Update README.md

README.md

@@ -1,3 +1,39 @@
----
-license: mit
----
+---
+license: mit
+---
+# 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"]
+```