An event is a dynamic situation that unfolds. Rosette event extraction analyzes unstructured text and extracts event mentions. An event model is trained to extract specific types of events. To use the endpoint, you must first train a model to extract the event types you are interested in. Events are dependent on both the structure of your data, as well as the information you are interested in extracting. There is no standard or default model for event extraction.
An event mention consists of a key phrase and one or more role mentions.
A key phrase is a word or phrase in the text that evokes the given event type.
Roles are entity mentions. i.e. people, places, times, and other mentions, which add detail to the key phrase. Roles have a name indicating the type of role.
As an example, let's consider a trip event:
Bob flew from Boston to Los Angeles.
The key phrase is flew. Other lemmas of flew would also be identified as key phrases: flying and flies, for example.
The roles are:
Los Angeles, destination
The key phrases (flew) and roles (traveler, origin, Los Angeles) were all defined in advance and a model trained to extract them. The event mention would identify the role mentions: Bob, Boston, Los Angeles.
The event type for flying could have other roles defined, such as when (a date or time). Not all roles must be extracted for all event mentions. The schema, which defines the key phrases and roles, defines which roles are required. If a role is required, the event will not be extracted without a role mention.