Skip to main content


         This documentation site is for previous versions. Visit our new documentation site for current releases.      
 

Out-of-the-box text analytics models

Updated on July 5, 2022

Pega Platform provides trained and ready-to-use text analytics models.

Model nameText analytics featureLanguageRule nameModel description
Sentiment ModelsTopic detectionDutchEnglishFrenchGermanItalianPortugueseSpanishpySentimentModelsAnalyzes text to detect sentiment at topic and phrase level.
pySmallTalkTopic detectionDutchEnglishFrenchGermanItalianPortugueseSpanishpySmallTalkAnalyzes chatbot content to detect and classify small talk topics, for example, greetings or asking for help.

For more information, see Configure your chatbot for detecting small talk.

System EntitiesText extractionEnglishpySystemEntitiesAnalyzes email and chatbot content to detect the following entities:
  • account number
  • address
  • amount
  • city
  • country
  • date
  • day_name
  • designation
  • digit
  • email
  • location
  • month_name
  • organization
  • person
  • person_salutation
  • phone
  • SSN
  • time
  • url
  • us_airport
  • USA_state
  • username
  • zipcode
Unit EntitiesText extractionEnglishpyUnitsAnalyzes text to detect the following unit entities:
  • area
  • data
  • distance
  • money
  • percentage
  • speed
  • temperature
  • volume
  • weight
Email ParserText extractionDutchEnglishFrenchGermanItalianPortugueseSpanishpxEmailParserAnalyzes email content and detects the following email components:
  • body
  • disclaimer
  • signature

Have a question? Get answers now.

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

Did you find this content helpful?

Want to help us improve this content?

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