Skip to main content

This content has been archived and is no longer being updated.

Links may not function; however, this content may be relevant to outdated versions of the product.

Building machine-learning text extraction models

Suggest edit Updated on April 5, 2022

Use Pega Platform machine-learning capabilities to create text extraction models for named entity recognition.

Before you begin: By using models that are based on the Conditional Random Fields (CRF) algorithm, you can extract information from unstructured data and label it as belonging to a particular group. For example, if the document that you want to analyze mentions Galaxy S8, the text extraction model classifies that as Phone.
Did you find this content helpful? YesNo

Have a question? Get answers now.

Visit the Support Center to ask questions, engage in discussions, share ideas, and help others.

We'd prefer it if you saw us at our best.

Pega.com is not optimized for Internet Explorer. For the optimal experience, please use:

Close Deprecation Notice
Contact us