Ontology examples

ontology_builder = lb.OntologyBuilder(
    classifications=[  # list of classification objects
        lb.Classification(class_type=lb.Classification.Type.RADIO,
                          name="radio_question",
                          options=[
                              lb.Option(value="first_radio_answer"),
                              lb.Option(value="second_radio_answer")
                          ]),
        lb.Classification(class_type=lb.Classification.Type.CHECKLIST,
                          name="checklist_question",
                          options=[
                              lb.Option(value="first_checklist_answer"),
                              lb.Option(value="second_checklist_answer")
                          ]),
        lb.Classification(class_type=lb.Classification.Type.TEXT,
                          name="free_text"),
        lb.Classification(
            class_type=lb.Classification.Type.RADIO,
            name="nested_radio_question",
            options=[
                lb.Option("first_radio_answer",
                          options=[
                              lb.Classification(
                                  class_type=lb.Classification.Type.RADIO,
                                  name="sub_radio_question",
                                  options=[lb.Option("first_sub_radio_answer")])
                          ])
            ]),
        lb.Classification(
            class_type=lb.Classification.Type.CHECKLIST,
            name="nested_checklist_question",
            options=[
                lb.Option(
                    "first_checklist_answer",
                    options=[
                        lb.Classification(
                            class_type=lb.Classification.Type.CHECKLIST,
                            name="sub_checklist_question",
                            options=[lb.Option("first_sub_checklist_answer")])
                    ])
            ]),
    ],
    tools=[  # List of Tool objects
        lb.Tool(tool=lb.Tool.Type.BBOX, name="bounding_box"),
        lb.Tool(tool=lb.Tool.Type.BBOX,
                name="bbox_with_radio_subclass",
                classifications=[
                    lb.Classification(
                        class_type=lb.Classification.Type.RADIO,
                        name="sub_radio_question",
                        options=[lb.Option(value="first_sub_radio_answer")]),
                ]),
        lb.Tool(tool=lb.Tool.Type.POLYGON, name="polygon"),
        lb.Tool(tool=lb.Tool.Type.RASTER_SEGMENTATION, name="mask"),
      	lb.Tool(tool=lb.Tool.Type.RASTER_SEGMENTATION,
                name="mask_with_text_subclass",
                classifications=[
                    lb.Classification(
                        class_type=lb.Classification.Type.TEXT,
                        name="sub_free_text")
                ]),
        lb.Tool(tool=lb.Tool.Type.POINT, name="point"),
        lb.Tool(tool=lb.Tool.Type.LINE, name="polyline"),
        lb.Tool(tool=lb.Tool.Type.RELATIONSHIP, name="relationship")
    ])

ontology = client.create_ontology("Image Annotation Import Demo Ontology",
                                  ontology_builder.asdict(),
                                  media_type=lb.MediaType.Image)

ontology_builder = lb.OntologyBuilder(
    tools=[
        lb.Tool(tool=lb.Tool.Type.BBOX, name="bbox_video"),
        lb.Tool(tool=lb.Tool.Type.POINT, name="point_video"),
        lb.Tool(tool=lb.Tool.Type.LINE, name="line_video_frame"),
        lb.Tool(tool=lb.Tool.Type.RASTER_SEGMENTATION, name="video_mask"),
        lb.Tool(
          tool=lb.Tool.Type.BBOX, name="bbox_class",
          classifications=[
            lb.Classification(
              class_type=lb.Classification.Type.RADIO,
              name="checklist_class",
              scope = lb.Classification.Scope.INDEX,
              options=[
                lb.Option(value="first_checklist_answer"),
                lb.Option(value="second_checklist_answer")
              ]
            )
          ]
        ),
      	lb.Tool(tool=lb.Tool.Type.RASTER_SEGMENTATION,
                name="mask_with_text_subclass",
                classifications=[
                    lb.Classification(
                        class_type=lb.Classification.Type.TEXT,
                        name="sub_free_text")
                    ]
                )
    ],
    classifications=[
        lb.Classification(
            class_type=lb.Classification.Type.CHECKLIST,
            name="checklist_class",
            scope = lb.Classification.Scope.INDEX, ## Need to defined scope for frame classifications
            options=[
                lb.Option(value="first_checklist_answer"),
                lb.Option(value="second_checklist_answer")
            ]
        ),
        lb.Classification(
            class_type=lb.Classification.Type.RADIO,
            name="radio_class",
            scope = lb.Classification.Scope.INDEX,
            options=[
                lb.Option(value="first_radio_answer"),
                lb.Option(value="second_radio_answer")
            ]
        ),
         lb.Classification(
              class_type=lb.Classification.Type.RADIO,
              name="nested_radio_question",
              options=[
                  lb.Option("first_radio_answer",
                        options=[
                            lb.Classification(
                                class_type=lb.Classification.Type.RADIO,
                                name="sub_radio_question",
                                options=[lb.Option("first_sub_radio_answer")]
                            )
                        ]
                  )
              ]
        ),
        lb.Classification(
          class_type=lb.Classification.Type.CHECKLIST,
          name="nested_checklist_question",
          options=[
              lb.Option("first_checklist_answer",
                options=[
                  lb.Classification(
                      class_type=lb.Classification.Type.CHECKLIST,
                      name="sub_checklist_question",
                      options=[lb.Option("first_sub_checklist_answer")]
                  )
              ]
            )
          ]
        ),
        lb.Classification(
          class_type=lb.Classification.Type.RADIO,
          name="radio_class_global",
          options=[
                lb.Option(value="first_radio_answer"),
                lb.Option(value="second_radio_answer")
            ]
        ),
        lb.Classification(
          class_type=lb.Classification.Type.CHECKLIST,
          name="checklist_class_global",
          options=[
                lb.Option(value="first_checklist_answer"),
                lb.Option(value="second_checklist_answer")
          ]
        ),
        lb.Classification(
          class_type=lb.Classification.Type.TEXT,
          name="free_text"
        )
    ]
)

ontology = client.create_ontology("Video Annotation Import Demo Ontology",
                                  ontology_builder.asdict(),
                                  media_type=lb.MediaType.Video)

ontology_builder = lb.OntologyBuilder(
  classifications=[ # List of Classification objects
    lb.Classification( 
      class_type=lb.Classification.Type.RADIO, 
      name="radio_question", 
      options=[lb.Option(value="first_radio_answer")]
    ),
    lb.Classification( 
      class_type=lb.Classification.Type.RADIO, 
      name="nested_radio_question", 
      options=[
        lb.Option(value="first_radio_answer",
          options=[
              lb.Classification(
                class_type=lb.Classification.Type.RADIO,
                name="sub_radio_question",
                options=[
                  lb.Option(value="first_sub_radio_answer")
                ]
            ),
          ]
        ),
      ], 
    ),
     lb.Classification(
      class_type=lb.Classification.Type.CHECKLIST,
      name="nested_checklist_question",
      options=[
          lb.Option("first_checklist_answer",
            options=[
              lb.Classification(
                  class_type=lb.Classification.Type.CHECKLIST,
                  name="sub_checklist_question", 
                  options=[lb.Option("first_sub_checklist_answer")]
              )
          ]
        )
      ]
    ),
    lb.Classification( 
      class_type=lb.Classification.Type.CHECKLIST, 
      name="checklist_question", 
      options=[
        lb.Option(value="first_checklist_answer"),
        lb.Option(value="second_checklist_answer"), 
        lb.Option(value="third_checklist_answer")            
      ]
    ), 
     lb.Classification( 
      class_type=lb.Classification.Type.TEXT,
      name="free_text"
    )
  ],
  tools=[ # List of Tool objects
         lb.Tool(
            tool=lb.Tool.Type.NER, 
            name="named_entity"
          ),
         lb.Tool( 
            tool=lb.Tool.Type.RELATIONSHIP,
            name="relationship"
          )
    ]
)
ontology = client.create_ontology("Ontology Text Annotations", ontology_builder.asdict()) 

ontology_builder = lb.OntologyBuilder(
    tools=[
        lb.Tool(tool=lb.Tool.Type.POINT, name="point_geo"),
        lb.Tool(tool=lb.Tool.Type.LINE, name="polyline_geo"),
        lb.Tool(tool=lb.Tool.Type.POLYGON, name="polygon_geo"),
        lb.Tool(tool=lb.Tool.Type.POLYGON, name="polygon_geo_2"),
        lb.Tool(tool=lb.Tool.Type.BBOX, name="bbox_geo"), 
        lb.Tool( 
          tool=lb.Tool.Type.BBOX, 
          name="bbox_checklist_geo",
          classifications=[
                lb.Classification(
                    class_type=lb.Classification.Type.CHECKLIST,
                    name="checklist_class_name",
                    options=[
                      lb.Option(value="first_checklist_answer")
                    ]
                ),
            ]
          ),
        lb.Tool( 
          tool=lb.Tool.Type.BBOX, 
          name="bbox_text_geo",
          classifications=[
                lb.Classification(
                    class_type=lb.Classification.Type.TEXT,
                    name="free_text_geo"
                ),
            ]
          )    
      ],
      classifications = [
          lb.Classification(
              class_type=lb.Classification.Type.CHECKLIST, 
              name="checklist_question_geo",
              options=[
                  lb.Option(value="first_checklist_answer"),
                  lb.Option(value="second_checklist_answer"), 
                  lb.Option(value="third_checklist_answer")
              ]
          ), 
          lb.Classification(
              class_type=lb.Classification.Type.RADIO, 
              name="radio_question_geo",
              options=[
                  lb.Option(value="first_radio_answer")
              ]
          ),
          
        lb.Classification( 
          class_type=lb.Classification.Type.RADIO, 
          name="nested_radio_question", 
          options=[
            lb.Option(value="first_radio_answer",
              options=[
                  lb.Classification(
                    class_type=lb.Classification.Type.RADIO,
                    name="sub_radio_question",
                    options=[
                      lb.Option(value="first_sub_radio_answer")
                    ]
                ),
              ]
            ),
          ], 
        ),
        lb.Classification(class_type=lb.Classification.Type.TEXT,
                          name="free_text"),
        lb.Classification(
          class_type=lb.Classification.Type.CHECKLIST,
          name="nested_checklist_question",
          options=[
              lb.Option("first_checklist_answer",
                options=[
                  lb.Classification(
                      class_type=lb.Classification.Type.CHECKLIST,
                      name="sub_checklist_question", 
                      options=[lb.Option("first_sub_checklist_answer")]
                  )
              ]
            )
          ]
      ) 
    ]
)

ontology = client.create_ontology("Ontology Geospatial Annotations", ontology_builder.asdict(), media_type=lb.MediaType.Geospatial_Tile)

ontology_builder = lb.OntologyBuilder(
  classifications=[ # List of Classification objects
    lb.Classification( 
      class_type=lb.Classification.Type.RADIO,
      name="radio_question", 
      scope = lb.Classification.Scope.GLOBAL,
      options=[
        lb.Option(value="first_radio_answer"),
        lb.Option(value="second_radio_answer")
      ]
    ),
    lb.Classification(
      class_type=lb.Classification.Type.CHECKLIST,
      name="checklist_question", 
      scope = lb.Classification.Scope.GLOBAL,
      options=[
        lb.Option(value="first_checklist_answer"),
        lb.Option(value="second_checklist_answer")
      ]
    ), 
    lb.Classification(
      class_type=lb.Classification.Type.TEXT,
      name="free_text",
      scope = lb.Classification.Scope.GLOBAL
    ),
    lb.Classification(
        class_type=lb.Classification.Type.RADIO,
        name="nested_radio_question",
        scope = lb.Classification.Scope.GLOBAL,
        options=[
            lb.Option("first_radio_answer",
                options=[
                    lb.Classification(
                        class_type=lb.Classification.Type.RADIO,
                        name="sub_radio_question",
                        options=[lb.Option("first_sub_radio_answer")]
                    )
                ])
          ]
    ),
    lb.Classification(
      class_type=lb.Classification.Type.CHECKLIST,
      name="nested_checklist_question",
      scope = lb.Classification.Scope.GLOBAL,
      options=[
          lb.Option("first_checklist_answer",
            options=[
              lb.Classification(
                  class_type=lb.Classification.Type.CHECKLIST,
                  name="sub_checklist_question", 
                  options=[lb.Option("first_sub_checklist_answer")]
              )
          ])
      ]
    ),      
  ],
  tools=[ # List of Tool objects
    lb.Tool( tool=lb.Tool.Type.BBOX,name="bounding_box"), 
    lb.Tool(tool=lb.Tool.Type.NER, name="named_entity"),
    lb.Tool(tool=lb.Tool.Type.RELATIONSHIP,name="relationship"),
    lb.Tool(tool=lb.Tool.Type.NER,
            name="ner_with_checklist_subclass",
            classifications=[
              lb.Classification(
                class_type=lb.Classification.Type.CHECKLIST,
                name="sub_checklist_question",
                options=[
                  lb.Option(value="first_sub_checklist_answer")
                ]
              )
          ]),
    lb.Tool( tool=lb.Tool.Type.BBOX,
            name="bbox_with_radio_subclass",
            classifications=[
              lb.Classification(
                  class_type=lb.Classification.Type.RADIO,
                  name="sub_radio_question",
                  options=[
                    lb.Option(
                      value="first_sub_radio_answer" ,
                      options=[
                        lb.Classification(
                          class_type=lb.Classification.Type.RADIO,
                          name="second_sub_radio_question",
                          options=[lb.Option("second_sub_radio_answer")]
                        )]
                    )]
                )]
      )]
)

ontology = client.create_ontology("Document Annotation Import Demo",
                                  ontology_builder.asdict(),
                                  media_type=lb.MediaType.Document)

ontology_builder = lb.OntologyBuilder(
  classifications=[ 
    lb.Classification( 
      class_type=lb.Classification.Type.TEXT,
      name="text_audio"), 
    lb.Classification( 
      class_type=lb.Classification.Type.CHECKLIST,                   
      name="checklist_audio", 
      options=[
        lb.Option(value="first_checklist_answer"),
        lb.Option(value="second_checklist_answer")            
      ]
    ), 
    lb.Classification( 
      class_type=lb.Classification.Type.RADIO, 
      name="radio_audio", 
      options=[
        lb.Option(value="first_radio_answer"),
        lb.Option(value="second_radio_answer")
      ]
    )
  ]
)

ontology = client.create_ontology("Ontology Audio Annotations", 
                                  ontology_builder.asdict(), 
                                  media_type=lb.MediaType.Audio)

ontology_builder = lb.OntologyBuilder(
  classifications=[ 
    lb.Classification( 
      class_type=lb.Classification.Type.TEXT,
      name="text_html"), 
    lb.Classification( 
      class_type=lb.Classification.Type.CHECKLIST,                   
      name="checklist_html", 
      options=[
        lb.Option(value="first_checklist_answer"),
        lb.Option(value="second_checklist_answer")            
      ]
    ), 
    lb.Classification( 
      class_type=lb.Classification.Type.RADIO, 
      name="radio_html", 
      options=[
        lb.Option(value="first_radio_answer"),
        lb.Option(value="second_radio_answer")
      ]
    )
  ]
)

ontology = client.create_ontology("Ontology HTML Annotations", ontology_builder.asdict(), media_type=lb.MediaType.Html)

ontology_builder = lb.OntologyBuilder(
  tools=[ 
    lb.Tool(tool=lb.Tool.Type.NER,name="ner"),
    lb.Tool(tool=lb.Tool.Type.RELATIONSHIP,name="relationship")
    ], 
  classifications=[ 
    lb.Classification( 
      class_type=lb.Classification.Type.TEXT,
      scope=lb.Classification.Scope.INDEX,  # Remove this line or set scope to "GLOBAL" if importing global text annotations
      instructions="text_convo"), 
    lb.Classification( 
      class_type=lb.Classification.Type.CHECKLIST, 
      scope=lb.Classification.Scope.INDEX,  # Remove this line or set scope to "GLOBAL" if importing global checklist annotations                 
      instructions="checklist_convo", 
      options=[
        lb.Option(value="first_checklist_answer"),
        lb.Option(value="second_checklist_answer")            
      ]
    ), 
    lb.Classification( 
      class_type=lb.Classification.Type.RADIO, 
      instructions="radio_convo", 
      scope=lb.Classification.Scope.INDEX, # Remove this line or set scope to "GLOBAL" if importing global radio  annotations         
      options=[
        lb.Option(value="first_radio_answer"),
        lb.Option(value="second_radio_answer")
      ]
    )
  ]
)

ontology = client.create_ontology("Ontology Conversation Annotations", ontology_builder.asdict())

ontology_builder = lb.OntologyBuilder(
    tools=[
        lb.Tool(
            tool=lb.Tool.Type.MESSAGE_SINGLE_SELECTION,
            name="single select feature",
        ),
        lb.Tool(
            tool=lb.Tool.Type.MESSAGE_MULTI_SELECTION,
            name="multi select feature",
        ),
        lb.Tool(tool=lb.Tool.Type.MESSAGE_RANKING, name="ranking feature"),
    ],
    classifications=[
        lb.Classification(
            class_type=lb.Classification.Type.CHECKLIST,
            name="checklist feature",
            options=[
                lb.Option(value="option 1", label="option 1"),
                lb.Option(value="option 2", label="option 2"),
            ],
        ),
        lb.Classification(
            class_type=lb.Classification.Type.RADIO,
            name="radio_question",
            options=[
                lb.Option(value="first_radio_answer"),
                lb.Option(value="second_radio_answer"),
            ],
        ),
    ],
)

# Create ontology
ontology = client.create_ontology(
    "MCE ontology",
    ontology_builder.asdict(),
    media_type=lb.MediaType.Conversational,
    ontology_kind=lb.OntologyKind.ModelEvaluation,
)