elplaguister/DTS_line_datasets · Datasets at Hugging Face

topic_shift bool 2 classes	utterance stringlengths 1 7.9k	session_id stringlengths 7 14
false	Yeah , but But how does the expert but how does the expert system know how who which one to declare the winner , if it doesn't know the question it is , and how that question should be answered ?	QMSum_134
false	Based on the k what the question was , so what the discourse , the ontology , the situation and the user model gave us , we came up with these values for these decisions.	QMSum_134
false	Yeah I know. But how do we weight what we get out ? As , which one i Which ones are important ? So my i So , if we were to it with a Bayes - net , we 'd have to have a node for every question that we knew how to deal with , that would take all of the inputs and weight them appropriately for that question.	QMSum_134
false	Mm - hmm.	QMSum_134
false	Does that make sense ? Yay , nay ?	QMSum_134
false	Um , I mean , are you saying that , what happens if you try to scale this up to the situation , or are we just dealing with arbitrary language ?	QMSum_134
false	We	QMSum_134
false	Is that your point ?	QMSum_134
false	Well , no. I I guess my question is , Is the reason that we can make a node f or OK. So , lemme see if I 'm confused. Are we going to make a node for every question ? Does that make sense ?	QMSum_134
false	For every question ?	QMSum_134
false	Or not.	QMSum_134
false	Like	QMSum_134
false	Every construction.	QMSum_134
false	Hmm. I don't Not necessarily , I would think. I mean , it 's not based on constructions , it 's based on things like , uh , there 's gonna be a node for Go - there or not , and there 's gonna be a node for Enter , View , Approach.	QMSum_134
false	Wel W OK. So , someone asked a question.	QMSum_134
false	Yeah.	QMSum_134
false	How do we decide how to answer it ?	QMSum_134
false	Well , look at look Face yourself with this pr question. You get this You 'll have y This is what you get. And now you have to make a decision. What do we think ? What does this tell us ? And not knowing what was asked , and what happened , and whether the person was a tourist or a local , because all of these factors have presumably already gone into making these posterior probabilities. What what we need is a just a mechanism that says , " Aha ! There is "	QMSum_134
false	Yeah. I just don't think a " winner - take - all " type of thing is the	QMSum_134
false	I mean , in general , like , we won't just have those three , right ? We 'll have , uh , like , many , many nodes. So we have to , like So that it 's no longer possible to just look at the nodes themselves and figure out what the person is trying to say.	QMSum_134
false	Yep. Because there are interdependencies , right ? The uh Uh , no. So if if for example , the Go - there posterior possibility is so high , um , uh , w if it 's if it has reached reached a certain height , then all of this becomes irrelevant. So. If even if if the function or the history or something is scoring pretty good on the true node , true value	QMSum_134
false	Wel I don't know about that , cuz that would suggest that I mean	QMSum_134
false	He wants to go there and know something about it ?	QMSum_134
false	Do they have to be mutual Yeah. Do they have to be mutually exclusive ?	QMSum_134
false	I think to some extent they are. Or maybe they 're not.	QMSum_134
false	Cuz I , uh The way you describe what they meant , they weren't mutu uh , they didn't seem mutually exclusive to me.	QMSum_134
false	Well , if he doesn't want to go there , even if the Enter posterior proba So.	QMSum_134
false	Wel	QMSum_134
false	Go - there is No. Enter is High , and Info - on is High.	QMSum_134
false	Well , yeah , just out of the other three , though , that you had in the	QMSum_134
false	Hmm ?	QMSum_134
false	those three nodes. The - d They didn't seem like they were mutually exclusive.	QMSum_134
false	No , there 's No. But It 's through the	QMSum_134
false	So th s so , yeah , but some So , some things would drop out , and some things would still be important.	QMSum_134
false	Mm - hmm.	QMSum_134
false	But I guess what 's confusing me is , if we have a Bayes - net to deal w another Bayes - net to deal with this stuff ,	QMSum_134
false	Mm - hmm.	QMSum_134
false	you know , uh , is the only reason OK , so , I guess , if we have a Ba - another Bayes - net to deal with this stuff , the only r reason we can design it is cuz we know what each question is asking ?	QMSum_134
false	Yeah. I think that 's true.	QMSum_134
false	And then , so , the only reason way we would know what question he 's asking is based upon Oh , so if Let 's say I had a construction parser , and I plug this in , I would know what each construction the communicative intent of the construction was	QMSum_134
false	Mm - hmm.	QMSum_134
false	and so then I would know how to weight the nodes appropriately , in response. So no matter what they said , if I could map it onto a Where - Is construction , I could say , " ah !	QMSum_134
false	Ge Mm - hmm.	QMSum_134
false	well the the intent , here , was Where - Is " ,	QMSum_134
false	OK , right.	QMSum_134
false	and I could look at those.	QMSum_134
false	Yeah. Yes , I mean. Sure. You do need to know I mean , to have that kind of information.	QMSum_134
false	Hmm. Yeah , I 'm also agreeing that a simple pru Take the ones where we have a clear winner. Forget about the ones where it 's all sort of middle ground. Prune those out and just hand over the ones where we have a winner. Yeah , because that would be the easiest way. We just compose as an output an XML mes message that says. " Go there now. " " Enter historical information. " And not care whether that 's consistent with anything. Right ? But in this case if we say , " definitely he doesn't want to go there. He just wants to know where it is. " or let 's call this this " Look - At - H " He wants to know something about the history of. So he said , " Tell me something about the history of that. " Now , the e But for some reason the Endpoint - Approach gets a really high score , too. We can't expect this to be sort of at O point three , three , three , O point , three , three , three , O point , three , three , three. Right ? Somebody needs to zap that. You know ? Or know There needs to be some knowledge that	QMSum_134
false	We Yeah , but , the Bayes - net that would merge I just realized that I had my hand in between my mouth and my micr er , my and my microphone. So then , the Bayes - net that would merge there , that would make the decision between Go - there , Info - on , and Location , would have a node to tell you which one of those three you wanted , and based upon that node , then you would look at the other stuff.	QMSum_134
false	Yep. Yep.	QMSum_134
false	I mean , it i Does that make sense ?	QMSum_134
false	Yep. It 's sort of one of those , that 's It 's more like a decision tree , if if you want. You first look o at the lowball ones ,	QMSum_134
false	Yeah , i	QMSum_134
false	and then	QMSum_134
false	Yeah , I didn't intend to say that every possible OK. There was a confusion there , k I didn't intend to say every possible thing should go into the Bayes - net , because some of the things aren't relevant in the Bayes - net for a specific question. Like the Endpoint is not necessarily relevant in the Bayes - net for Where - Is until after you 've decided whether you wanna go there or not.	QMSum_134
false	Mm - hmm.	QMSum_134
false	Right.	QMSum_134
false	Show us the way , Bhaskara.	QMSum_134
false	I guess the other thing is that um , yeah. I mean , when you 're asked a specific question and you don't even Like , if you 're asked a Where - Is question , you may not even look like , ask for the posterior probability of the , uh , EVA node , right ? Cuz , that 's what I mean , in the Bayes - net you always ask for the posterior probability of a specific node. So , I mean , you may not even bother to compute things you don't need.	QMSum_134
false	Um. Aren't we always computing all ?	QMSum_134
false	No. You can compute , uh , the posterior probability of one subset of the nodes , given some other nodes , but totally ignore some other nodes , also. Basically , things you ignore get marginalized over.	QMSum_134
false	Yeah , but that 's that 's just shifting the problem. Then you would have to make a decision ,	QMSum_134
false	Yeah. So you have to make	QMSum_134
false	" OK , if it 's a Where - Is question , which decision nodes do I query ? "	QMSum_134
false	Yeah. Yes. But I would think that 's what you want to do.	QMSum_134
false	That 's un	QMSum_134
false	Right ?	QMSum_134
false	Mmm.	QMSum_134
false	Well , eventually , you still have to pick out which ones you look at.	QMSum_134
false	Yeah.	QMSum_134
false	So it 's pretty much the same problem ,	QMSum_134
false	Yeah it 's it 's it 's apples and oranges.	QMSum_134
false	isn't it ?	QMSum_134
false	Nuh ? I mean , maybe it does make a difference in terms of performance , computational time.	QMSum_134
false	Mm - hmm.	QMSum_134
false	So either you always have it compute all the posterior possibilities for all the values for all nodes , and then prune the ones you think that are irrelevant ,	QMSum_134
false	Mmm.	QMSum_134
false	or you just make a p @ @ a priori estimate of what you think might be relevant and query those.	QMSum_134
false	Yeah.	QMSum_134
false	So basically , you 'd have a decision tree query , Go - there. If k if that 's false , query this one. If that 's true , query that one. And just basically do a binary search through the ?	QMSum_134
false	I don't know if it would necessarily be that , uh , complicated. But , uh I mean , it w	QMSum_134
false	Well , in the case of Go - there , it would be. In the case Cuz if you needed an If y If Go - there was true , you 'd wanna know what endpoint was. And if it was false , you 'd wanna d look at either Lo - Income Info - on or History.	QMSum_134
false	Yeah. That 's true , I guess. Yeah , so , in a way you would have that.	QMSum_134
false	Also , I 'm somewhat boggled by that Hugin software.	QMSum_134
false	OK , why 's that ?	QMSum_134
false	I can't figure out how to get the probabilities into it. Like , I 'd look at	QMSum_134
false	Mm - hmm.	QMSum_134
true	It 's somewha It 's boggling me.	QMSum_134
false	OK. Alright. Well , hopefully it 's fixable.	QMSum_134
false	Ju	QMSum_134
false	It 's there 's a	QMSum_134
false	Oh yeah , yeah. I d I just think I haven't figured out what the terms in Hugin mean , versus what Java Bayes terms are.	QMSum_134
false	OK.	QMSum_134
false	Um , by the way , are Do we know whether Jerry and Nancy are coming ?	QMSum_134
false	So we can figure this out.	QMSum_134
false	Or ?	QMSum_134
false	They should come when they 're done their stuff , basically , whenever that is. So.	QMSum_134
false	What d what do they need to do left ?	QMSum_134
false	Um , I guess , Jerry needs to enter marks , but I don't know if he 's gonna do that now or later. But , uh , if he 's gonna enter marks , it 's gonna take him awhile , I guess , and he won't be here.	QMSum_134
false	And what 's Nancy doing ?	QMSum_134

false

Yeah , but But how does the expert but how does the expert system know how who which one to declare the winner , if it doesn't know the question it is , and how that question should be answered ?

QMSum_134

false

Based on the k what the question was , so what the discourse , the ontology , the situation and the user model gave us , we came up with these values for these decisions.

QMSum_134

false

Yeah I know. But how do we weight what we get out ? As , which one i Which ones are important ? So my i So , if we were to it with a Bayes - net , we 'd have to have a node for every question that we knew how to deal with , that would take all of the inputs and weight them appropriately for that question.

QMSum_134

false

Mm - hmm.

QMSum_134

false

Does that make sense ? Yay , nay ?

QMSum_134

false

Um , I mean , are you saying that , what happens if you try to scale this up to the situation , or are we just dealing with arbitrary language ?

QMSum_134

false

We

QMSum_134

false

Is that your point ?

QMSum_134

false

Well , no. I I guess my question is , Is the reason that we can make a node f or OK. So , lemme see if I 'm confused. Are we going to make a node for every question ? Does that make sense ?

QMSum_134

false

For every question ?

QMSum_134

false

Or not.

QMSum_134

false

Like

QMSum_134

false

Every construction.

QMSum_134

false

Hmm. I don't Not necessarily , I would think. I mean , it 's not based on constructions , it 's based on things like , uh , there 's gonna be a node for Go - there or not , and there 's gonna be a node for Enter , View , Approach.

QMSum_134

false

Wel W OK. So , someone asked a question.

QMSum_134

false

Yeah.

QMSum_134

false

How do we decide how to answer it ?

QMSum_134

false

Well , look at look Face yourself with this pr question. You get this You 'll have y This is what you get. And now you have to make a decision. What do we think ? What does this tell us ? And not knowing what was asked , and what happened , and whether the person was a tourist or a local , because all of these factors have presumably already gone into making these posterior probabilities. What what we need is a just a mechanism that says , " Aha ! There is "

QMSum_134

false

Yeah. I just don't think a " winner - take - all " type of thing is the

QMSum_134

false

I mean , in general , like , we won't just have those three , right ? We 'll have , uh , like , many , many nodes. So we have to , like So that it 's no longer possible to just look at the nodes themselves and figure out what the person is trying to say.

QMSum_134

false

Yep. Because there are interdependencies , right ? The uh Uh , no. So if if for example , the Go - there posterior possibility is so high , um , uh , w if it 's if it has reached reached a certain height , then all of this becomes irrelevant. So. If even if if the function or the history or something is scoring pretty good on the true node , true value

QMSum_134

false

Wel I don't know about that , cuz that would suggest that I mean

QMSum_134

false

He wants to go there and know something about it ?

QMSum_134

false

Do they have to be mutual Yeah. Do they have to be mutually exclusive ?

QMSum_134

false

I think to some extent they are. Or maybe they 're not.

QMSum_134

false

Cuz I , uh The way you describe what they meant , they weren't mutu uh , they didn't seem mutually exclusive to me.

QMSum_134

false

Well , if he doesn't want to go there , even if the Enter posterior proba So.

QMSum_134

false

Wel

QMSum_134

false

Go - there is No. Enter is High , and Info - on is High.

QMSum_134

false

Well , yeah , just out of the other three , though , that you had in the

QMSum_134

false

Hmm ?

QMSum_134

false

those three nodes. The - d They didn't seem like they were mutually exclusive.

QMSum_134

false

No , there 's No. But It 's through the

QMSum_134

false

So th s so , yeah , but some So , some things would drop out , and some things would still be important.

QMSum_134

false

Mm - hmm.

QMSum_134

false

But I guess what 's confusing me is , if we have a Bayes - net to deal w another Bayes - net to deal with this stuff ,

QMSum_134

false

Mm - hmm.

QMSum_134

false

you know , uh , is the only reason OK , so , I guess , if we have a Ba - another Bayes - net to deal with this stuff , the only r reason we can design it is cuz we know what each question is asking ?

QMSum_134

false

Yeah. I think that 's true.

QMSum_134

false

And then , so , the only reason way we would know what question he 's asking is based upon Oh , so if Let 's say I had a construction parser , and I plug this in , I would know what each construction the communicative intent of the construction was

QMSum_134

false

Mm - hmm.

QMSum_134

false

and so then I would know how to weight the nodes appropriately , in response. So no matter what they said , if I could map it onto a Where - Is construction , I could say , " ah !

QMSum_134

false

Ge Mm - hmm.

QMSum_134

false

well the the intent , here , was Where - Is " ,

QMSum_134

false

OK , right.

QMSum_134

false

and I could look at those.

QMSum_134

false

Yeah. Yes , I mean. Sure. You do need to know I mean , to have that kind of information.

QMSum_134

false

Hmm. Yeah , I 'm also agreeing that a simple pru Take the ones where we have a clear winner. Forget about the ones where it 's all sort of middle ground. Prune those out and just hand over the ones where we have a winner. Yeah , because that would be the easiest way. We just compose as an output an XML mes message that says. " Go there now. " " Enter historical information. " And not care whether that 's consistent with anything. Right ? But in this case if we say , " definitely he doesn't want to go there. He just wants to know where it is. " or let 's call this this " Look - At - H " He wants to know something about the history of. So he said , " Tell me something about the history of that. " Now , the e But for some reason the Endpoint - Approach gets a really high score , too. We can't expect this to be sort of at O point three , three , three , O point , three , three , three , O point , three , three , three. Right ? Somebody needs to zap that. You know ? Or know There needs to be some knowledge that

QMSum_134

false

We Yeah , but , the Bayes - net that would merge I just realized that I had my hand in between my mouth and my micr er , my and my microphone. So then , the Bayes - net that would merge there , that would make the decision between Go - there , Info - on , and Location , would have a node to tell you which one of those three you wanted , and based upon that node , then you would look at the other stuff.

QMSum_134

false

Yep. Yep.

QMSum_134

false

I mean , it i Does that make sense ?

QMSum_134

false

Yep. It 's sort of one of those , that 's It 's more like a decision tree , if if you want. You first look o at the lowball ones ,

QMSum_134

false

Yeah , i

QMSum_134

false

and then

QMSum_134

false

Yeah , I didn't intend to say that every possible OK. There was a confusion there , k I didn't intend to say every possible thing should go into the Bayes - net , because some of the things aren't relevant in the Bayes - net for a specific question. Like the Endpoint is not necessarily relevant in the Bayes - net for Where - Is until after you 've decided whether you wanna go there or not.

QMSum_134

false

Mm - hmm.

QMSum_134

false

Right.

QMSum_134

false

Show us the way , Bhaskara.

QMSum_134

false

I guess the other thing is that um , yeah. I mean , when you 're asked a specific question and you don't even Like , if you 're asked a Where - Is question , you may not even look like , ask for the posterior probability of the , uh , EVA node , right ? Cuz , that 's what I mean , in the Bayes - net you always ask for the posterior probability of a specific node. So , I mean , you may not even bother to compute things you don't need.

QMSum_134

false

Um. Aren't we always computing all ?

QMSum_134

false

No. You can compute , uh , the posterior probability of one subset of the nodes , given some other nodes , but totally ignore some other nodes , also. Basically , things you ignore get marginalized over.

QMSum_134

false

Yeah , but that 's that 's just shifting the problem. Then you would have to make a decision ,

QMSum_134

false

Yeah. So you have to make

QMSum_134

false

" OK , if it 's a Where - Is question , which decision nodes do I query ? "

QMSum_134

false

Yeah. Yes. But I would think that 's what you want to do.

QMSum_134

false

That 's un

QMSum_134

false

Right ?

QMSum_134

false

Mmm.

QMSum_134

false

Well , eventually , you still have to pick out which ones you look at.

QMSum_134

false

Yeah.

QMSum_134

false

So it 's pretty much the same problem ,

QMSum_134

false

Yeah it 's it 's it 's apples and oranges.

QMSum_134

false

isn't it ?

QMSum_134

false

Nuh ? I mean , maybe it does make a difference in terms of performance , computational time.

QMSum_134

false

Mm - hmm.

QMSum_134

false

So either you always have it compute all the posterior possibilities for all the values for all nodes , and then prune the ones you think that are irrelevant ,

QMSum_134

false

Mmm.

QMSum_134

false

or you just make a p @ @ a priori estimate of what you think might be relevant and query those.

QMSum_134

false

Yeah.

QMSum_134

false

So basically , you 'd have a decision tree query , Go - there. If k if that 's false , query this one. If that 's true , query that one. And just basically do a binary search through the ?

QMSum_134

false

I don't know if it would necessarily be that , uh , complicated. But , uh I mean , it w

QMSum_134

false

Well , in the case of Go - there , it would be. In the case Cuz if you needed an If y If Go - there was true , you 'd wanna know what endpoint was. And if it was false , you 'd wanna d look at either Lo - Income Info - on or History.

QMSum_134

false

Yeah. That 's true , I guess. Yeah , so , in a way you would have that.

QMSum_134

false

Also , I 'm somewhat boggled by that Hugin software.

QMSum_134

false

OK , why 's that ?

QMSum_134

false

I can't figure out how to get the probabilities into it. Like , I 'd look at

QMSum_134

false

Mm - hmm.

QMSum_134

true

It 's somewha It 's boggling me.

QMSum_134

false

OK. Alright. Well , hopefully it 's fixable.

QMSum_134

false

Ju

QMSum_134

false

It 's there 's a

QMSum_134

false

Oh yeah , yeah. I d I just think I haven't figured out what the terms in Hugin mean , versus what Java Bayes terms are.

QMSum_134

false

OK.

QMSum_134

false

Um , by the way , are Do we know whether Jerry and Nancy are coming ?

QMSum_134

false

So we can figure this out.

QMSum_134

false

Or ?

QMSum_134

false

They should come when they 're done their stuff , basically , whenever that is. So.

QMSum_134

false

What d what do they need to do left ?

QMSum_134

false

Um , I guess , Jerry needs to enter marks , but I don't know if he 's gonna do that now or later. But , uh , if he 's gonna enter marks , it 's gonna take him awhile , I guess , and he won't be here.

QMSum_134

false

And what 's Nancy doing ?

QMSum_134