Update README.md

README.md

@@ -63,7 +63,9 @@ The GQA (Visual Reasoning in the Real World) dataset is a large-scale visual que
 
 This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 35000 samples.
 
-Note: This dataset does not contain questions, only the scene graph annotations as detection-level attributes.
+Note: This is a 35,000 sample subset which does not contain questions, only the scene graph annotations as detection-level attributes.
+
+You can find the recipe notebook for creating the dataset [here](https://colab.research.google.com/drive/1IjyvUSFuRtW2c5ErzSnz1eB9syKm0vo4?usp=sharing)
 
 ## Installation
 
@@ -95,9 +97,7 @@ session = fo.launch_app(dataset)
 ## Scene Graph Annotations
 
 - Each of the 113K images in GQA is associated with a detailed scene graph describing the objects, attributes and relations present.
-- 
 - The scene graphs are based on a cleaner version of the Visual Genome scene graphs.
-- 
 - For each image, the scene graph is provided as a dictionary (sceneGraph) containing:
   - Image metadata like width, height, location, weather
   - A dictionary (objects) mapping each object ID to its name, bounding box coordinates, attributes, and relations[6]