metadata

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. We also release more data in our GitHub page. 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

from datasets import load_dataset

dataset = load_dataset("li-lab/tutorqa")

# Access individual tasks
task1 = dataset["task1"]
task6 = dataset["task6"]

Citation

@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}
}