| --- |
| language: |
| - en |
| license: apache-2.0 |
| pretty_name: RAGmix |
| task_categories: |
| - question-answering |
| - text-retrieval |
| task_ids: |
| - extractive-qa |
| - closed-domain-qa |
| tags: |
| - rag |
| - retrieval-augmented-generation |
| - evaluation |
| - benchmark |
| - multi-domain |
| - heterogeneous |
| - document-qa |
| - apache-2.0 |
| - digitalcorpora |
| configs: |
| - config_name: Ragmix |
| data_files: |
| - split: test |
| path: data/test-00000-of-00001-43be72dace544f4fba6c2a484a3a0032.parquet |
| size_categories: |
| - n<1K |
| dataset_info: |
| features: |
| - name: category |
| dtype: string |
| - name: document |
| dtype: string |
| - name: question |
| dtype: string |
| - name: answer |
| dtype: string |
| splits: |
| - name: test |
| num_examples: 100 |
| --- |
| |
| # RAGmix |
|
|
| **RAGmix** is a heterogeneous, multi-domain evaluation dataset for **Retrieval-Augmented Generation (RAG)** systems. |
|
|
| It mixes real-world document styles—policies, meeting minutes, clinical and scientific text, financial disclosures, job postings, and more—so models can be tested outside a single vertical. Each example pairs a full source document with one grounded question and a reference answer. |
|
|
| Source PDFs were obtained from **[Digital Corpora](https://digitalcorpora.org/)** and converted to markdown for this release. This is a **test-only** split (100 examples). |
|
|
| ## How the data was built |
|
|
| 1. **Documents** — Heterogeneous PDFs were downloaded from Digital Corpora, a public repository of digital corpora for forensics education and research, and converted to markdown (OCR/layout-aware parsing with image analysis where needed). |
| 2. **Questions** — One evaluation question per document, targeting specific, document-grounded facts (dates, amounts, requirements, findings, procedures). |
| 3. **Answers** — Short reference answers written from the same document only (no external knowledge required for the gold answer). |
| 4. **Categories** — Manual topic labels for multi-domain analysis. |
|
|
| ``` |
| from datasets import load_dataset |
| rag_dataset = load_dataset("iam-tsr/ragmix") |
| ``` |
|
|
| ## Limitations |
|
|
| - Small scale (100 examples); statistical significance is limited. |
| - One question per document; does not cover multi-hop or multi-document reasoning. |
| - Documents vary widely in length and quality (OCR/markdown artifacts may remain). |
| - Categories are coarse; some documents sit near domain boundaries. |
| - English only. |
| - Reference answers are human-written summaries of document facts; alternative phrasings may also be correct. |
|
|
| ## Ethical considerations |
|
|
| - Document texts originate from third-party PDFs hosted via Digital Corpora; treat redistribution of full text carefully under applicable rights and Digital Corpora’s terms. |
| - Some documents touch sensitive topics (health, religion, legal enforcement). Prefer evaluation / research use. |
| - Do not treat answers as professional medical, legal, or financial advice. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{ragmix, |
| title = {RAGmix: A Heterogeneous Multi-Domain Dataset for RAG Evaluation}, |
| author = {Tushar Soni}, |
| year = {2026}, |
| howpublished = {Hugging Face Datasets}, |
| note = {Test split, 100 document-grounded QA examples. Source PDFs from Digital Corpora (https://digitalcorpora.org/).} |
| } |
| |
| @misc{digitalcorpora, |
| title = {Digital Corpora}, |
| author = {Garfinkel, Simson L. and others}, |
| howpublished = {\url{https://digitalcorpora.org/}}, |
| note = {Public digital corpora for education and research} |
| } |
| ``` |
|
|
| ## License |
|
|
| This public extract is made available under [Apache license 2.0](https://www.apache.org/licenses/LICENSE-2.0.html). Users should also abide to the Digital Corpora. |
|
|
| ## Changelog |
|
|
| - **v0.1** — Initial test release: 100 examples, 15 categories. |
|
|
