Entities

An entity is a textual reference to the unique name of a real-world object such as people, places, and commercial items, and to precise references to measures such as dates and quantities.

For example, in the text "John moved to 1313 Mockingbird Lane in 2012," "John" might be recognized as a PERSON, "1313 Mockingbird Lane" might be recognized as a LOCATION, and "2012" might be recognized as a DATE.

Each entity also has a score that indicates the level of confidence that Amazon Comprehend has that it correctly detected the entity type. You can filter out the entities with lower scores to reduce the risk of using incorrect detections.

The following table lists the entity types.

Type	Description
COMMERCIAL_ITEM	A branded product
DATE	A full date (for example, 11/25/2017), day (Tuesday), month (May), or time (8:30 a.m.)
EVENT	An event, such as a festival, concert, election, etc.
LOCATION	A specific location, such as a country, city, lake, building, etc.
ORGANIZATION	Large organizations, such as a government, company, religion, sports team, etc.
OTHER	Entities that don't fit into any of the other entity categories
PERSON	Individuals, groups of people, nicknames, fictional characters
QUANTITY	A quantified amount, such as currency, percentages, numbers, bytes, etc.
TITLE	An official name given to any creation or creative work, such as movies, books, songs, etc.

Detect entities operations can be performed using any of the primary languages supported by Amazon Comprehend. This includes only predefined (non-custom) entity detection. All documents must be in the same language.

You can use any of the following API operations to detect entities in a document or set of documents.

• DetectEntities

• BatchDetectEntities

• StartEntitiesDetectionJob

The operations return a list of API Entity objects, one for each entity in the document. The BatchDetectEntities operation returns a list of Entity objects, one list for each document in the batch. The StartEntitiesDetectionJob operation starts an asynchronous job that produces a file containing a list of Entity objects for each document in the job.

The following example is the response from the DetectEntities operation.

{
    "Entities": [
        {
            "Text": "today",
            "Score": 0.97,
            "Type": "DATE",
            "BeginOffset": 14,
            "EndOffset": 19
        },
        {
            "Text": "Seattle",
            "Score": 0.95,
            "Type": "LOCATION",
            "BeginOffset": 23,
            "EndOffset": 30
        }
    ],
    "LanguageCode": "en"
}