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--- |
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license: apache-2.0 |
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configs: |
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- config_name: corpus |
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data_files: |
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- split: train |
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path: corpus/train-* |
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- config_name: question_answers |
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data_files: |
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- split: train |
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path: question_answers/train-* |
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- split: test |
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path: question_answers/test-* |
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dataset_info: |
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- config_name: corpus |
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features: |
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- name: doc_id |
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dtype: string |
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- name: url |
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dtype: string |
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- name: title |
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dtype: string |
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- name: document |
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dtype: string |
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- name: md_document |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 10625185 |
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num_examples: 1144 |
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download_size: 3327056 |
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dataset_size: 10625185 |
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- config_name: question_answers |
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features: |
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- name: question_id |
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dtype: string |
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- name: question |
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dtype: string |
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- name: correct_answer |
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dtype: string |
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- name: correct_answer_document_ids |
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dtype: string |
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- name: ground_truths_contexts |
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dtype: string |
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splits: |
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|
- name: train |
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|
num_bytes: 60268 |
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num_examples: 45 |
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- name: test |
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|
num_bytes: 33340 |
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num_examples: 30 |
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download_size: 58074 |
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dataset_size: 93608 |
|
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--- |
|
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--- |
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# watsonxDocsQA Dataset |
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## Overview |
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**watsonxDocsQA** is a new open-source dataset and benchmark contributed by IBM. The dataset is derived from enterprise product documentation and is designed specifically for end-to-end Retrieval-Augmented Generation (RAG) evaluation. The dataset consists of two components: |
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- **Documents**: A corpus of 1,144 text and markdown files generated by crawling enterprise documentation ([main page - crawl March 2024](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/welcome-main.html)). |
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- **Benchmark**: A set of 75 question-answer (QA) pairs with gold document labels and answers. The QA pairs are crafted as follows: |
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- **25 questions**: Human-generated by two subject matter experts. |
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- **50 questions**: Synthetically generated using the `tiiuae/falcon-180b` model, then manually filtered and reviewed for quality. The methodology is detailed in [Yehudai et al. 2024](https://arxiv.org/pdf/2401.14367). |
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--- |
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## Data Description |
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### Corpus Dataset |
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The corpus dataset contains the following fields: |
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| Field | Description | |
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|------------------|------------------------------------------| |
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| `doc_id` | Unique identifier for the document | |
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| `title` | Document title as it appears on the HTML page | |
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| `document` | Textual representation of the content | |
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| `md_document` | Markdown representation of the content | |
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| `url` | Origin URL of the document | |
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### Question-Answers Dataset |
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The QA dataset includes these fields: |
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| Field | Description | |
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|------------------------------|-------------------------------------------------| |
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| `question_id` | Unique identifier for the question | |
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| `question` | Text of the question | |
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| `correct_answer` | Ground-truth answer | |
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| `ground_truths_contexts_ids` | List of ground-truth document IDs | |
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| `ground_truths_contexts` | List of grounding texts on which the answer is based | |
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--- |
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## Samples |
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Below is an example from the `question_answers` dataset: |
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- **question_id**: watsonx_q_2 |
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- **question**: What foundation models have been built by IBM? |
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- **correct_answer**: |
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"Foundation models built by IBM include: |
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- granite-13b-chat-v2 |
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- granite-13b-chat-v1 |
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- granite-13b-instruct-v1" |
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- **ground_truths_contexts_ids**: B2593108FA446C4B4B0EF5ADC2CD5D9585B0B63C |
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- **ground_truths_contexts**: Foundation models built by IBM \n\nIn IBM watsonx.ai, ... |
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--- |
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## Citation |
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If you decide to use this dataset, please consider citing our preprint |
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```bibtex |
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@misc{orbach2025analysishyperparameteroptimizationmethods, |
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title={An Analysis of Hyper-Parameter Optimization Methods for Retrieval Augmented Generation}, |
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author={Matan Orbach and Ohad Eytan and Benjamin Sznajder and Ariel Gera and Odellia Boni and Yoav Kantor and Gal Bloch and Omri Levy and Hadas Abraham and Nitzan Barzilay and Eyal Shnarch and Michael E. Factor and Shila Ofek-Koifman and Paula Ta-Shma and Assaf Toledo}, |
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year={2025}, |
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eprint={2505.03452}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/2505.03452}, |
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} |
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``` |
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--- |
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## Contact |
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For questions or feedback, please: |
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- Email: [[email protected]](mailto:[email protected]) |
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- Or, open an [pull request/discussion](https://huggingface.co/datasets/ibm-research/watsonxDocsQA/discussions/new) in this repository. |
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--- |
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