adding qna data, readme, notice

NOTICES.md

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+# OCB Third-Party Notices
+
+This file documents third-party content redistributed in the OCB
+public release and the licenses under which it is redistributed.
+
+## Hosted reference files from Kaggle
+
+The following file is redistributed under the MIT License. The
+original MIT license notice is preserved here per MIT terms.
+
+- `games_may2024_cleaned_sampled.csv`
+  Source: https://www.kaggle.com/datasets/artermiloff/steam-games-dataset
+  License: MIT
+  Original copyright notice: [paste the MIT notice from the Kaggle dataset's LICENSE file]
+
+The following file is redistributed under CC0 1.0 (no attribution
+required, included here for transparency):
+
+- `fraud_detection_bank_dataset.csv`
+  Source: https://www.kaggle.com/datasets/volodymyrgavrysh/fraud-detection-bank-dataset-20
+  License: CC0 1.0
+
+## Hosted reference files from U.S. government open-data portals
+
+Files from these sources are U.S. Government Work / Public Domain
+or are released under open-data terms permitting redistribution.
+No attribution is legally required; the URL manifest preserves source
+attribution for transparency.
+
+## URL-referenced files
+
+Files referenced via the URL manifest retain their original licenses.
+OCB does not assert a license over these files.

README.md

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 ---
 license: cdla-permissive-2.0
+language:
+- en
+tags:
+- benchmark
+- document-comprehension
+- office-documents
+- question-answering
+- llm-evaluation
+pretty_name: OfficeComprehensionBenchmark (OCB)
+size_categories:
+- 1K<n<10K
 ---
+
+# OfficeComprehensionBenchmark (OCB)
+
+OCB is a benchmark for evaluating document comprehension and grounded reasoning over Microsoft Office files (Word, Excel, PowerPoint). It comprises two tracks:
+
+- **File Fidelity Q&A** — measures structural and visual perception of document artifacts (text, tables, charts, formulas, formatting, embedded objects).
+- **Domain Q&A** — measures expert-level reasoning over real-world business documents across 12 industries.
+
+## Companion repository
+
+Evaluation prompts, judge scripts, file-download utilities, and PDF→Office conversion scripts are maintained in the companion GitHub repository:
+
+**https://github.com/confanon/OfficeComprehensionBench**
+
+This Hugging Face dataset hosts the questions, reference answers, atomic assertion rubrics, the URL manifest for externally-hosted reference files, and the redistributable subset of reference files. Most reproduction tasks (running judges, fetching URL-referenced files, converting source PDFs to native Office formats) require the GitHub repository.
+
+## Benchmark size
+
+- **File Fidelity track:** 244 files, 922 queries
+- **Domain Q&A track:** 124 files, 120 queries, 8,450 atomic assertions across 12 industries
+
+These numbers reflect the full evaluation set reported in the accompanying paper. See the *May 07 Update* note below for the relationship between the evaluated set and the publicly released artifact.
+
+## Distribution model
+
+OCB uses a hybrid distribution model driven by source licensing:
+
+- **Hosted directly on Hugging Face** — reference files whose source license permits redistribution under CDLA-Permissive-2.0, plus all questions, reference answers, and assertion rubrics.
+- **Referenced via URL manifest** — reference files whose source licensing does not permit redistribution. The manifest is shipped with this dataset; the GitHub repository contains a release script that downloads each file from its original public source and, where required, converts it from its source format (e.g., PDF) into the native Office format (.docx, .xlsx, .pptx) used by the benchmark.
+
+## May 07 Update
+
+Three Excel files originally included in the evaluation set are **excluded from this public release for licensing reasons**:
+
+- `winemag-data-130k-v2_sampled.csv`
+- `Banking_Call_Data.csv`
+- `brazilian_ecommerce_cleaned.csv`
+
+These files are sourced from Kaggle datasets published under CC BY-NC-SA 4.0, which is incompatible with the CDLA-Permissive-2.0 release license. The associated File Fidelity queries that target these files are also excluded from the public release.
+
+**Reported benchmark numbers in the paper reflect the full evaluation set including these files.** Users wishing to reproduce the full evaluation can obtain the three source datasets directly from Kaggle under the original publishers' terms; URLs are listed in the URL manifest alongside the other externally-referenced files.
+
+## License
+
+This dataset is released under the **Community Data License Agreement – Permissive, Version 2.0 (CDLA-Permissive-2.0)** — https://cdla.dev/permissive-2-0/.
+
+Sub-components carry the following licenses:
+
+- **OCB-authored content** (questions, reference answers, atomic assertions, expert-authored reference files): CDLA-Permissive-2.0.
+- **Hosted reference files from U.S. government open-data portals**: U.S. Government Work / Public Domain (federal sources) or open-data terms permitting redistribution (state/local sources). Redistributed under CDLA-Permissive-2.0.
+- **Hosted reference files from Kaggle**: only files under CC0 1.0 or MIT are redistributed. Attribution and notice obligations of MIT-licensed sources are preserved in the `NOTICES.md` file in this repository.
+- **URL-referenced files**: retain their original licenses; OCB does not assert a license over these files. Users fetch them directly from the original publishers under those publishers' terms.
+
+See `NOTICES.md` in this repository for per-source attribution and notice details.
+
+## Intended use
+
+OCB is intended for evaluation, not training. Validated use cases include:
+
+- Benchmarking model accuracy on grounded question answering over structured and semi-structured Office files
+- Comparing models on cross-format reasoning (e.g., Word + Excel inputs)
+- Evaluating fidelity of structural and visual document perception
+- Ablation studies on retrieval and grounding components for Office-document pipelines
+
+Not validated, and not recommended:
+
+- Use as training data
+- Evaluation on file formats outside .docx / .xlsx / .pptx
+- High-stakes deployment decisions in regulated domains (medical, legal, financial advice) on the basis of OCB scores alone
+
+## Citation
+
+```bibtex
+@misc{ocb2026,
+  title  = {OfficeComprehensionBenchmark},
+  author = {Anonymous},
+  year   = {2026},
+  note   = {Under review at NeurIPS 2026 Evaluations \& Datasets Track}
+}
+```
+
+## Maintenance
+
+Versioned releases are maintained on Hugging Face under this repository. Issues, corrections, and erratum requests are tracked through the dataset repository's discussion page. We commit to maintaining the dataset for at least 3 years post-publication.
+
+If an externally-hosted file becomes unavailable from its original source, we will either replace it with an equivalent example or document the removal in the errata.

data/{ocb-00000-of-00001.parquet → ocb_qna_data.parquet}

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