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Entities are used to extract user information from natural language.

A distinction is usually made between System Entities and custom entities. System entities are entities already contained in the system for addresses, times and numbers, for example.

Custom entities, on the other hand, can be defined by the user and contain, for example, product information or a staff directory, depending on the use case.

Entities in NLP Services

The Entity Recognition is already integrated in the current NLP Services [1][2][3] and is, besides the Intent Matching, the main component of the Natural Language Processing for chatbots.

Example for an Entity Extraction

I would like to order a small Pizza Margherita to Berliner Straße 1.

Entities:

small (Custom Entity pizza_size)

Margherita (Custom Entity pizza_type)

Berliner Straße 1 (System Entity street_address)

 

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Sources

[1] https://dialogflow.com/docs/intents

[2] https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-utterance

[3] https://cloud.ibm.com/docs/services/assistant?topic=assistant-intents