Annotation is the process of adding information to your text so that it can be used to analyze further data or train a model.
What is annotation?
Annotation is the process of assigning tags to text data in order to train a machine-learning model.
Annotations turn unstructured data into information that can be used to gain informed insights, and extract useful information that can be further analyzed.
What are annotations used for?
Annotations have multiple applications with regard to transforming your data into information.
You can use them to analyze data as well as help a machine learning (or AI) model to train.
Key parts of annotation
Annotation is divided into two main processes: Text Classification and Text Structuration.
Each of these processes is used to transform unstructured data into information.
In the video series below you can go deeper into both of these processes, as well as their corresponding components, to better understand how annotation works and extract useful insights from your data.
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