A: You know , all the pointing is gonna be lost .
F: Oh , yeah .
E: Yeah .
F: Yeah , that 's why I said " point to Robert " , when I did it .
B: Well every time Nancy giggles it means it means that it 's your job .
A: Uh .
A: Yeah .
A: Mmm , isn't I mean , I 'm I was sort of dubious why why he even introduces this sort of reality , you know , as your basic mental space
A: and then builds up E: Mm - hmm .
A: d doesn't start with some because it 's so obvi it should be so obvious , at least it is to me , <comment> that whenever I say something I could preface that with " I think . "
E: Yeah .
A: Nuh ?
A: So there should be no categorical difference between your base and all the others that ensue .
E: Yeah .
C: No , but there 's there 's a Gricean thing going on there ,
C: that when you say " I think " you 're actually hedging .
F: Mmm .
E: Yeah , I mean F: It 's like I don't totally think E: Yeah .
C: Right .
F: I mostly think , uh E: Y
A: Yeah , it 's Absolutely .
E: Yeah , it 's an it 's an evidential .
E: It 's sort of semi - grammaticalized .
E: People have talked about it this way .
E: And you know , you can do sort of special things .
E: You can , th
E: put just the phrase " I think " as a parenthetical in the middle of a sentence and so on , and so forth .
F: Actually one of the child language researchers who works with T Tomasello studied a bunch of these constructions
A: Yeah .
E: So F: and it was like it 's not using any kind of interesting embedded ways
F: just to mark , you know , uncertainty or something like that .
E: Yeah .
F: So .
A: Yeah , but about linguistic hedges ,
A: I mean , those those tend to be , um , funky anyways
A: because they blur C: So we don't have that in here either do we ?
E: Yeah .
F: Hedges ?
C: Yeah , yeah .
F: Hhh , <comment> I there used to be a slot for speaker , um ,
F: it was something like factivity .
F: I couldn't really remember what it meant
F: so I took it out .
E: Yeah .
F: But it 's something E: Um .
E: Well we were just talking about this sort of evidentiality and stuff like that , right ?
F: we we were talking about sarcasm too , right ?
F: Oh , oh .
E: I mean ,
F: Oh , yeah , yeah , right .
E: that 's what I think is ,
E: um , sort of telling you what percent reality you should give this
C: So we probably should .
F: Yeah .
E: or the , you know A: Mm - hmm .
C: Confidence or something like that .
E: Yeah ,
E: and the fact that I 'm , you know the fact maybe if I think it versus he thinks that might , you know , depending on how much you trust the two of us or whatever ,
F: Yeah .
E: you know A: Uh great word in the English language is called " about " .
A: If you study how people use that it 's also F: What 's the word ?
A: " about . "
C: About .
A: It 's about C: Oh , that in that use of " about " , yeah .
A: clever .
F: Oh , oh , oh , as a hedge .
E: Yeah .
C: And I think And I think y if you want us to spend a pleasant six or seven hours you could get George started on that .
E: He wrote a paper about thirty - five years ago on that one .
B: I r I read that paper ,
C: Yeah .
B: the hedges paper ?
E: Yeah .
B: I read some of that paper actually .
E: Would you believe that that paper lead directly to the development of anti - lock brakes ?
C: Yeah .
F: What ?
C: No .
E: Ask me about it later
E: I 'll tell you how .
E: When we 're not on tape .
F: I 'd love to know .
B: Oh , man .
F: So , and and I think , uh , someone had raised like sarcasm as a complication at some point .
C: There 's all that stuff .
C: Yeah , let 's I I don't I think F: And
F: we just won't deal with sarcastic people .
C: Yeah , I mean E: I don't really know what like E: We we don't have to care too much about the speaker attitude , right ?
E: Like there 's not so many different F: Certainly not as some E: hhh , <comment> I don't know , m
F: Well , they 're intonational markers I think for the most part .
E: Yeah .
F: I don't know too much about the like grammatical E: I just mean E: There 's lots of different attitudes that that the speaker could have and that we can clearly identify , and so on , and so forth .
F: Yeah .
E: But like what are the distinctions among those that we actually care about for our current purposes ?
C: Right .
C: Right , so , uh , this this raises the question of what are our current purposes .
F: Mm - hmm .
C: Right ?
F: Oh , yeah , do we have any ?
E: Oh , shoot .
E: Here it is three - fifteen already .
A: Mmm .
A: Yeah .
C: Uh , so , um ,
C: I I don't know the answer
C: but but , um , it does seem that ,
C: you know , this is this is coming along .
C: I think it 's it 's converging .
C: It 's as far as I can tell there 's this one major thing we have to do
C: which is the mental the whole s mental space thing .
C: And then there 's some other minor things .
F: Mm - hmm .
C: Um , and we 're going to have to s sort of bound the complexity .
C: I mean , if we get everything that anybody ever thought about you know , w we 'll go nuts .
E: Yeah .
C: So we had started with the idea that the actual , uh , constraint was related to this tourist domain
C: and the kinds of interactions that might occur in the tourist domain ,
C: assuming that people were being helpful and weren't trying to d
C: you know , there 's all sorts of God knows , irony , and stuff like E: Yeah .
C: which you isn't probably of much use in dealing with a tourist guide .
E: Yeah .
C: Yeah ?
C: Uh .
F: M mockery .
C: Right .
C: Whatever .
C: So
C: y uh , no end of things th that that , you know , we don't deal with .
A: But it C: And C: Go ahead .
A: i isn't that part easy though
A: because in terms of the s simspec , it would just mean you put one more set of brack brackets around it ,
A: and then just tell it to sort of negate whatever the content of that is in terms of irony
E: Yeah .
C: N no .
F: Mmm .
A: or E: Right .
C: No .
F: Maybe .
F: Yeah , in model theory cuz the semantics is always like " speaker believes not - P " ,
C: No .
F: you know ?
F: Like " the speaker says P and believes not - P " .
C: Right .
E: We have a theoretical model of sarcasm now .
F: But E: Yeah , right , I mean .
F: Right , right , but ,
C: Right .
C: No , no .
C: Anyway , so so , um , I guess
C: uh , let me make a proposal on how to proceed on that ,
C: which is that , um ,
C: it was Keith 's , uh , sort of job over the summer to come up with this set of constructions .
C: Uh , and my suggestion to Keith is that you , over the next couple weeks , n
E: Mmm .
C: don't try to do them in detail or formally
C: but just try to describe which ones you think we ought to have .
E: OK .
C: Uh , and then when Robert gets back we 'll look at the set of them .
E: OK .
C: Just just sort of , you know , define your space .
E: Yeah , OK .
C: And , um , so th these are this is a set of things that I think we ought to deal with .
E: Yeah .
C: And then we 'll we 'll we 'll go back over it
C: and w people will will give feedback on it .
E: OK .
C: And then then we 'll have a at least initial spec of of what we 're actually trying to do .
E: Yeah .
C: And that 'll also be useful for anybody who 's trying to write a parser .
E: Mm - hmm .
C: Knowing uh E: In case there 's any around .
F: If we knew anybody like that .
C: Right ,
C: " who might want "
C: et cetera .
C: So , uh E: OK .
C: So a and we get this this , uh , portals fixed
C: and then we have an idea of the sort of initial range .
C: And then of course Nancy you 're gonna have to , uh , do your set of C: but you have to do that anyway .
F: For the same , yeah , data . Yeah , mm - hmm .
C: So so we 're gonna get the w we 're basically dealing with two domains ,
C: the tourist domain and the and the child language learning .
B: Mmm .
C: And we 'll see what we need for those two .
C: And then my proposal would be to , um , not totally cut off more general discussion
C: but to focus really detailed work on the subset of things that we 've we really want to get done .
E: Mm - hmm .
E: Mm - hmm .
C: And then as a kind of separate thread , think about the more general things and and all that .
E: Mm - hmm .
A: Well , I also think the detailed discussion will hit you know , bring us to problems that are of a general nature
C: Uh , without doubt .
A: and maybe even F: Yeah .
C: Yeah .
C: But what I want to do is is is to to constrain the things that we really feel responsible for .
A: even suggest some solutions .
A: Yeah .
A: Mmm .
E: Mm - hmm .
C: So that that we say these are the things we 're really gonna try do by the end of the summer
C: and other things we 'll put on a list of of research problems or something ,
C: because you can easily get to the point where nothing gets done
C: because every time you start to do something you say , " oh , yeah , but what about this case ? "
E: Mm - hmm .
C: This is this is called being a linguist .
A: Mmm .
E: Yeah .
C: And , uh ,
E: Basically .
F: Or me .
C: Huh ?
F: Or me .
F: Anyways B: There 's that quote in Jurafsky and Martin where where it goes where some guy goes , " every time I fire a linguist the performance of the recognizer goes up . "
C: Right .
F: Yeah .
E: Exactly .
C: Right .
C: But anyway .
C: So , is is that does that make sense as a , uh a general way to proceed ?
F: Sure , yeah .
E: Yeah , yeah , we 'll start with that ,
E: just figuring out what needs to be done
E: then actually the next step is to start trying to do it .
C: Exactly right .
E: Got it .
A: Mmm .
A: Mmm .
E: OK .
A: We have a little bit of news , uh , just minor stuff .
A: The one big B: Ooo , can I ask a E: You ran out of power .
A: Huh ?
B: Can I ask a quick question about this side ?
F: Yes .
A: Yeah .
B: Is this , uh was it intentional to leave off things like " inherits "
B: and F: Oops .
F: Um ,
E: No .
F: not really F: just on the constructions , right ?
B: Yeah ,
F: Um ,
B: like constructions can inherit from other things ,
B: am I right ?
F: yeah .
B: Yeah .
F: I didn't want to think too much about that for for now .
B: OK .
F: So , uh , maybe it was subconsciously intentional .
C: Yeah .
C: Yeah , uh E: Um , yeah , there should be I I wanted to s find out someday if there was gonna be some way of dealing with , uh , if this is the right term , multiple inheritance ,
C: yeah .
E: where one construction is inheriting from , uh from both parents ,
C: Mm - hmm .
F: Uh - huh .
F: Yep .
E: uh , or different ones ,
E: or three or four different ones .
C: Yeah .
F: Yeah .
E: Cuz the problem is that then you have to C: So let me F: Refer to them .
E: which of you know , which are how they 're getting bound together .
C: Yeah , right , right , right .
F: Yeah , and and there are certainly cases like that .
C: Yeah , yeah , yeah .
F: Even with just semantic schemas we have some examples .
C: Right .
F: So ,
F: and we 've been talking a little bit about that anyway .
C: Yeah . So what I would like to do is separate that problem out .
F: Inherits .
C: So um ,
E: OK .
C: my argument is there 's nothing you can do with that that you can't do by just having more constructions .
E: Yeah , yes .
C: It 's uglier and it d doesn't have the deep linguistic insights and stuff .
E: That 's right .
C: Uh ,
E: But whatever .
F: Uh , those are over rated .
E: Yeah , no , no , no no .
C: Right .
E: No , by all means ,
E: right . Uh , sure .
C: And so I what I 'd like to do is is in the short run focus on getting it right .
C: And when we think we have it right then saying , " aha ! ,
E: Yeah .
C: can we make it more elegant ? "
E: Yeah , that 's E: Yeah .
C: Can can we , uh What are the generalizations , and stuff ?
E: Connect the dots .
E: Yeah .
C: But rather than try to guess a inheritance structure and all that sort of stuff before we know what we 're doing .
E: Yep .
E: Yeah .
C: So I would say in the short run we 're not gonna b
E: Yeah .
C: First of all , we 're not doing them yet at all .
C: And and it could be that half way through we say , " aha ! ,
C: we we now see how we want to clean it up . "
E: Mm - hmm .
C: Uh , and inheritance is only one I mean , that 's one way to organize it
C: but there are others .
E: Yeah .
C: And it may or may not be the best way .
C: I 'm sorry ,
C: you had news .
A: Mmm .
A: Oh , just small stuff .
A: Um , thanks to Eva on our web site we can now ,
A: if you want to run JavaBayes , uh , you could see get download these classes .
A: And then it will enable you A: she modified the GUI so it has now a m a m a button menu item for saving it into the embedded JavaBayes format .
D: Mm - hmm .
B: Mmm .
A: So that 's wonderful .
C: Great .
A: And , um and she , a You tested it out .
A: Do you want to say something about that , that it works , right ?
D: I was just checking like , when we wanna , um , get the posterior probability of , like , variables .
A: With the D: You know how you asked whether we can , like , just observe all the variables like in the same list ?
D: You can't .
D: You have to make separate queries every time .
A: Uh - huh .
A: OK , that 's that 's a bit unfortunate
D: So D: Yeah .
A: but
A: for the time being it 's it 's it 's fine to do it D: You just have to have a long list of , you know , all the variables .
A: Yeah .
D: Basically .
A: But uh F: Uh , all the things you want to query , you just have to like ask for separately .
D: Yeah , yeah .
A: Well that 's probably maybe in the long term that 's good news
A: because it forces us to think a little bit more carefully how how we want to get an out output .
A: Um , but that 's a different discussion for a different time .
A: And , um ,
A: I don't know .
A: We 're really running late ,
A: so I had , uh , an idea yesterday
A: but , uh , I don't know whether we should even start discussing .
C: W what C: Yeah , sure , tell us what it is .
A: Um , the construal bit that , um , has been pointed to but hasn't been , um , made precise by any means , um , may w may work as follows .
A: I thought that we would , uh A: that the following thing would be in incredibly nice
A: and I have no clue whether it will work at all or nothing .
A: So that 's just a tangent , a couple of mental disclaimers here .
A: Um , imagine you you write a Bayes - net ,
A: um F: Bayes ?
A: Bayes - net ,
F: OK .
A: um , completely from scratch every time you do construal .
A: So you have nothing .
A: Just a white piece of paper .
C: Mmm ,
C: right .
A: You consult consult your ontology
A: which will tell you a bunch of stuff , and parts , and properties , uh - uh - uh
F: Grout out the things that that you need .
C: Right .
A: then y you 'd simply write , uh , these into onto your your white piece of paper .
A: And you will get a lot of notes and stuff out of there .
A: You won't get you won't really get any C P
A: T 's , therefore we need everything that that configures to what the situation is ,
A: IE , the context dependent stuff .
A: So you get whatever comes from discourse
A: but also filtered .
A: Uh , so only the ontology relevant stuff from the discourse
F: Mm - hmm .
A: plus the situation and the user model .
A: And that fills in your CPT 's with which you can then query , um , the the net that you just wrote
A: and find out how thing X is construed as an utterance U .
A: And the embedded JavaBayes works exactly like that ,
A: that once you A: we have , you know , precise format in which to write it ,
A: so we write it down .
A: You query it .
A: You get the result ,
A: and you throw it away .
A: And the the nice thing about this idea is that you don't ever have to sit down and think about it or write about it .
A: You may have some general rules as to how things can be can be construed as what , so that will allow you to craft the the the initial notes .
A: But it 's in that respect it 's completely scalable .
A: Because it doesn't have any prior , um , configuration .
A: It 's just you need an ontology of the domain
A: and you need the context dependent modules .
A: And if this can be made to work at all , that 'd be kind of funky .
C: Um , it sounds to me like you want P R
A: P R Ms - uh , PRM
A: I mean , since you can unfold a PRM into a straightforward Bayes - net C: Beca - because it b because C: No , no , you can't .
C: See the the critical thing about the PRM is it gives these relations in general form .
C: So once you have instantiated the PRM with the instances and ther then you can then you can unfold it .
A: Then you can .
A: Mm - hmm , yeah .
A: No , I was m using it generic .
A: So , uh , probabilistic , whatever , relational models .
A: Whatever you write it .
C: Well , no , but it matters a lot
A: In C: because you what you want are these generalized rules
C: about the way things relate ,
C: th that you then instantiate in each case .
A: And then then instantiate them .
C: Yeah , and that 's A: That 's ma maybe the the way the only way it works .
C: Yeah , that 's the only way it could work .
C: I we have a our local expert on P R
C: uh , but my guess is that they 're not currently good enough to do that .
C: But we 'll we 'll have to see .
C: Uh A: But , uh ,
C: Yes .
C: This is that 's that would be a good thing to try .
C: It 's related to the Hobbs abduction story
C: in that you th you throw everything into a pot
C: and you try to come up with the , uh A: Except there 's no no theorem prover involved .
F: Best explanation .
C: No , there isn't a theorem prover
C: but there but but the , um , The cove the the P R Ms are like rules of inference
C: and you 're you 're coupling a bunch of them together .
A: Mm - hmm , yeah .
C: And then ins instead of proving you 're trying to , you know , compute the most likely .
C: Uh C: Tricky .
C: But you yeah , it 's a good it 's a it 's a good thing to put in your thesis proposal .
A: What 's it ?
C: So are you gonna write something for us before you go ?
A: Yes .
A: Um .
C: Oh , you have something .
A: In the process thereof , or whatever .
C: OK .
C: So , what 's what when are we gonna meet again ?
F: When are you leaving ?
F: Thursday ,
A: Fri - uh ,
F: Friday ?
D: Fri
A: Thursday 's my last day here .
F: OK .
C: Yeah .
A: So A: I would suggest as soon as possible .
A: Do you mean by we , the whole ben gang ?
C: N no , I didn't mean y just the two of us .
C: We obviously we can we can do this .
C: But the question is do you want to , for example , send the little group , uh , a draft of your thesis proposal
C: and get , uh , another session on feedback on that ?
C: Or