|
--- |
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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-* |
|
- 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 |
|
splits: |
|
- name: train |
|
num_bytes: 10625185 |
|
num_examples: 1144 |
|
download_size: 3327056 |
|
dataset_size: 10625185 |
|
- config_name: question_answers |
|
features: |
|
- name: question_id |
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dtype: string |
|
- name: question |
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dtype: string |
|
- name: correct_answer |
|
dtype: string |
|
- name: correct_answer_document_ids |
|
dtype: string |
|
- name: ground_truths_contexts |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 60268 |
|
num_examples: 45 |
|
- name: test |
|
num_bytes: 33340 |
|
num_examples: 30 |
|
download_size: 58074 |
|
dataset_size: 93608 |
|
--- |
|
--- |
|
|
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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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## 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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