README.md

metadata

license: mit
task_categories:
  - question-answering
  - text-classification
  - text-retrieval
language:
  - en
tags:
  - academic
  - questions
  - evidence
  - papers
size_categories:
  - 1K<n<10K

ELAIPBench Dataset

Description

This dataset contains academic questions with evidence passages extracted from research papers. Each question is paired with a relevant passage from the source paper that provides evidence for answering the question.It was officially adopted as the dataset for the CCKS 2025 Academic Paper Question Answering Challenge.

Dataset Structure

The dataset contains 403 questions with the following fields:

• question_type: Type of question (SA-MCQ, MA-MCQ, etc.)
• question: The question text
• answer: The correct answer
• relevant_passage: Evidence passage extracted from the paper
• paper_content: Full content of the source paper

Usage

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("KangKang625/ELAIPBench")

# Access the data
data = dataset['test']
print(f"Number of questions: {len(data)}")
print(f"First question: {data[0]['question']}")
print(f"Paper content length: {len(data[0]['paper_content'])}")

Citation

If you use this dataset, please cite the original ELAIPBench paper.

License

MIT License