Yes, all the data we use to train our model on, is handcrafted by our AI trainers. What they do is figure out all the different questions that are most common to ask for each intent we want to predict. We have built a tool that helps them creating all these sentences, often we use templates with keywords.
It is still under development, we started at the end of last summer. We use Torch and Python-NLTK.
Why have you chosen torch instead of staying completely in python? I assume that you use nltk for tagging, entity regoncition, ... and torch for your classifier.
What kind of model is possible in LUA-torch that could not be done in python with caffe/tensorflow?
It is still under development, we started at the end of last summer. We use Torch and Python-NLTK.