Text annotation is identifying and labelling sentences with additional information or metadata to define the characteristics of sentences. This information could be highlighting parts of speech in a sentence, grammar syntax, keywords, phrases, emotions, sarcasm, sentiments and more depending on the scope of a project. Machine learning modules are fed with such AI training data, where they learn diverse aspects of sentences, sentence formation, and more to understand human conversations better.

Types of Text Annotation

Annotations for text include a wide range of types, such as sentiment, intent, semantic, and relationship. These options are available across a wide array of human languages.

Sentiment Annotation
Sentiment annotation evaluates attitudes and emotions behind a text by labelling that text as positive, negative, or neutral.

Intent Annotation
Intent annotation analyzes the need or desire behind a text, classifying it into several categories, such as request, command, or confirmation.

Semantic Annotation
Semantic annotation attaches various tags to text that reference concepts and entities, such as people, places, or topics.

Relationship Annotation
Relationship annotation seeks to draw various relationships between different parts of your document. Typical tasks include dependency resolution and coreference resolution. The type of project and associated use cases will determine which text annotation technique should be selected.