Huh. Still , I have no recollection whatsoever of the email. I 'll have to go back and check.
Not important. So , what is important is that we understand what the proposed task is. And , the  the i uh , Robert and I talked about this some on Friday. And we think it 's well - formed. So we think it 's a well - formed , uh , starter task for this , uh , deeper understanding in the tourist domain.
So , where exactly is the , uh , deeper understanding being done ? Like I mean , s is it before the Bayes - net ? Is it , uh
Well , it 's the  it 's  it 's always all of it. So , in general it 's always going to be , the answer is , everywhere. Uh , so the notion is that , uh , this isn't real deep. But it 's deep enough that you can distinguish between these th three quite different kinds of , uh , going to see some tourist thing. And , so that 's  that 's the quote " deep " that we 're trying to get at. And , Robert 's point is that the current front - end doesn't give you any way to  Not only doesn't it do it , but it also doesn't give you enough information to do it. It isn't like , if you just took what the front - end gives you , and used some clever inference algorithm on it , you would be able to figure out which of these is going on. So , uh , and this is  Bu - I in general it 's gonna be true of any kind of deep understanding , there 's gonna be contextual things , there 're gonna be linguistic things , there 're gonna be discourse things , and they gotta be combined. And , my idea on how to combine them is with a belief - net , although it may turn out that t some totally different thing is gonna work better. Um , the idea would be that  you , uh , take your  You 're editing your slide ?