Update README.md

README.md

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----
-license: apache-2.0
-configs:
-- config_name: corpus
-  data_files:
-  - split: train
-    path: corpus/train-*
-- config_name: question_answers
-  data_files:
-  - split: train
-    path: question_answers/train-*
-  - split: test
-    path: question_answers/test-*
-dataset_info:
-- config_name: corpus
-  features:
-  - name: doc_id
-    dtype: string
-  - name: url
-    dtype: string
-  - name: title
-    dtype: string
-  - name: document
-    dtype: string
-  - name: md_document
-    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
-    dtype: string
-  - name: question
-    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: 60224
-    num_examples: 45
-  - name: test
-    num_bytes: 33370
-    num_examples: 30
-  download_size: 58177
-  dataset_size: 93594
----
+---
+license: apache-2.0
+configs:
+- config_name: corpus
+  data_files:
+  - split: train
+    path: corpus/train-*
+- config_name: question_answers
+  data_files:
+  - split: train
+    path: question_answers/train-*
+  - split: test
+    path: question_answers/test-*
+dataset_info:
+- config_name: corpus
+  features:
+  - name: doc_id
+    dtype: string
+  - name: url
+    dtype: string
+  - name: title
+    dtype: string
+  - name: document
+    dtype: string
+  - name: md_document
+    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
+    dtype: string
+  - name: question
+    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: 60224
+    num_examples: 45
+  - name: test
+    num_bytes: 33370
+    num_examples: 30
+  download_size: 58177
+  dataset_size: 93594
+---
+---
+
+# watsonxDocsQA Dataset
+
+## Overview
+
+**watsonxDocsQA** is a new open-source dataset and benchmark derived from enterprise product documentation. Designed specifically for end-to-end Retrieval-Augmented Generation (RAG) evaluation, it consists of two key components:
+
+- **Documents**: A corpus of 1,144 text and markdown files generated by crawling enterprise documentation (link to the documentation source : [https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/welcome-main.html](#)).
+- **Benchmark**: A set of 75 question-answer (QA) pairs with gold document labels and answers.
+
+The QA pairs are crafted as follows:
+- **25 questions**: Human-generated by two subject matter experts.
+- **50 questions**: Synthetically generated using the `tiiuae/falcon-180b` model, then manually filtered and reviewed for quality. The methodology is detailed in [this paper](https://arxiv.org/pdf/2401.14367).
+
+### Key Details
+- **Number of Samples**: 
+  - Corpus: 1,144 documents
+  - QA Set: 75 questions
+- **Format**: CSV
+- **License**: [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)
+
+---
+
+## Data Description
+
+### Corpus Dataset
+The corpus dataset contains the following fields:
+
+| Field            | Description                              |
+|------------------|------------------------------------------|
+| `doc_id`         | Unique identifier for the document       |
+| `title`          | Document title as it appears on the HTML page |
+| `document`       | Textual representation of the content    |
+| `md_document`    | Markdown representation of the content   |
+| `url`            | Origin URL of the document               |
+
+### Question-Answers Dataset
+The QA dataset includes these fields:
+
+| Field                        | Description                                      |
+|------------------------------|-------------------------------------------------|
+| `question_id`                | Unique identifier for the question              |
+| `question`                   | Text of the question                            |
+| `correct_answer`             | Ground-truth answer                             |
+| `ground_truths_contexts_ids` | List of ground-truth document IDs               |
+| `ground_truths_contexts`            | List of ground-truth answer texts (typically extracted from the documents) |
+
+---
+
+## Samples
+
+---
+
+Below is an example from the `question_answers` dataset:
+
+- **question_id**: watsonx_q_2
+- **question**: What foundation models have been built by IBM?
+- **correct_answer**:  
+  "Foundation models built by IBM include:  
+  - granite-13b-chat-v2  
+  - granite-13b-chat-v1  
+  - granite-13b-instruct-v1"
+- **ground_truths_contexts_ids**: B2593108FA446C4B4B0EF5ADC2CD5D9585B0B63C
+- **ground_truths_contexts**: Foundation models built by IBM \n\nIn IBM watsonx.ai, ...
+
+---
+
+
+## Contact
+
+For questions or feedback, please:
+- Email: [[email protected]](mailto:[email protected])
+- Or, open an issue in this repository.
+
+---