Update README.md

README.md

@@ -4,6 +4,42 @@ license: mit
 
 This repository contains the development data files used in the SISAP2025 indexing challenge.
 
+## Datasets
+
+- Common Crawl CCNEWS:
+  - repo: <https://huggingface.co/datasets/sentence-transformers/ccnews/>
+  - Sentence BERT model: sentence-transformers/all-MiniLM-L6-v2
+  - similarity: Cosine / dot product
+  - dimension: 384
+  - corpus size: 614,664
+  - fields: _title_ and _article_, train embeddings come from _article_.
+
+- Google Questions & Answers:
+  - repo: <https://huggingface.co/datasets/sentence-transformers/gooaq/>
+  - Sentence BERT model: sentence-transformers/all-MiniLM-L6-v2
+  - similarity: Cosine / dot product
+  - dimension: 384
+  - corpus size: 3,012,496
+  - fields: _questions_ and _answers_, train embeddings come from _answers_.
+
+- PUBMED23 from MegRag:
+  - repo: <https://huggingface.co/datasets/MedRAG/pubmed>
+  - Sentence BERT model: sentence-transformers/all-MiniLM-L6-v2
+  - similarity: Cosine / dot product
+  - dimension: 384
+  - corpus size: 23,898,701
+  - fields: _title_ and _content_, train embeddings come from _content_.
+
+- Yahoo answers:
+  - repo: <https://huggingface.co/datasets/sentence-transformers/yahoo-answers>
+  - Sentence BERT model: sentence-transformers/all-MiniLM-L6-v2
+  - similarity: Cosine / dot product
+  - dimension: 384
+  - corpus size: 681,164
+  - fields: _question_ and _answer_, train embeddings come from _answer_.
+
+## Tasks
+
 - **Task 1:** $k=30$ nearest neighbor search on out-of-distribution queries in PUBMED23. -- sentence bert embeddings `sentence-transformers/all-MiniLM-L6-v2` from <https://huggingface.co/datasets/MedRAG/pubmed>.
 - **Task 2:** $k=15$ nearest neighbor graph (a.k.a. self-join problem) on Google QA  -- sentence bert embeddings `sentence-transformers/all-MiniLM-L6-v2` from <https://huggingface.co/datasets/sentence-transformers/gooaq/>
 
@@ -11,6 +47,7 @@ This repository contains the development data files used in the SISAP2025 indexi
 
 Additionally to PUBMED23 and Google QA we provide benchmark files for CCNEWS and Yahoo QA to help on tuning and experimentation.
 
+## h5 datasets
 The benchmark files are provided in h5 format and contain datasets and attributes
 ```
 🗂️  HDF5.File: (read-only) benchmark-dev-pubmed23.h5
@@ -43,6 +80,7 @@ Where
   - `algo` the algorithm used to create the gold-standard.
   - `querytime` the time in seconds used to compute the gold standard (using an Intel(R) Xeon(R) Silver 4216 CPU @ 2.10GHz with 60 threads)
 
+### Task2 h5 files
 `benchmark-dev-*.h5` files can be used for development and both gold-standards follow **task1**. For **task2** we provide an additional gold-standard 
 `allknn-benchmark-dev-gooaq.h5` that has the following structure: