Named Entity Recognizer

Extract entities from documents

This Amazon SageMaker model package can extract entities from sentences, documents, webpages, tweets, etc… and categorize entities such as dates, locations, names and more…

Extract entities from documents

This SageMaker model package allows you to identify and extract entities in a document, tweet, or other text.

It provides each entity’s category as well as the location in the text.

For example:

"I was in London yesterday"

Entity      Type   Start End
London	    GPE    9     15
yesterday	DATE   16    25

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Entities supported include:

  • PERSON People, including fictional.
  • NORP Nationalities or religious or political groups.
  • FAC Buildings, airports, highways, bridges, etc.
  • ORG Companies, agencies, institutions, etc.
  • GPE Countries, cities, states.
  • LOC Non-GPE locations, mountain ranges, bodies of water.
  • PRODUCT Objects, vehicles, foods, etc. (Not services.)
  • EVENT Named hurricanes, battles, wars, sports events, etc.
  • WORK_OF_ART Titles of books, songs, etc.
  • LAW Named documents made into laws.
  • LANGUAGE Any named language.
  • DATE Absolute or relative dates or periods.
  • TIME Times smaller than a day.
  • PERCENT Percentage, including ”%“.
  • MONEY Monetary values, including unit.
  • QUANTITY Measurements, as of weight or distance.
  • ORDINAL “first”, “second”, etc.
  • CARDINAL Numerals that do not fall under another type.

The model currently only supports English.

How to use this SageMaker model package

After subscribing to the product, you can make predictions using the AWS SageMaker API, or host a REST API for your application.

You can also use SageMaker to do batch processing (batch transform) of your documents and process multiple text segments at once.

See the Amazon SageMaker documentation for more information.


  • What is a SageMaker model package?

    • You can use SageMaker model packages to build a deployable model in SageMaker.
    • You can use the deployable model for real-time inference by hosting it on SageMaker hosting services.
    • You can also get inferences for an entire dataset by running batch transform jobs.

    See also Deploy a Model in Amazon SageMaker

  • How much does it cost?

    The model is currently priced per hour. See the product page on AWS Marketplace for more information.

    Contact us if you require a customized pricing model.