---
sourceDocument: Xanadu Enable AI
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/xanadu/intelligent-experiences

 Release :

    - xanadu

ft:locale :

    - en-US

ft:publication_title :

    - Xanadu Enable AI

ft:clusterId :

    - platai

bundleId :

    - platai

workflow :

    - Platform


---

# Create a mapped entity

# Create a mapped entity {#ariaid-title1}

* Release version: Xanadu
* 
* Updated August 1, 2024
* 
* ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read

Create an entity mapped to a vocabulary source, or to a list of values you manually
create for the entity. Mapped entities can help provide multiple values the model can use as
context when interpreting utterances.

## Before you begin

* Make sure that the NLU Workbench plugin, NLU Workbench - Core plugin, NLU Common Model plugin, and Predictive Intelligence plugin are all installed and activated on your instance.
* Create or use an existing NLU model for Virtual Agent or AI Search.
* Create or use an existing intent.
* Role required: nlu_editor, nlu_admin, or admin. The nlu_editor must be assigned to the model.
{#create-mapped-entity-lookup-source__ul_shl_vvs_tgb}

## About this task

Mapped entities take the words of the utterance and extract value based on a
designated source. The model uses the source when predicting the intent.  
When you create a mapped entity, you have the following three options for the source.

* Manual list of values: Use this option to manually enter a list of values for the entity. For example, you could create a mapped entity named priority and map it to the word urgent in an utterance, then manually build a list for it with values of High, Medium, and Low.
* Table vocabulary source: Use this option if you have a ServiceNow table that has the values you're looking for. Mapping an entity to a table vocabulary source enables the entity to reference multiple values from the table. For example, use a @Location vocabulary source, where @Location has values for cities and countries.
* List vocabulary source: Use this option if you don't have a ServiceNow table that has the values you're looking for. For example, use a @mouse vocabulary source, where @mouse has values for various models of hand-held computer devices.
{#create-mapped-entity-lookup-source__ul_lxg_vpz_3sb}

In this example procedure, you create a mapped entity for urgency.

## Procedure

1. Navigate to AllNLU WorkbenchModels.  
   The Virtual Agent tab opens by default.
2. Select the tab for your model's application, then the name of your model.
3. On the model details page, select the Intents tab.
4. In the Intents section of the model, select the name of an intent.  
   For this example procedure, you select #SubmitRequest.
5. In the Utterances tab, select a word in an utterance  
   In this scenario, you select the word urgent in the utterance
   I have an urgent request.
6. Select Mapped entities.
7. Select Create New Entity.  
8. On the form, configure the fields.  
   {#create-mapped-entity-lookup-source__table_z33_p1y_h5b__entry__2}

   | Field | Description |
   |-|-|
   | Entity Name | Name for the entity. |
   | Type | Type of entity. |
   | Model availability | Select this option if you want this entity to be included in all intents in your model. |
   | Source | Source of the entity values. |
   | Provide values for this entity | Values used to provide context for the model. |
   [ ]

   {#create-mapped-entity-lookup-source__table_z33_p1y_h5b}  
   For this example procedure, use the following configurations:
   * Entity Name: <kbd class="ph userinput">priority</kbd>
   * Type: Mapped
   * Model availability: Select the check box
   * Source: Use this if you have a table or list to refer to where the actual values and values they're mapped to are stored
   * Mapped value for the entity: <kbd class="ph userinput">high, medium, low</kbd>.
   {#create-mapped-entity-lookup-source__ul_r42_ysb_ynb}

9. Click Save.  
   Result: Your mapped entity saves. The entity appears
   on the Associated entities tab. Now the model can
   leverage machine learning and use the values provided to identify possible
   values.

## What to do next

You can create a mapped entity using a vocabulary source to use the values in the
source as the mapped entity.
**Related concepts**   

* [Using regular expressions in entities](https://servicenow-prod.fluidtopics.net/MLF7GQKcQp5lQTgeBdhGfw "Learn how to use regular expressions in your NLU entities to establish patterns that help the system locate, match, and manage text.")  
**Related tasks**   

* [Create a simple entity](https://servicenow-prod.fluidtopics.net/N~5DJDKjarceXuhwMKE6fg "Create one or more simple entities from words in your utterance examples. An entity is an object of, or context for, an action.")
* [Create a pattern entity](https://servicenow-prod.fluidtopics.net/R06p7nAAw5pbg~ybFCp32Q "Create a pattern entity from a word or phrase with repeatable patterns, such as email addresses and phone numbers. These patterns help the system to recognize similar utterances based on the patterns.")
* [Create a system-derived entity](https://servicenow-prod.fluidtopics.net/L1zE3lTZQATqQxa52hzljg "Create a custom entity that's derived from a default system entity such as date, time, duration, or location.")
* [Create an open-ended entity](https://servicenow-prod.fluidtopics.net/ZSZ60xAPMEW~bNeORY2HfA "Use an open-ended entity when you want to improve intent prediction accuracy. Open-ended entities help your model focus on the context of the utterances.")
* [Import entities](https://servicenow-prod.fluidtopics.net/iz1K~UJviKCvsN2yRoYoCQ "Reuse entities that you have created across your other Natural Language Understanding (NLU) models. Importing entities saves time and helps improve the intents in your model.")
* [Create a table vocabulary source](https://servicenow-prod.fluidtopics.net/f_YY3emeisk2eJFk_Eq3uw "Use the values from a ServiceNow table as a vocabulary source. Your Natural Language Understanding (NLU) models use your provided synonym to interpret utterances that contain values from the chosen source fields of the table.")
* [Create a list vocabulary source](https://servicenow-prod.fluidtopics.net/JUnyc2ohMGoaMY_2s~pRNg "Create a list of words or phrases to act as a vocabulary source. The values in the list source are replaced by the synonym if they are detected in a user utterance.")

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