@crazypro - The question to ask for me was - "what is the most important phrase and what does it mean?" In the example, "happy hour" and "mission" are the two t

@crazypro - The question to ask for me was - "what is the most important phrase and what does it mean?" In the example, "happy hour" and "mission" are the two things I need. Using some sort of knowledge base is hard because I can't predict every query the user may throw at me, and there will always be issues with disambiguation. For locations, I could have a gazetteer which would make life easier. What I meant was that existing libs, in my limited experience, can't do entity recognition (even those that use classifier based chunkers) unless you've got a good dataset of similar conversations. Which I don't yet. So my option was to build something that would take an arbitrary sentence and do so while only having limited training. Does that make sense? I'm utilizing word/phrase vectors - haven't moved to sentence vectors yet. And they are in the same space. I'm not entirely sure what compositional embedding entails, so presumably I'm not doing that. I would however love to chat offline and get more insight from you on it.