An overview of the Text Analysis toolset

The Text Analysis toolset contains tools that perform natural language processing on text. Text can be classified or transformed, and entities such as addresses can be extracted.

Tools in the Text Analysis toolset

Tool	Description
Classify Text Using Deep Learning	Runs a trained text classification model on a text field in a feature class or table and updates each record with an assigned class or category label.
Extract Entities Using Deep Learning	Runs a trained named entity recognizer model on text files in a folder to extract entities and locations (such as addresses, place or person names, dates, and monetary values) in a table. If the extracted entities contain an address, the tool geocodes the addresses using the specified locator and produces a feature class as an output.
Train Entity Recognition Model	Trains a named entity recognition model to extract a predefined set of entities from raw text.
Train Text Classification Model	Trains a text classification model to assign a predefined category or label to unstructured text.
Train Text Transformation Model	Trains a text transformation model to transform, translate, or summarize text.
Transform Text Using Deep Learning	Runs a trained sequence-to-sequence model on a text field in a feature class or table and updates it with a new field containing the converted, transformed, or translated text.