Hey I’ve been working on a chatbot project lately and I came across semantic parsing (http://nbviewer.jupyter.org/github/wcmac/sippycup/blob/master/sippycup-uni

Hey I’ve been working on a chatbot project lately and I came across semantic parsing (http://nbviewer.jupyter.org/github/wcmac/sippycup/blob/master/sippycup-unit-0.ipynb http://nbviewer.jupyter.org/github/wcmac/sippycup/blob/maste...) . Even Though we didn’t use it , I found it to be more robust and capable to handle very complicated utterances. The main disadvantage of using a grammar based approach is that it’s hard to extend the grammar to incorporate new intents and also creating a grammar is time consuming . But the approach used in various NLU services such as Snips and RASA is much more simpler. This can work fine for easy queries but once we start asking complicated questions using conjunctions and disjunctions these systems start becoming brittle. If they try to capture all the possible logical forms through intents they’ll need an exponential number of intents and also a huge dataset to capture all the intents. I would like to know your take on using a grammar based semantic parsing.