BioASQ - All Question Types

A comprehensive collection of BioASQ challenge questions organized by question type as separate splits.

Purpose

This dataset is a convenience collection of BioASQ questions reformatted for easier use. The original source data is from the BioASQ Challenge. We created this reorganized version (with question types as splits) to facilitate evaluation in our PaperSearchQA work.

IMPORTANT: This is not the original BioASQ dataset. We have simply reorganized the BioASQ data into splits by question type. All underlying question and answer data is from BioASQ.

Dataset Description

This dataset contains 5,404 biomedical questions from the BioASQ challenge, distributed across four question types:

• factoid (1,609 samples): Questions with short factual answers
• yesno (1,464 samples): Yes/No questions
• summary (1,283 samples): Questions requiring summarization
• list (1,048 samples): Questions with list-based answers

Each question type is provided as a separate split for convenient filtering and evaluation.

Source and Attribution

Original Data Source: BioASQ Challenge

BioASQ is a series of challenges on large-scale biomedical semantic indexing and question answering.

IMPORTANT: To use BioASQ data, you must:

1. Register at: https://bioasq.org/
2. Review and comply with BioASQ terms of use
3. Cite the BioASQ papers (see below)
4. Acknowledge the BioASQ dataset in any publications

Dataset Structure

Data Fields

Each sample contains:

• id: Unique question identifier
• body: The question text
• type: Question type (factoid, yesno, summary, or list)
• ideal_answer: Reference answer(s)
• exact_answer: Structured answer (for factoid/list questions)
• documents: URLs of relevant PubMed documents
• snippets: Relevant text snippets from the documents

Data Splits

The dataset is organized into 4 splits by question type:

Usage

from datasets import load_dataset

# Load all question types
dataset = load_dataset("jmhb/BioASQ")

# Load only factoid questions
factoid = load_dataset("jmhb/BioASQ", split="factoid")

# Load specific question types
dataset = load_dataset("jmhb/BioASQ", split=["factoid", "yesno"])

Citation

If you use this dataset, you must cite the original BioASQ papers (the first two below). If you found this processed version valuable, please also consider citing PaperSearchQA:

@article{krithara2023bioasq,
  title={BioASQ-QA: A manually curated corpus for Biomedical Question Answering},
  author={Krithara, Anastasia and Nentidis, Anastasios and Bougiatiotis, Konstantinos and Paliouras, Georgios},
  journal={Scientific Data},
  volume={10},
  number={1},
  pages={170},
  year={2023},
  publisher={Nature Publishing Group UK London}
}

@article{tsatsaronis2015overview,
  title={An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition},
  author={Tsatsaronis, George and Balikas, Georgios and Malakasiotis, Prodromos and Partalas, Ioannis and Zschunke, Matthias and Alvers, Michael R and Weissenborn, Dirk and Krithara, Anastasia and Petridis, Sergios and Polychronopoulos, Dimitris and others},
  journal={BMC bioinformatics},
  volume={16},
  number={1},
  pages={138},
  year={2015},
  publisher={Springer}
}

@misc{burgess2026papersearchqalearningsearchreason,
      title={PaperSearchQA: Learning to Search and Reason over Scientific Papers with RLVR},
      author={James Burgess and Jan N. Hansen and Duo Peng and Yuhui Zhang and Alejandro Lozano and Min Woo Sun and Emma Lundberg and Serena Yeung-Levy},
      year={2026},
      eprint={2601.18207},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2601.18207},
}

License and Terms of Use

BioASQ License

The original BioASQ data is available for research and educational purposes under specific terms:

• Non-commercial use: Freely available for academic research and education
• Commercial use: Requires written permission from BioASQ organizers
• Attribution: Must cite BioASQ papers and acknowledge the dataset
• Registration: Users must register at https://bioasq.org/

For full license terms, see: https://bioasq.org/participate

This Dataset

This reorganized version is provided for research convenience. All terms and conditions of the original BioASQ license apply.

Links

• BioASQ Challenge: http://bioasq.org/
• BioASQ Participants Area: https://participants-area.bioasq.org/
• PaperSearchQA Project: https://jmhb0.github.io/PaperSearchQA
• Code Repository: GitHub

Acknowledgments

This dataset is made available through the BioASQ Challenge organizers. We thank them for creating and maintaining this valuable resource for the biomedical NLP community.