How to detect fallback language in NLP of email bot?

We would like to use the NLP to automatically detect the language of the emails received from our customers in the our Customer Service (CS) application.

In particular we would like to distinguish the cases when the algorithm uses the fallback language (e.g. English ) from the cases where it detects the same language (english).

Our idea was to disable the fallback language and distinguishing the situations based on the output result of NLP: empty (when it was not able to detect the language) and non-empty (when it detects the language), but in the CS we are not able to disable this option (every time that we enable it, then after the refresh of the rule the checkbox appears checked again).

Can you help with this?

@AleMax225 This is something our SME may have to respond to.

@IvarS334 @gudis1 @mitra2 can you provide some input?

Below the GenAI response:

To disable the fallback language in the Customer Service application, you need to follow these steps:

  1. In the navigation pane of App Studio, click Channels.
  2. In the Current channel interfaces section, click the icon for your existing Email channel.
  3. In the Email channel, click the Behavior tab.
  4. Open the text analyzer rule.
  5. In the text analyzer rule, click the Advanced tab.
  6. In the Language settings section, uncheck the ‘Enable fallback language if the language is undetected’ checkbox.
  7. Click Save.

If the checkbox appears checked again after refreshing the rule, it might be a system issue. In this case, I recommend contacting Pega Support for further assistance.

:warning: This is a GenAI-powered tool. All generated answers require validation against the provided references.

Enabling automatic language detection for text analysis

@MarijeSchillern this is exactly what I have been trying until now, but is seems that for the CS this thing is not working properly…

@AleMax225 please log a support incident via the MSP and provide the INC id here so that we can help track it.

@MarijeSchillern Opened incident:

INC-B32451

The problem is in Prediction Studio, where the changes are not properly reflected in the underlaying rules.

We find out that the problem described above, can be solved by directly modifying the Text Analyzer rule from DEV STUDIO.

The problem is not present anymore in Pega 24.1.1.