Datasets:
metadata
license: mit
task_categories:
- text-retrieval
tags:
- retrieval-augmented-generation
- deep-research
- search
Passage Corpus (Pyserini Format) for the BrowseComp-Plus Dataset
This repository provides the passage corpus for the BrowseComp-Plus dataset in a format compatible with Pyserini, used in the paper Revisiting Text Ranking in Deep Research.
- Code: GitHub Repository
The corpus consists of 2,772,255 passages.
Unlike the version available at
https://huggingface.co/datasets/grill-lab/browsecomp-plus-passage-corpus, this release follows the Pyserini JSONL data format.
Each item contains two fields:
id: the unique passage identifier.contents: the concatenation of the source document title and the passage text.
This format is directly compatible with Pyserini BM25.
Sample Usage
As described in the official repository, you can build a Lucene index using Pyserini with the following command:
python -m pyserini.index.lucene \
--collection JsonCollection \
--input /path/to/downloaded/data/ \
--index ./indexes/index.bm25.passage \
--generator DefaultLuceneDocumentGenerator \
--threads 16 \
--storePositions --storeDocvectors --storeRaw
Contact
If you have any questions or suggestions, please contact:
Citation
If you find this work useful, please cite:
@article{meng2026revisiting,
title={Revisiting Text Ranking in Deep Research},
author={Meng, Chuan and Ou, Litu and MacAvaney, Sean and Dalton, Jeff},
journal={arXiv preprint arXiv:2602.21456},
year={2026}
}