Basic NLP concepts
This page covers the fundamental concepts of Natural language processing (NLP).
Understanding natural language is challenging. It takes us over 12 years to learn 20,000 common words. Imagine how hard it is for computers! Training NLP engines requires massive data. Fortunately, pre-trained models help. Our NLP engine handles spelling errors, synonyms, slang, and word order.
In this page, you'll learn about the basics to learn your bot's NLP model.
NLP model
An NLP model is made of a set of intents and entities which are trained on data so that the model can recognize expressions that were never seen.
Each bot has its own NLP model.
You can set up your NLP model under the NLP tab.

Whenever a user sends a message to the bot, the bot will check if that message can be labelled with an intent that is part of the NLP model.
Intents
An intent is a series of expressions (or utterances) that mean the same intention or goal from the user side. During the conversation, intents are recognised by the NLP engine and serve to steer the conversation in different ways.
You can add intents from the NLP tab.

Expressions
Expressions are example sentences to specific intent: they're all the different ways a user can express their intent.
You can add expressions from the NLP tab.

Entities
Entities are important pieces of information that can be extracted from an expression. You want to store these entities as variables so you can re-use them later on.

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