4
path: data/task4-*
- split: task5
path: data/task5-*
- split: task6
path: data/task6-*
---
# TutorQA Benchmark
This dataset is part of the benchmark introduced in the paper [Graphusion: Leveraging Large Language Models for
Scientific Knowledge Graph Fusion and Construction in NLP Education](https://arxiv.org/pdf/2407.10794v1). We also release more data in our [GitHub page](https://github.com/IreneZihuiLi/Graphusion/tree/main).
It contains 6 tasks designed for evaluating various aspects of reasoning, graph understanding, and language generation.
## Dataset Structure
Each task is a separate split:
- `task1`: Relation Judgment
- `task2`: Prerequisite Prediction
- `task3`: Path Searching
- `task4`: Subgraph Completion
- `task5`: Clustering
- `task6`: Idea Hamster (no answers, open ended)
| Split | Fields |
|:-------|:----------------------------|
| task1 | `question`, `answer` |
| task2 | `question`, `answer` |
| task3 | `question`, `answer` |
| task4 | `question`, `answer` |
| task5 | `question`, `answer` |
| task6 | `question` |
## Usage Example
```python
from datasets import load_dataset
dataset = load_dataset("li-lab/tutorqa")
# Access individual tasks
task1 = dataset["task1"]
task6 = dataset["task6"]
```
## Citation
```bibtex
@inproceedings{yang2025graphusion,
title={Graphusion: A RAG Framework for Knowledge Graph Construction with a Global Perspective},
author={Yang, Rui and Yang, Boming and Feng, Aosong and Ouyang, Sixun and Blum, Moritz and She, Tianwei and Jiang, Yuang and Lecue, Freddy and Lu, Jinghui and Li, Irene},
booktitle={Proceedings of the NLP4KGC Workshop at The Web Conference 2025 (WWW'25)},
year={2025},
url={https://arxiv.org/abs/2410.17600}
}
|