diff --git a/examples/basics/ontologies.ipynb b/examples/basics/ontologies.ipynb
index 64a13d7ff..a9dc0b4f9 100644
--- a/examples/basics/ontologies.ipynb
+++ b/examples/basics/ontologies.ipynb
@@ -1,18 +1,16 @@
 {
-  "nbformat": 4,
-  "nbformat_minor": 5,
-  "metadata": {},
   "cells": [
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "<td>\n",
         "   <a target=\"_blank\" href=\"https://labelbox.com\" ><img src=\"https://labelbox.com/blog/content/images/2021/02/logo-v4.svg\" width=256/></a>\n",
         "</td>"
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "<td>\n",
@@ -24,10 +22,10 @@
         "<a href=\"https://github.com/Labelbox/labelbox-python/tree/master/examples/basics/ontologies.ipynb\" target=\"_blank\"><img\n",
         "src=\"https://img.shields.io/badge/GitHub-100000?logo=github&logoColor=white\" alt=\"GitHub\"></a>\n",
         "</td>"
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "# Ontologies\n",
@@ -37,48 +35,49 @@
         "* Helpful Links:\n",
         "    * [Ontology documentation](https://docs.labelbox.com/docs/labelbox-ontology)\n",
         "    * [Project Setup Using Ontologies](https://github.com/Labelbox/labelbox-python/blob/master/examples/project_configuration/project_setup.ipynb)"
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "!pip install labelbox -q"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "import labelbox as lb\n",
         "import json"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "# API Key and Client\n",
         "Provide a valid api key below in order to properly connect to the Labelbox Client."
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# Add your api key\n",
         "API_KEY = \"\"\n",
         "client = lb.Client(api_key=API_KEY)"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
+      "id": "1d40f49d",
       "metadata": {},
       "source": [
         "### Create Ontology From Normalized Data\n",
@@ -92,14 +91,16 @@
         "| Polygon           | polygon      |\n",
         "| Polyline          | line         |\n",
         "| Point             | point        |\n",
-        "| Segmentation mask | superpixel   |\n",
+        "| Segmentation mask | raster-segmentation  |\n",
         "| Entity            | named-entity |\n",
         "| Relationship      | edge         |"
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# This will automatically create new feature schema\n",
         "ontology_name = \"sdk-ontology\"\n",
@@ -116,22 +117,22 @@
         "ontology = client.create_ontology(name=ontology_name,\n",
         "                                  normalized=ontology_normalized_json)\n",
         "print(ontology)"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "### Create Ontology From Existing Feature Schemas\n",
         "* It is often useful to support the same features in multiple ontologies. \n",
         "* Labelbox supports this workflow by allowing users to create ontologies using existing feature schemas."
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# First create the feature schema\n",
         "feature_schema_cat = client.create_feature_schema(feature_schema_cat_normalized)\n",
@@ -139,23 +140,23 @@
         "print(feature_schema_cat.uid)\n",
         "ontology = client.create_ontology_from_feature_schemas(ontology_name,\n",
         "                                                       [feature_schema_cat.uid])"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "### Create Ontology From a Mix of New and Existing Feature Schemas\n",
         "* If we want to create a new ontology that expands upon a previous ontology it is helpful to be able to share a portion of the features.\n",
         "* To do this we will create the new schema ids that we want. Then we will create an ontology from the new list of ids.\n",
         "* Note that for additional customization you can also combine the normalized json and use the create_ontology() method (not covered here)."
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# Create new dog schema id\n",
         "feature_schema_dog_normalized = {\n",
@@ -169,103 +170,101 @@
         "# (ie. the cat feature schema will not be re-created)\n",
         "ontology = client.create_ontology_from_feature_schemas(\n",
         "    ontology_name, [feature_schema_cat.uid, feature_schema_dog.uid])"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "### Read\n",
         "* We can directly query by id for ontologies and feature schemas\n",
         "* We also can search for both by name"
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "#### Fetch by ID\n",
         "feature_schema = client.get_feature_schema(feature_schema_cat.uid)\n",
         "ontology = client.get_ontology(ontology.uid)\n",
         "print(feature_schema)\n",
         "print(ontology)"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "#### Search by name\n",
         "feature_schema = next(client.get_feature_schemas(\"cat\"))\n",
         "ontology = next(client.get_ontologies(ontology_name))\n",
         "print(feature_schema)\n",
         "print(ontology)"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "### Update and Delete"
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# Check if feature is archived\n",
         "feature_schema = next(client.get_feature_schemas(\"cat\"))\n",
         "client.is_feature_schema_archived(ontology_id=ontology.uid, feature_schema_id=feature_schema.uid)"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# Update a feature's title \n",
         "client.update_feature_schema_title(feature_schema_id=feature_schema.uid, title=\"cat-2\")\n",
         "feature = client.get_feature_schema(feature_schema_id=feature_schema.uid)\n",
         "print(\"Feature: \", feature)"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# Replace a feature \n",
         "tool = lb.Tool(feature_schema_id=feature_schema.uid, name=\"tool-cat-upserted\", tool=lb.Tool.Type.BBOX, color=\"#FF0000\")\n",
         "upserted_feature_schema_id = client.upsert_feature_schema(tool.asdict()).uid\n",
         "feature = client.get_feature_schema(feature_schema_id=upserted_feature_schema_id)\n",
         "print(\"Updated feature: \", feature)"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# Insert a new feature \n",
         "tool = lb.Tool(name=\"tool-cat-2\", tool=lb.Tool.Type.RASTER_SEGMENTATION)\n",
         "feature_schema_id_new = client.create_feature_schema(tool.asdict()).uid\n",
         "client.insert_feature_schema_into_ontology(feature_schema_id=feature_schema_id_new, ontology_id=ontology.uid , position=2)\n",
         "print(\"Updated ontology: \", client.get_ontology(ontology_id=ontology.uid))"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "Delete or Archived a feature:\n",
@@ -273,40 +272,42 @@
         "If the feature schema is a root level node with associated labels, it will be archived.\n",
         "If the feature schema is a nested node in the ontology and does not have associated labels, it will be deleted.\n",
         "If the feature schema is a nested node in the ontology and has associated labels, it will not be deleted."
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "client.delete_feature_schema_from_ontology(ontology_id=ontology.uid, feature_schema_id=feature_schema_id_new)"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# Only features with annotations will be archived, features without annotations will be deleted. \n",
         "feature_schema_id_with_annotations = \"\" \n",
         "ontology_id = \"\"\n",
         "client.unarchive_feature_schema_node(ontology_id=ontology_id, root_feature_schema_id=feature_schema_id_with_annotations)"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "### Ontology Builder\n",
         "* The ontology builder is a tool for creating and modifying normalized json"
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# Create normalized json with a bounding box and segmentation tool\n",
         "ontology_builder = lb.OntologyBuilder(tools=[\n",
@@ -317,20 +318,20 @@
         "ontology = client.create_ontology(\"ontology-builder-ontology\",\n",
         "                                  ontology_builder.asdict())\n",
         "print(json.dumps(ontology.normalized, indent=2))"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "* Alternative syntax for defining the ontology via the OntologyBuilder"
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# Create\n",
         "ontology_builder = lb.OntologyBuilder()\n",
@@ -342,20 +343,20 @@
         "ontology = client.create_ontology(\"ontology-builder-ontology\",\n",
         "                                  ontology_builder.asdict())\n",
         "print(json.dumps(ontology.normalized, indent=2))"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "* Classifications are supported too (Both for top level and as subclassifications)"
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "ontology_builder = lb.OntologyBuilder(\n",
         "    tools=[\n",
@@ -374,20 +375,20 @@
         "                                lb.Option(value=\"blurry\")])\n",
         "    ])\n",
         "print(json.dumps(ontology_builder.asdict(), indent=2))"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "Example of how to add sub-classfication within an option"
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "# We will use add_classification to add this classification to a previously built ontology_builder or you can create new ontology_builder = OntologyBuilder() \n",
         "radio_classification = lb.Classification(class_type=lb.Classification.Type.RADIO,\n",
@@ -403,20 +404,20 @@
         "ontology = client.create_ontology(\"example of nested classification\",\n",
         "                                  ontology_builder.asdict())\n",
         "print(json.dumps(ontology.normalized, indent=2))"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "* All Tool objects are constructed the same way:"
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "bbox_tool = lb.Tool(tool=lb.Tool.Type.BBOX, name=\"dog_box\")\n",
         "poly_tool = lb.Tool(tool=lb.Tool.Type.POLYGON, name=\"dog_poly\")\n",
@@ -425,21 +426,21 @@
         "line_tool = lb.Tool(tool=lb.Tool.Type.LINE, name=\"dog_orientation\")\n",
         "ner_tool = lb.Tool(tool=lb.Tool.Type.NER, name=\"dog_reference\")\n",
         "relationship_tool = lb.Tool(tool=lb.Tool.Type.RELATIONSHIP, name=\"relationship\")"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     },
     {
+      "cell_type": "markdown",
       "metadata": {},
       "source": [
         "* Classifications are all constructed the same way (except text which doesn't require options)\n",
         "* Classifications can be global or subclasses to a tool (ie dog bounding box, with a breed classification)"
-      ],
-      "cell_type": "markdown"
+      ]
     },
     {
+      "cell_type": "code",
+      "execution_count": null,
       "metadata": {},
+      "outputs": [],
       "source": [
         "text_classification = lb.Classification(class_type=lb.Classification.Type.TEXT,\n",
         "                                     name=\"dog_name\")\n",
@@ -450,10 +451,14 @@
         "    class_type=lb.Classification.Type.CHECKLIST,\n",
         "    name=\"background\",\n",
         "    options=[lb.Option(\"at_park\"), lb.Option(\"has_leash\")])"
-      ],
-      "cell_type": "code",
-      "outputs": [],
-      "execution_count": null
+      ]
     }
-  ]
-}
\ No newline at end of file
+  ],
+  "metadata": {
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}