NLP outcomes database tables
Obtain information about the outcomes of natural language processing (NLP) by running
reports on the database tables in which Pega Platform stores the
results of text analysis. You can analyze the NLP outcomes in business intelligence (BI)
tools to gain insights into your interactions with customers, or use them for auditing
purposes to meet contractual requirements. Two database tables hold the NLP outcomes. The tables have a one-to-many relationship
and are linked through the summary ID: Records in the Summary table contain high-level information about each interaction,
such as the input text for the NLP analysis, source channel, language, and overall
sentiment. The pyOutcome property in a record contains the
overall NLP outcome in a binary large object (BLOB). In the NLP outcome, for every topic, entity, or intent detected, there is an entry in
the Details table. Each record contains the following properties: Review the results of the text analysis of messages that come through your email
or chat channels by accessing records in the Summary database table that stores the NLP
outcomes. Typically, you retrieve the NLP outcomes data by querying the Pega Platform database from a database client. However, for educational
purposes, you can view individual NLP Result records in Dev Studio.Table name Class Description pr_data_nlp_summary Data-NLP-Report-Summary The Summary table contains one record for the overall NLP outcome
of each interaction. pr_data_nlp_details Data-NLP-Report-Details The Details table contains records for each topic, entity, or
intent detected in an NLP outcome. Each record is mapped to the
summary record through the summary ID. Summary table
Details table
Viewing NLP outcomes in the Summary database table
Previous topic Natural language processing reference Next topic Machine-learning models for text analytics