- Getting Started
- Administration
- Manage Sources and Datasets
- Understanding the data structure and permissions
- Create a data source in the GUI
- Uploading a CSV file into a source
- Create a new dataset
- Multilingual sources and datasets
- Enabling sentiment on a dataset
- Amend a dataset's settings
- Delete messages via the UI
- Delete a dataset
- Export a dataset
- Using Exchange Integrations
- Preparing Data for .CSV Upload
- Model Training and Maintenance
- Understanding labels, entities and metadata
- Label hierarchy and best practice
- Defining your taxonomy objectives
- Analytics vs. automation use cases
- Turning your objectives into labels
- Building your taxonomy structure
- Taxonomy design best practice
- Importing your taxonomy
- Overview of the model training process
- Generative Annotation (NEW)
- Understanding the status of your dataset
- Model training and labelling best practice
- Training with label sentiment analysis enabled
- Train
- Introduction to 'Refine'
- Precision and recall explained
- Precision and recall
- How does Validation work?
- Understanding and improving model performance
- Why might a label have low average precision?
- Training using 'Check label' and 'Missed label'
- Training using Teach label (Refine)
- Training using Search (Refine)
- Understanding and increasing coverage
- Improving Balance and using 'Rebalance'
- When to stop training your model
- Using Analytics & Monitoring
- Automations and Communications Mining
- FAQs and More
Enabling, disabling, updating and creating entities
User permissions required: 'View Sources' AND 'Modify Datasets' OR 'Datasets Admin'.
Enabling entities on a new dataset
To enable entities on a new dataset that you want to create, you simply need to select them during the setup process.
Click the + button in the box shown below and you will be presented with a dropdown menu of all of the entities that you are able to enable for that dataset. Simply click all of the entities you want to enable before creating the dataset. If you add any in error, you can click the ‘X’ icon next to the entity name to remove it.
To understand more about how to create a new dataset, see here.
Enabling, updating, and disabling entities on an existing dataset
If you want to enable, update or disable entities for an existing dataset, you can do so from the settings tab on the top navigation bar, and then selecting the 'Labels & Entities' tab.
Enabling entities:
To enable existing entities, click inside the 'Entities' box, and select the entities you want to enable from the drop down menu. Once you're happy with your selections, click 'Update Entities' (as shown below).
These entities will have their settings pre-selected for you. You can then update them, including making them trainable, as shown below.
Updating entities:
To update an enabled entity, click the entity in the entity box as shown in the above images and the 'Edit entity' modal (below) will appear.
Here you can update the base entity, the title of the entity and the API name (these concepts are described in detail below), as well as making the entity 'trainable'.
If you have previously reviewed entities for an entity kind that was not set to 'trainable', this information is still stored.
Disabling entities:
To remove any selected entities, simply click the 'X' icon next to the entity name, and then click 'Update Entities'.
If you remove an entity and click 'Update Entities', this will also remove the training data for that entity for this dataset. If you chose to re-enable the entity, you will need to train it again.
If you make a mistake while updating the entities, click 'Reset' before you click 'Update Entities' and your changes will not be applied.
Creating new entities
The above sections have covered how to enable and update existing pre-trained entities for both new and existing datasets. In each instance, for either a new or existing dataset, you can also create new entities.
Newly created entities can be based on an existing pre-trained entity or can be trained from scratch (like a new label).
You can do this by clicking the '+' icon in the entity box, either in the 'Create dataset' flow or in the dataset settings page (as shown above).
This will bring up the 'Add a new entity' modal as shown below.
Here you can set the entity base, title, and API name, as well as selecting whether the entity is trainable or not (these can be updated later as shown above).
When you've filled in each of the fields (explained below), simply click 'Create'.
Entity base
- This will serve as the initial state for your new entity, and the dropdown will contain a list of all the pre-trained entities
available to you
- For example, if you select 'Date' as your base entity, all of the entities predicted for this kind will be dates, and you could then train the platform to only recognise specific dates
-
If you want to train an entity entirely from scratch, you can select 'None - Train from scratch', and then you essentially start with a blank canvas when training the entity. The platform's predictions for this entity will be entirely based on the training examples you provide
Entity title
- The entity title is the name of the entity that will appear in the UI of the platform
API name
- The API name of the entity is what will be returned via the API when it provides predictions for messages
- The API name cannot contain any spaces or punctuation except for dash ( - ) and underscore ( _ )