But I don’t see the point of using multiple intents flag? What is special about that? Where is the difference if I define an intent affirm_booktaxi just with the intent classifier classicaly?
multi intent helps classification performance if intent labels are named consistently: they are composed of smaller tokens that have consist meaning bound to parts of the phrases.
Is there now any difference but performance when you use multiple intents? When I have multiple senteneces like greet and booking in one message, I could train this as greet_booking together with just the subintents greet and booking. Will there be any differences in intent classfication then (with and without the flag)?
Because you introduced this concept as something new when users say different things in one message. Such that you get the feeling there is some splitting internally for different classification…
hi,i have read the source code of the solution of tensorflow pipeline,here are some of my thought.
1.we can also use spacy_sklearn pipeline if we see the multiple intent as a new intent label just like single intent
2.it has better performance if we use tensorflow pipeline which solve the multiple intent case by partitioning.tensorflow pipeline can distinguish similar intent label (such as intent:a+b and intent:a+b+c) better
here are my thought
1.tensorflow pipeline will chunk the intent label (such as a+b) into single label by the specified separator if we use the flag as true.
tensorflow can also solve single intent case,as long as we set the flag as false
Any idea how to handle multiple intents in FormAction.
Consider the case below
User: I want to book a table for two?
Bot: When do you want to book table?
User: Today
Bot: What time?
User: 7 PM. Are you open on Sunday?
Here user answered the one of FormAction questions but asked additional question which is supposed to be handled by different Action after current FormAction completes