Best practices on NLU utterances

Hi all,

We have recently started using Virtual Agent with NLU. There are three separate NLU models with an intent each. Each intent is connected to a different Virtual Agent topic.

For each intent, we have a good number of utterances around 100 each, each utterance having 3 words or more. Most utterances are simple I need x or I got y. We copied some of the out-of-the-box NLU intents with addition of some common search terms used by users. We have tried to stay away from some of the common pitfalls of avoiding one word utterances and abbreviations.

The NLU was working quite well until we introduced the 2nd and 3rd Virtual Agent topic and now we can see a 100% match for quite a few phrases leading to the Virtual Agent coming up with 'I want to be sure I got this right. What item best describes what you want to do?'. We have tried adjusting the NLU Intent confidence delta threshold but didn't have any luck. 

Does anyone have an idea how we can resolve our NLU approach? Should we have one model with all the intents to make the testing easier? Should we consolidate the utterances to 20-30s instead of adding most of the common search terms?

Regards,

Ayman