Once you have defined your objectives, you can start turning them into labels. Labels should contain all the concepts and intents you want to capture in the dataset to meet your specific objectives. Typical groups of labels that you may include are:
Typical groups of labels to structure your taxonomy
These are typical labels used by our customers, regardless of their use case or industry. Not all of them may be applicable to your model, and you may have other types of labels that are important to meet your objectives.
Each of these types of labels, including what they capture and what they help to answer, are covered in more detail in this section.
Once you’ve defined your labels and your target taxonomy structure, it’s important to define the key data points (i.e. entities) you want to extract from your comms data. These are typically used to facilitate downstream automation, but can also be useful for analytics. For guidance on defining and setting up your entities correctly, please see our training guide