Hmm.
Yeah.
And so what uh uh a s you s let 's say a simple parse from a s from an utterance won't really give us is what the person actually wants. Does he wanna go there to see it ? Does he wanna go there now ? Later ? How does the person wanna go there ? Is that person more likely to want to walk there ? Walk a scenic route ? and so forth. There are all kinds of decisions that we have identified in terms of getting to places and in terms of finding information about things. And we are constructing  and then we 've identified more or less the extra - linguistic parameters that may f play a role. Information related to the user and information related to the situation. And we also want to look closely on the linguistic information that what we can get from the utterance. That 's part of why we implant these intentions in the data collection to see whether people actually phrase things differently whether they want to enter in order to buy something or whether they just wanna go there to look at it. And um so the idea is to construct uh um suitable interfaces and a belief - net for a module that actually tries to guess what the underlying intention  was. And then enrich or augment the M - three - L structures with what it thought what more it sort of got out of that utterance. So if it can make a good suggestion , " Hey ! " you know , " that person doesn't wanna enter. That person just wants to take a picture , " cuz he just bought film , or " that person wants to enter because he discussed the admission fee before ". Or " that person wants to enter because he wants to buy something and that you usually do inside of buildings " and so forth. These ah these types of uh these bits of additional information are going to be embedded into the M - three - L structure in an  sort of subfield that we have reserved. And if the action planner does something with it , great. If not you know , then that 's also something um that we can't really  at least we  want to offer the extra information. We don't really  um we 're not too worried.
Mm - hmm.