minorproject-research/researchy_questions_modified
Dataset Summary This dataset is derived from corbyrosset/researchy_questions, a collection of ~100k non-factoid, multi-perspective "Researchy Questions" mined from real Bing search engine logs. After a labor-intensive filtering funnel from billions of queries, these "needles in the haystack" are questions that probably require a lot of sub-questions and research to answer adequately, and are shown to be harder than other open-domain QA datasets like Natural Questions.… See the full description on the dataset page: https://huggingface.co/datasets/minorproject-research/researchy_questions_modified.
Dataset Summary
This dataset is derived from `corbyrosset/researchy_questions`, a collection of ~100k non-factoid, multi-perspective "Researchy Questions" mined from real Bing search engine logs. After a labor-intensive filtering funnel from billions of queries, these "needles in the haystack" are questions that probably require a lot of sub-questions and research to answer adequately, and are shown to be harder than other open-domain QA datasets like Natural Questions.
Modification made: the original dataset nested the headers, subquestions, and queries fields inside a single gpt4_decomposition object per row. This dataset simply flattens that nested gpt4_decomposition column into three top-level columns — headers, subquestions, and queries — alongside the original question field. No values were changed, filtered, or regenerated; the underlying data is exactly as in the source dataset, only restructured for easier direct access.
Dataset Structure
Data Splits
Data Fields
question(string): the original user-issued search query / question.headers(list of list of string): grouped top-level sub-question headers from GPT-4's closed-book decomposition of the question (flattened fromgpt4_decomposition.headers).subquestions(list of string): the flat list of sub-questions GPT-4 generated to decompose the question (flattened fromgpt4_decomposition.subquestions).queries(list of string): search queries GPT-4 suggested for retrieving grounding documents to answer the question (flattened fromgpt4_decomposition.queries).
Note: this version does not includeintrinsic_scores,DocStream,decompositional_score, ornonfactoid_scorefrom the original dataset — onlyquestionand the flattenedgpt4_decompositionfields are retained.
Source Data
This dataset is a direct restructuring of `corbyrosset/researchy_questions`, released under the CDLA-2.0 permissive license.
Citation
If you use this dataset, please cite both the original Researchy Questions paper and this dataset.
Original dataset:
@misc{rosset2024researchy,
title={Researchy Questions: A Dataset of Multi-Perspective, Decompositional Questions for LLM Web Agents},
author={Corby Rosset and Ho-Lam Chung and Guanghui Qin and Ethan C. Chau and Zhuo Feng and Ahmed Awadallah and Jennifer Neville and Nikhil Rao},
year={2024},
eprint={2402.17896},
archivePrefix={arXiv},
primaryClass={cs.CL}
}This dataset:
@misc{[your_citation_key],
title={[Your Dataset Title]},
author={Aatifa Rizvi and Lakshya Varshney},
year={2026},
howpublished={\url{https://huggingface.co/datasets/minorproject-research/researchy_questions_modified}},
note={Flattened version of corbyrosset/researchy\_questions}
}License
This dataset inherits the CDLA-2.0 license of the original corbyrosset/researchy_questions dataset.
Acknowledgements
This dataset is a lightly restructured version of Researchy Questions, created by Corby Rosset and colleagues. All credit for the underlying question collection, filtering methodology, and GPT-4 decomposition annotations goes to the original authors.
