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  • Tonic Textual guide
  • Getting started with Textual
  • Previewing Textual detection and redaction
  • Entity types that Textual detects
    • Built-in entity types
    • Managing custom entity types
  • Language support in Textual
  • Datasets - Create redacted files
    • Datasets workflow for text redaction
    • Creating and managing datasets
    • Assigning tags to datasets
    • Displaying the file manager
    • Adding and removing dataset files
    • Reviewing the sensitivity detection results
    • Configuring the redaction
      • Configuring added and excluded values for built-in entity types
      • Working with custom entity types
      • Selecting the handling option for entity types
      • Configuring synthesis options
      • Configuring handling of file components
    • Adding manual overrides to PDF files
      • Editing an individual PDF file
      • Creating templates to apply to PDF files
    • Sharing dataset access
    • Previewing the original and redacted data in a file
    • Downloading redacted data
  • Pipelines - Prepare LLM content
    • Pipelines workflow for LLM preparation
    • Viewing pipeline lists and details
    • Assigning tags to pipelines
    • Setting up pipelines
      • Creating and editing pipelines
      • Supported file types for pipelines
      • Creating custom entity types from a pipeline
      • Configuring file synthesis for a pipeline
      • Configuring an Amazon S3 pipeline
      • Configuring a Databricks pipeline
      • Configuring an Azure pipeline
      • Configuring a Sharepoint pipeline
      • Selecting files for an uploaded file pipeline
    • Starting a pipeline run
    • Sharing pipeline access
    • Viewing pipeline results
      • Viewing pipeline files, runs, and statistics
      • Displaying details for a processed file
      • Structure of the pipeline output file JSON
    • Downloading and using pipeline output
  • Textual Python SDK
    • Installing the Textual SDK
    • Creating and revoking Textual API keys
    • Obtaining JWT tokens for authentication
    • Instantiating the SDK client
    • Datasets and redaction
      • Create and manage datasets
      • Redact individual strings
      • Redact individual files
      • Transcribe and redact an audio file
      • Configure entity type handling for redaction
      • Record and review redaction requests
    • Pipelines and parsing
      • Create and manage pipelines
      • Parse individual files
  • Textual REST API
    • About the Textual REST API
    • REST API authentication
    • Redaction
      • Redact text strings
  • Datasets
    • Manage datasets
    • Manage dataset files
  • Snowflake Native App and SPCS
    • About the Snowflake Native App
    • Setting up the app
    • Using the app
    • Using Textual with Snowpark Container Services directly
  • Install and administer Textual
    • Textual architecture
    • Setting up and managing a Textual Cloud pay-as-you-go subscription
    • Deploying a self-hosted instance
      • System requirements
      • Deploying with Docker Compose
      • Deploying on Kubernetes with Helm
    • Configuring Textual
      • How to configure Textual environment variables
      • Configuring the number of textual-ml workers
      • Configuring the number of jobs to run concurrently
      • Configuring the format of Textual logs
      • Setting a custom certificate
      • Configuring endpoint URLs for calls to AWS
      • Enabling PDF and image processing
      • Setting the S3 bucket for file uploads and redactions
      • Required IAM role permissions for Amazon S3
      • Configuring model preferences
    • Viewing model specifications
    • Managing user access to Textual
      • Textual organizations
      • Creating a new account in an existing organization
      • Single sign-on (SSO)
        • Viewing the list of SSO groups in Textual
        • Azure
        • GitHub
        • Google
        • Keycloak
        • Okta
      • Managing Textual users
      • Managing permissions
        • About permissions and permission sets
        • Built-in permission sets and available permissions
        • Viewing the lists of permission sets
        • Configuring custom permission sets
        • Configuring access to global permission sets
        • Setting initial access to all global permissions
    • Textual monitoring
      • Downloading a usage report
      • Tracking user access to Textual
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On this page
  • Viewing the list of custom entity types
  • Creating, editing, and deleting a custom entity type
  • Creating a custom entity type
  • Editing a custom entity type
  • Deleting a custom entity type
  • Custom entity type configuration settings
  • Name and description
  • Regular expressions to identify matching values
  • Testing an expression
  • Enabling and disabling the entity type for pipelines and datasets

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  1. Entity types that Textual detects

Managing custom entity types

Last updated 14 days ago

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Required global permission - either:

  • Create custom entity types

  • Edit any custom entity type

In addition to the built-in entity types, you can also create custom entity types.

Custom entity types are based on regular expressions. If a value matches a configured regular expression for the custom entity type, then it is identified as that entity type.

You can control whether each dataset or pipeline uses each custom entity type.

Viewing the list of custom entity types

To display the list of entity types, in the Textual navigation bar, click Custom Entity Types.

For each custom entity type, the list includes:

  • Entity type name and description.

  • Regular expressions to identify matching values.

  • The number of datasets and pipelines that the entity type is active for.

Creating, editing, and deleting a custom entity type

Creating a custom entity type

Required global permission: Create custom entity types

To create a custom entity type, on the Custom Entity Types page, click Create Custom Entity Type.

The dataset details and pipeline details pages also contain a Create Custom Entity Type option.

  • To save the new type, but not scan dataset and pipeline files for the new type, click Save Without Scanning Files.

  • To both save the new type and scan for it, click Save and Scan Files.

To detect new custom entity types in a dataset or pipeline, Textual needs to run a scan. If you do not run the scan when you save the custom entity type, then:

  • On the dataset details page, you are prompted to run a scan.

  • On the pipeline details page for an uploaded file pipeline, you are prompted to run a scan.

  • For a cloud storage pipeline, a new scan runs when you run the pipeline.

Editing a custom entity type

Required global permission: You can edit any custom entity type that you create.

Users with the global permission Edit any custom entity type can edit any custom entity type.

To edit a custom entity type, on the Custom Entity Types page, click the edit icon for the entity type.

You can also edit a custom entity type from the dataset or pipeline details page.

For an existing entity type, you can change the description, the regular expressions, and the enabled datasets and pipelines.

You cannot change the entity type name, which is used to produce the identifier to use to configure the entity type handling from the SDK.

After you update the configuration:

  • To save the changes, but not scan dataset and pipeline files based on the updated configuration, click Save Without Scanning Files.

  • To both save the new type and scan based on the updated configuration, click Save and Scan Files.

To reflect the changes to custom entity types in a dataset or pipeline, Textual needs to run a scan. If you do not run the scan when you save the changes, then:

  • On the dataset details page, you are prompted to run a scan.

  • On the pipeline details page for an uploaded file pipeline, you are prompted to run a scan.

  • For a cloud storage pipeline, a new scan runs when you run the pipeline.

Deleting a custom entity type

When you delete a custom entity type, it is removed from the datasets and pipelines that it was active for.

To delete a custom entity type:

  1. On the Custom Entity Types page, click the delete icon for the entity type.

  2. On the confirmation panel, click Delete Entity Type.

Custom entity type configuration settings

The custom entity type configuration includes:

  • Name and description

  • Regular expressions to identify matching values. From the configuration panel, you can test the expressions against text that you provide.

  • Datasets and pipelines to make the entity type active for. You can also enable and disable custom entity types from the dataset and pipeline details pages.

Name and description

In the Name field, provide a name for the entity type. Each custom entity type name:

  • Must be unique within an organization.

  • Can only contain alphanumeric characters and spaces. Custom entity type names cannot contain punctuation or other special characters.

After you save the entity type, you cannot change the name. Textual uses the name as the basis for the identifier that you use to refer to the entity type in the SDK.

In the Description field, provide a longer description of the custom entity type.

Regular expressions to identify matching values

Under Keywords, Phrases, or Regexes, provide expressions to identify matching values for the entity type.

An entry can be as simple as a single word or phrase, or you can provide a more complex regular expression to identify the values.

Textual maintains an empty row at the bottom of the list. When you type an expression into the last row, Textual adds a new empty row.

To add an entry, begin to type the value in the empty row.

To edit an entry, click the entry field, then edit the value.

To remove an entry, click its delete icon.

Testing an expression

Under Test Entry, you can check whether Textual correctly identifies a value as the entity type based on the provided expression.

To test an expression:

  1. From the dropdown list, select the entry to test.

  1. In the text area, provide the text to test.

As you enter the text, Textual automatically scans the text for matches to the selected expression. The Result field displays the input text and highlights the matching values.

Enabling and disabling the entity type for pipelines and datasets

Under Activate custom entity, you identify the datasets and pipelines to make the entity active for. From the pipeline details or dataset details, you can also enable and disable custom entity types for that pipeline or dataset.

To make the entity active for all current and future datasets and pipelines, check Automatically activate for all current, and new pipelines and datasets.

To make the entity active for specific pipelines and datasets, set the toggle for the dataset or pipeline to the on position.

To filter the list based on the pipeline or dataset name, in the filter field, begin to type text from the name. Textual updates the list to only include matching datasets and pipelines.

To update all of the currently displayed datasets and pipelines, click Bulk action, then click Enable or Disable.

After you :

You can also enable and disable custom entity types from within a dataset or pipeline. For more information, go to .

configure the entity type
Custom Entity Types page
Details panel for a custom entity type
Regular expressions list for a custom entity type
Dropdown list to select the regular expression to test
Test results for a custom entity type regular expression
Activate Custom Entity Type section to select the datasets and pipeline that include the custom entity type
Enabling and disabling custom entity types