Tags:

• aura-nlp

Categories:

• components

Aura NLP

What is Aura NLP?

Aura NLP (Natural Language Processing) is the module of Aura Cognitive Services in charge of processing and understanding human natural language in simplified use cases.

Aura’s interaction with users is based on the intent & entity model: a user’s request expressed in natural language is understood by Aura in terms of identifying the user’s intent and the associated entities.

An NLP model contains three basic components: stages, connectors and pipelines. Stages provide different methods for the recognition of intents and entities in the user’s utterance. They are linked through different types of connectors composing an NLP pipeline.

When developing a use case, linguists or NLP experts must build up the NLP model and train it, that is, teach Aura to understand. Afterwards, the model is tested through an ongoing and cyclical process until its accuracy is good enough in terms of recognition of the use case intent and entities.

Throughout this section, you can access to detailed information, both descriptive and practical, regarding Aura NLP:

📄 Aura NLP basic concepts and components. Key concepts that must be known by linguists in order to manage Aura NLP.
📄 Configuration of the NLP system. Description of NLP operational configuration (internal) and introduction to the configuration of NLP stages.
📄 API definition
📄 Moreover, access our practical guidelines for NLP experts and linguists: Train Aura to understand: Use cases development over Aura NLP.

Overview of intent and entities recognition

Aura’s conversational process with the user is composed of three overall stages: the user makes a request to Aura; Aura recognizes the user’s intent and associated entities; Aura provides the user with the requested answer or service.

Two are the main actors in the process: while aura-bot is the component in charge of handling the conversational flow with the user, Aura NLP is responsible for the understanding process, which is schematically shown below.

1. Aura user asks for a service/request (utterance) through a specific channel.

2. aura-bot receives the request and handles it. For its understanding, aura-bot summons Aura NLP.

3. Aura NLP recognizes the intents and associated entities in the user request and sends the information back to aura-bot.