---
pretty_name: BRIGHT stackoverflow (unified retrieval schema)
license: cc-by-4.0
language:
- en
task_categories:
- text-retrieval
tags:
- bright
- retrieval
- reasoning
configs:
- config_name: corpus
  data_files:
  - split: test
    path: corpus/test-*.parquet
- config_name: queries
  data_files:
  - split: test
    path: queries/test-*.parquet
- config_name: qrels
  data_files:
  - split: test
    path: qrels/test-*.parquet
---
# BRIGHT: stackoverflow

A format conversion of the **standard passage-retrieval** setting of
[BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval](https://arxiv.org/abs/2407.12883),
by the original BRIGHT authors. Source: [xlangai/BRIGHT](https://huggingface.co/datasets/xlangai/BRIGHT/tree/3066d29c9651a576c8aba4832d249807b181ecae),
pinned to `3066d29c9651a576c8aba4832d249807b181ecae`. This is a converted mirror, not an independently annotated dataset.
The original dataset is distributed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
See `SOURCE_README.md` for the original dataset card and attribution.

| Table | Rows | Columns |
|---|---:|---|
| corpus | 107,081 | id, title, text |
| queries | 117 | id, text |
| qrels | 478 | query-id, corpus-id, score |
| exclusions (optional) | 0 | query-id, corpus-id |

All published configs use the `test` split. `corpus.text` is exactly the original
`documents.content`; `title` is empty. Query IDs, document IDs and original `examples.query`
strings are preserved without normalization. `qrels` is the unique set of `gold_ids` pairs,
with binary score 1. Duplicate labels are collapsed; no relevance judgments are added.
Gold reasoning, gold answers, `gold_ids_long`, generated query rewrites and `long_documents`
are not part of the converted evaluation inputs.

This subset has no real excluded documents; the optional `exclusions` table is omitted.
The `N/A` exclusion sentinel is removed. Excluded IDs and positive IDs are validated against
the corpus and must be disjoint for each query. Keep `ignore_identical_ids=false`: matching
query/document ID strings alone do not imply a BRIGHT exclusion.

Evaluate each BRIGHT subset against its own complete corpus. Report nDCG@10 per subset and
the unweighted mean across the 12 subsets. Record encoder context limits and truncation.
The original [evaluation code](https://github.com/xlang-ai/BRIGHT) defines the protocol.

Converted with `scripts/preprocess/dataset/convert_bright.py` in the SPARSE project.
`conversion.json` records source and output SHA-256 hashes, row counts and validation checks.