How does Multi-Intent classification work?

Rasa Open Source
1

Hi - I was hoping to get some more details on how multi-intent classification works ‘under the hood’.

I’ve had a look at the docs, and the suggested tutorial as well as the GitHub repo for that tutorial. Unfortunately, I haven’t found any of those sources particularly enlightening when it comes to how the multi-intent classification itself works.

In the source code I’ve see that the intent names seem to be split into tokens here but I am unclear as to what the implications of this are. I think my query is quite similar to this previous question here

I would be really grateful if anyone was able to shed some more light on the topic for me. Thanks in advance!

2

Bump! Hoping that someone see this and gives me some advice!

3

The Tensorflow Pipeline Tutorial is deprecated as multi-intent classification is done now by DIETClassifier (I guess?). But I’m also interested in more details like:

  • training data for intent “ask_question”
  • training data for intent “topic_book_hotel”
  • do we need more training data for the multi-intent “ask_question+topic_book_hotel” - how much?

Other case:

  • training data for “inform”
  • training data for “thanks”
  • do we need for each story the turn “thanks+inform” (for example) for
    • utter_welcome
    • utter_process_information
  • or is it possible to have one story only for thanks and utter_welcome that is merged with other stories if we have multiple intents like the one above?

Thanks :slight_smile: