Update README.md

README.md

@@ -55,6 +55,7 @@ configs:
     path: triplets/train-*
   - split: test
     path: triplets/test-*
+license: apache-2.0
 ---
 
 This product search dataset compiles multiple open source product search datasets, that can be used for representation learning tasks.
@@ -68,6 +69,45 @@ This product search dataset compiles multiple open source product search dataset
 | Home Depot | bstds/home_depot | Home Depot |
 | Crowdflower | napsternxg/kaggle_crowdflower_ecommerce_search_relevance | Crowdflower |
 
+### Schema
+
+### Document
+
+To standardize attributes across different sources and their availability, we use a template that can be applied based on available product information.
+
+```python
+if kwargs.get("title"):
+    template = f"""**product title**: {kwargs.get('title')}\n"""
+else:
+    template = """"""
+if kwargs.get("category"):
+    template += f"""**product category**: {kwargs.get('category').replace(" / ", " > ")}\n"""
+if kwargs.get("attributes"):
+    template += """**product attributes**:\n"""
+    for k, v in kwargs.get("attributes").items():
+        template += f""" - **{k}**: {v}\n"""
+
+if kwargs.get("description"):
+    template += f"""**product description**: {kwargs.get('description')}"""
+```
+
+The dataset has two splits:
+ - `Pairs`
+ - `Triplets`
+
+### Pairs
+
+Query: The user query.
+Document: The product that was retrieved by the system.
+Relevance: The relevance of the `<query, document>` pair.
+
+Each individual source will have their logic for sampling queries, documents, and relevance assessments.
+Most of the sources and manually graded by a group of annotators, except for `Marqo/marqo-GS-10M` which is the top 100 products retrieved from the system. I recommend reading the individual sources for a deeper understanding of their methodology.
+
+
+### Triplets
+
+
 ### Train
 
 | Dataset     | Queries | Documents | Pairs    |