---
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


---

# Cross-model Conflict Review

# Cross-model Conflict Review {#ariaid-title1}

* Release version: Xanadu
* 
* Updated August 1, 2024
* 
* ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 5 minutes to read

Identify conflicting intents within or across models so you can take corrective actions, resolve such conflicts, and improve your NLU model performance.

## Summary usage {#nlu-intent-conflict-review-resolution__section_cnw_12v_vnb}

As the number of intents within a model increases, two intents may overlap in scope. This may occur when training utterances in one intent are almost identical to utterances in another intent. There may also be conflicting
intents across models and even applications.

Utterances may also be marked as <kbd class="ph userinput">Not relevant</kbd>, meaning that no intent should be predicted. When these irrelevant utterances are too similar to utterances assigned to an intent, they are displayed in
Conflict Review. For more information, see [Irrelevance detection in NLU](https://servicenow-prod.fluidtopics.net/NnoHTqwCVlEJpXb2a9J67w "Keep Virtual Agent chats focused with Irrelevance detection. Use the Irrelevance detection feature to train your NLU model to avoid making predictions for utterances that are not relevant.").

To address and fix these issues, Cross-model Conflict Review runs an analysis on your models.
Use the analysis to identify and resolve these issues prior to model publication and
deployment.

## Installation {#nlu-intent-conflict-review-resolution__section_kxx_jjd_lpb}

Cross-model Conflict Review is part of the NLU Workbench - Advanced Features app available on
the ServiceNow® Store.

To use Cross-model Conflict Review, ensure that the NLU Workbench - Advanced
Features (com.snc.nlu.workbench.advanced) plugin is active on your instance. For more
information, see [Install NLU Workbench - Advanced Features](https://servicenow-prod.fluidtopics.net/00W_IkegTREyjMfI15wftA "You can install the NLU Workbench - Advanced Features application (com.snc.nlu.workbench.advanced) if you have the admin role.") and [Activate the NLU Workbench](https://servicenow-prod.fluidtopics.net/rCLbf7GXrT3OPe5NypV1Iw "Activate the following plugins to activate the NLU Workbench.").

## Roles {#nlu-intent-conflict-review-resolution__section_er5_tx5_zzb}

To access Cross-model Conflict Review, use the nlu_admin or admin role. When assigned to a model, the nlu_editor can resolve conflicts in that model.

## Running the analysis {#nlu-intent-conflict-review-resolution__section_iv3_b2v_vnb}

The Conflict Review screen shows a list view of all conflict reviews created in your instance. When a review is completed, it's added to a running list of reviews. In this example scenario, you're creating the first review in
your instance, so when it's completed, it's shown in the count as 1 of 1 reviews. As more conflicts arise over time, you will see multiple reviews in the list.

Conflict reviews are analyzed on either one or two NLU models. When you run an analysis on a single model, the system shows intents and utterances that are only in that model. When you run an analysis on 2 models, the system shows intents and
utterances that are in both models.

Conflict reviews always run on the last trained version of the model(s) they analyze.

Conflict reviews have two types: Critical and Moderate. The standard approach is to begin with the critical ones.  
When a conflict is detected, you can use one of following actions to resolve the conflict:

* Ignore the conflict
* Delete an identical or nearly identical utterance from one of the intents
* Edit the utterances to make them more distinct from each other
{#nlu-intent-conflict-review-resolution__ul_oht_32h_14b}

In this example scenario, you're resolving a conflict where two different intents contain the exact same utterance.

1. Navigate to AllNLU WorkbenchNLU Advanced FeaturesCross-model Conflict Review.

2. Select Run analysis.

3. In the Model(s) field on the Choose one or two models to analyze for conflicts screen, select two NLU models for the analysis. In this example scenario, you choose the demo_hardware_issue and demo_it_request
models.

4. Select Run Analysis.  
Figure 1. Running conflict analysis

The Conflict Review screen refreshes to show the analysis, including the two models you selected for analysis, the counts of Critical and Moderate conflicts under review, the number of reviews that have been completed, and the
run date for the analysis. If you point to the far right column on the screen you will see options to rerun the analysis, or delete it and start all over.

5. In the Model(s) column, select your two paired models so you can drill down into the review.  
Figure 2. Conflict review

The screen refreshes to show the details of the conflict review. Note the summary of the two models you chose for the analysis, their latest training dates, the types of conflicts they hold, and the version time stamp of the
analysis. Note also the 0 of 1 count, which indicates that this is the first conflict review created in this instance. As the system detects more conflicts over time, and those conflicts are reviewed, the count
increases.

If you were to determine the utterances in the image below are fine as they are, then you should click Ignore. Clicking Ignore tells the system you've completed your review, so it marks it as reviewed and
moves on to the next conflict review. However, in this scenario, you don't ignore the conflict, because intents that share the same utterance are a conflict worthy of review.  
Figure 3. Reviewing conflict details

To determine how you will resolve this conflict, consider the 2 intent names and the identical utterances they share. Consider which intent is more likely to use the laptop is really slow utterance. If you compare
the 2 intent names closely, you might realize that a laptop that's really slow isn't the same as a laptop that doesn't work. However, a laptop that's really slow is indeed a laptop issue. So in this example scenario, you decide
to dig deeper into the intents to scan the context of their other utterances.

Note also that when an intent uses unique utterances, it helps the system to more accurately predict which utterances belong to it. Hence, you will need to edit or delete the utterance from 1 of the 2 intents. In this example
scenario, you decide to dig into the #laptop_not_working intent.

6. Select laptop_not_working.  
Figure 4. Reviewing overlapping utterances

The #laptop_not_working Intent screen appears, showing its current 3 utterances. You make the decision to delete the laptop is really slow utterance from the #laptop_not_working intent.  
Figure 5. Reviewing the target utterance

7. Click the Delete this utterance trash can icon.  
Figure 6. Resolving conflicts

The Confirm Delete screen appears.

8. Select Delete.  
Figure 7. Deleting conflicts

The Confirm Delete screen disappears, and the Utterances count drops from 3 to 2 because you've deleted the laptop is really slow utterance from the intent.  
Figure 8. Confirmation of deleting an utterance

9. Select Train.

A banner appears on the Intent screen, confirming the model is successfully trained.

10. Select Conflict Review in the navigator.  
Figure 9. Confirmation of successfully training a model

Result:

The Conflict Review list screen appears, showing your conflict review analysis is complete, and that it's been reviewed.  
Figure 10. Confirmation that a conflict has been reviewed

*[\>]: and then