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# Relation Features

Relations are associative concepts. In the NLP API you can think of them as a set of relationships between one or more entities and the attributes specific to those relationships. Relations can be simple, involving only 2 entities in a single relationship, or complex, involving multiple relationships, and multiple entities. An example of a simple relation is the qualifier relation. This relation consists of two arguments where one is the entity being described, and the other is the descriptive term. An example of a complex relation is a follow-up relation which models a follow-up recommendation and consists of three different relationships: the reason for the follow-up, the recommended procedure and timeline.

The NLP API supports the following feature relation types:

* [Experiencer relation](/nlp/database/schema/relations/experiencer)
* [Measurement relation](/nlp/database/schema/relations/measurement)
* [Medication relation](/nlp/database/schema/relations/medication)
* [Qualifier relation](/nlp/database/schema/relations/qualifier)
* [Anatomic site relation](/nlp/database/schema/relations/anatomic-site)
* [Temporality relation](/nlp/database/schema/relations/temporality)
* [Reported Event relation](/nlp/database/schema/relations/reported-event)
* [Follow-up relation](/nlp/database/schema/relations/followup)
* [Imagelink relation](/nlp/database/schema/relations/imagelink)

Extraction of relations must be enabled during processing, see [Submitting Documents](/nlp/guides/submitting-documents).