Intently Natural Language Understanding (NLU)

Welcome to Intently NLU’s documentation.

Intently NLU is a Natural Language Understanding python library that allows to parse sentences written in natural language, and extract structured information. It is a fork of Snips NLU.

The motivation of this project is to create a robust, fast and easy-to-use nlu library similar to Snips NLU with support for newer Python versions or tools, since Snips NLU has not been updated for a long time.

Let’s look at the following example, to illustrate the main purpose of this lib:

"What will be the weather in berlin at 9pm?"

Properly trained, the Intently NLU engine will be able to extract structured data such as:

{
  "intent": "weather/intents/searchWeatherForecast",
  "probability": 0.95,
  "raw_utterance": "What will be the weather in berlin at 9pm?",
  "resolved_slots": {
    "locality": "berlin",
    "forecast_start_datetime": "9pm"
  }
}

About this documentation

This documentation is divided into different parts. It is recommended to start by the first two ones.

The Installation part will get you set up. Then, the Quickstart section will help you build an example.

After this, you can either start the Tutorial which will guide you through the steps to create your own NLU engine and start parsing sentences, or you can alternatively check the Key Concepts & Data Model to know more about the NLU concepts used in this lib.

If you want to dive into the codebase or customize some parts, you can check the github repository.