Text Analytics rapidly and accurately captures key concepts from text data by using an extraction process. This process relies on linguistic resources to dictate how large amounts of unstructured, textual data should be analyzed and interpreted.

You can use the Resource editor tab to view the linguistic resources used in the extraction process. These resources are stored in the form of templates and libraries, which are used to extract concepts, group them under types, discover patterns in the text data, and other processes. Text Analytics offers several preconfigured resource templates, and in some languages, you can also use the resources in text analysis packages.

Custom libraries and templates

Since these resources might not fit the context of your data perfectly, you can create and manage your own resources for a particular context or domain in the Resource editor tab.

You can save any changes that you make to a library or template as a project asset, which you can then reuse in other flows. You can also import custom libraries or templates in case you manage your resources by using local files.