Hey, I am building a conversational bot that can automate Gsuite related tasks such as creating email ids, mailing groups, adding folks to DL etc. I experimented with some models for intent detection and entity extraction and here are my findings: a) For intent detection, which is a multiclass classification problem in my case, Bert (base+uncased) was the best, followed by ELMO and FastText (FT) supervised. Rasa (starspace) was not far behind FT. I used precision, recall and f-score for measuring performance.
b) For entity extraction, Flair was much better than the ones that I tried which included Rasa (CRF) and Bert.
As far as dialog management is concerned, Rasa is super cool with all its features. So, what I want to do is use Rasa core for dialog management and FT for intent detection + Flair for entity extraction. Bert is good for intent detection but too slow because of the model size. And, FT is also super fast for training models.
So, my question is can I use custom NLU viz. FT for intent and Flair for entity extraction with Rasa core for dialog management.
Appreciate your thoughts and help!