Document Transformations and Information States

Staffan Larsson & Annie Zaenen / October 2000 / page 1 /

RINDI

Document Transformations and Document Transformations and Information StatesInformation States

Document Transformations and Document Transformations and Information StatesInformation States

Staffan Larsson, Annie Zaenen

SIGdial workshop, ACL 2000, Hong Kong


RINDI

Goals of this talkGoals of this talkGoals of this talkGoals of this talk

• sketch a model of the relation between monologue and dialogue in instructional discourse, based on the TRINDI information state approach

• investigate possibilities of using domain task plans to generate discourse with various degrees of interactivity

• adapt an existing TrindiKit dialogue system, designed for information-seeking dialogue, to handle instructional dialogue and monologue

• NB. We are not dealing with educational (a.k.a. instructional) dialogue


RINDI Overview of talkOverview of talkOverview of talkOverview of talk

• motivationmotivation

• monologue and dialoguemonologue and dialogue

• the TRINDI information state approachthe TRINDI information state approach

• IMDiS (Instructional Monologue and Dialogue System) IMDiS (Instructional Monologue and Dialogue System)

• from domain plan to monologue and dialogue plansfrom domain plan to monologue and dialogue plans

• monologue and dialogue behaviour in IMDiSmonologue and dialogue behaviour in IMDiS

• conclusions & prospectsconclusions & prospects


RINDI Practical motivation for document Practical motivation for document transformationtransformationPractical motivation for document Practical motivation for document transformationtransformation

• Practical advantages of being able to adapt the Practical advantages of being able to adapt the “same” document to different uses and media“same” document to different uses and media

• Costly to develop presentations from scratch for each Costly to develop presentations from scratch for each new medianew media


RINDI Theoretical issues Theoretical issues Theoretical issues Theoretical issues

• Written discourse and human-human dialogue are the Written discourse and human-human dialogue are the extremes of the scale of interactivityextremes of the scale of interactivity

• We explore some intermediate levels of interactivity We explore some intermediate levels of interactivity using the TRINDI information state approach using the TRINDI information state approach

• How can we model the differences between these How can we model the differences between these levels, independently of domain-specific knowledge?levels, independently of domain-specific knowledge?

• Concepts:Concepts:– interactivity in monologue and dialogueinteractivity in monologue and dialogue

– interactivity vs. initiativeinteractivity vs. initiative

– spoken vs. written discoursespoken vs. written discourse

– maxim of quantity in monologue and dialogue maxim of quantity in monologue and dialogue


RINDI Degrees of interactivityDegrees of interactivityDegrees of interactivityDegrees of interactivity

• Dialogue is interactive, since participants can Dialogue is interactive, since participants can influence each other’s movesinfluence each other’s moves

• Monologue is typically non-interactiveMonologue is typically non-interactive

• Written monologue is minimally interactive; reader can Written monologue is minimally interactive; reader can influence order & speed of reading influence order & speed of reading

highnone

written monologue

human-humandialogue

spoken monologue

inter-activityminimal


RINDI Interactivity vs. initiativeInteractivity vs. initiativeInteractivity vs. initiativeInteractivity vs. initiative

• Interactivity does not imply shared initiative; it is Interactivity does not imply shared initiative; it is possible to have a dialogue with both task and possible to have a dialogue with both task and dialogue initiative staying on one sidedialogue initiative staying on one side

• In instructional dialogue, task initiative is typically held In instructional dialogue, task initiative is typically held by instructor; dialogue initiative may shiftby instructor; dialogue initiative may shift


RINDI Spoken vs. written instructional Spoken vs. written instructional discoursediscourseSpoken vs. written instructional Spoken vs. written instructional discoursediscourse

• separate dimension from interactivity (and initiative)separate dimension from interactivity (and initiative)

• written monologue has advantage of providing written monologue has advantage of providing minimal interactivityminimal interactivity

• spoken monologue (e.g. tape recording) has spoken monologue (e.g. tape recording) has advantage of leaving hands and eyes free to do other advantage of leaving hands and eyes free to do other thingsthings– prerecorded repetitions and reformulations can be used as a prerecorded repetitions and reformulations can be used as a

substitute for interactivitysubstitute for interactivity


RINDI Quantity of information in monologueQuantity of information in monologueQuantity of information in monologueQuantity of information in monologue

• manuals are cooperative, and are based on implicit manuals are cooperative, and are based on implicit assumptions about the readerassumptions about the reader

• setting: instructor has know-how information which setting: instructor has know-how information which instructee does notinstructee does not

• all information, and preferably only that information, all information, and preferably only that information, which is needed by the instructee to complete the task which is needed by the instructee to complete the task should be transferred (Grice’s maxim of quantity)should be transferred (Grice’s maxim of quantity)– however, if education is an issue, additional information however, if education is an issue, additional information

(explanations) should be supplied (explanations) should be supplied

• in manuals, instructor must keep provide more in manuals, instructor must keep provide more information than may be necessary for any given information than may be necessary for any given instructee instructee (cf. Young ’97, how to generate text from (cf. Young ’97, how to generate text from dynamically generated plans which are very detailed)dynamically generated plans which are very detailed)


RINDI Quantity of information in dialogueQuantity of information in dialogueQuantity of information in dialogueQuantity of information in dialogue

• interactivity makes it possible for instructee to control interactivity makes it possible for instructee to control the amount of information given by the instructorthe amount of information given by the instructor

• instructee must be able to inform instructor about her instructee must be able to inform instructor about her state, thus influencing the instructors movesstate, thus influencing the instructors moves

• instructor needs to keep track of the state of the instructor needs to keep track of the state of the instructee to determine what information to provideinstructee to determine what information to provide


RINDI From written manual to spoken From written manual to spoken dialogue – 3 levels of interactivitydialogue – 3 levels of interactivityFrom written manual to spoken From written manual to spoken dialogue – 3 levels of interactivitydialogue – 3 levels of interactivity

• 1. written/spoken monologue1. written/spoken monologue– no overt interaction (but minimal interaction in written m.)no overt interaction (but minimal interaction in written m.)

• 2. recapture minimal interactivity in spoken 2. recapture minimal interactivity in spoken presentationpresentation– system can ask yes/no questions and deals with simple user system can ask yes/no questions and deals with simple user

feedback (“done”, “OK”, “what did you say?”)feedback (“done”, “OK”, “what did you say?”)

• 3. increase interactivity3. increase interactivity– user can control level of detail by indicating whether she user can control level of detail by indicating whether she

already knows certain subproceduresalready knows certain subprocedures

– requires more detailed domain task planrequires more detailed domain task plan


RINDI Example from a Xerox manualExample from a Xerox manualExample from a Xerox manualExample from a Xerox manual

• Reinstalling the print headReinstalling the print head

• Caution: make sure that the green carriage lock lever is STILL moved all Caution: make sure that the green carriage lock lever is STILL moved all the way forward before you reinstall the print headthe way forward before you reinstall the print head

• 1. Line up the hole in the print head with the green post on the printer 1. Line up the hole in the print head with the green post on the printer carriagecarriage

• Lower the print head down gently into positionLower the print head down gently into position

• 2. Gently push the green carriage lock lever up until it snaps into place2. Gently push the green carriage lock lever up until it snaps into place

• This secures the print headThis secures the print head

• 3. Close the tops cover and re-attach the scanner3. Close the tops cover and re-attach the scanner

• 4. Press and release the yellow LED button4. Press and release the yellow LED button

• The printer will prepare the cartridge for printingThe printer will prepare the cartridge for printing

• Note: if the carriage does not move from the center position after you Note: if the carriage does not move from the center position after you press the carriage change button, remove and reinstall the print headpress the carriage change button, remove and reinstall the print head


RINDI The TRINDI information state approachThe TRINDI information state approachThe TRINDI information state approachThe TRINDI information state approach

• Information statesInformation states represent information available to represent information available to dialogue participants, at any given stage of the dialogue participants, at any given stage of the dialoguedialogue

• Dialogue movesDialogue moves trigger information state updates, trigger information state updates, formalised as information stateformalised as information state update rules update rules

• TrindiKit: software package for implementing dialogue TrindiKit: software package for implementing dialogue systems; based on the information state approach to systems; based on the information state approach to dialogue management dialogue management – Explicit information state data-structureExplicit information state data-structure

• makes systems more transparentmakes systems more transparent

• closer to dialogue processing theorycloser to dialogue processing theory

• easier comparison of theorieseasier comparison of theories

– modularity for simple and efficient reconfiguration and modularity for simple and efficient reconfiguration and reusabilityreusability


RINDI Building a systemBuilding a systemBuilding a systemBuilding a system

TRINDIKIT

dialogue theory(IS, rules, moves etc)

domain knowledge(resources)

domain-specificsystem

domain-independentsystem

software engineering(basic types, control flow)


RINDI

inputinter-pret

Information State

resource

control

update selectgene-rate

output

resource

DME


RINDI GoDiS - An experimental dialogue GoDiS - An experimental dialogue system built using the TrindiKitsystem built using the TrindiKitGoDiS - An experimental dialogue GoDiS - An experimental dialogue system built using the TrindiKitsystem built using the TrindiKit

• Information-seeking dialogueInformation-seeking dialogue

• Information state based Ginzburg’s notion of Information state based Ginzburg’s notion of Questions Under Discussion (QUD)Questions Under Discussion (QUD)

• Dialogue plans to drive dialogue; plans are Dialogue plans to drive dialogue; plans are dynamically interpreted by information state update dynamically interpreted by information state update rulesrules

• Simpler than general reasoning and planningSimpler than general reasoning and planning

• More versatile than frame-filling and finite automataMore versatile than frame-filling and finite automata

• Moves: ask, answer, greet, thank, requestRepeat, Moves: ask, answer, greet, thank, requestRepeat, repeatrepeat


RINDI GoDiS information state typeGoDiS information state typeGoDiS information state typeGoDiS information state type

PRIVATE :PLAN : stackset( Action )

AGENDA : stack( Action )

SHARED :

BEL : set( Prop )

TMP : (same type as SHARED)

BEL : set( Prop )

QUD : stack( Question )

LM: set( Move )


RINDI from GoDiS to IMDiS information statefrom GoDiS to IMDiS information statefrom GoDiS to IMDiS information statefrom GoDiS to IMDiS information state

SHARED.ACTIONSSHARED.ACTIONS: :

stack of actions that the system has instructed the stack of actions that the system has instructed the user to perform but that have not yet been confirmed user to perform but that have not yet been confirmed as doneas done


RINDI IMDiS information state typeIMDiS information state typeIMDiS information state typeIMDiS information state type

PRIVATE :PLAN : stackset( Action )

AGENDA : stack( Action )

SHARED :

BEL : set( Prop )

TMP : (same type as SHARED)

BEL : set( Prop )

QUD : stack( Question )

ACTIONS : stack( Action )

LM: set( Move )


RINDI IMDiS in monologue modeIMDiS in monologue modeIMDiS in monologue modeIMDiS in monologue mode

• 2 moves: Instruct, Inform2 moves: Instruct, Inform

• All actions use the update rule autoConfirmAll actions use the update rule autoConfirm

• rule autoConfirmrule autoConfirm

pre:

eff:

val(SHARED.ACTIONS, A)

pop(SHARED.ACTIONS) add(SHARED.BEL, done(A))


RINDI IMDiS in dialogue modeIMDiS in dialogue modeIMDiS in dialogue modeIMDiS in dialogue mode

• 9 moves (6 GoDiS moves, the 2 above and Confirm)9 moves (6 GoDiS moves, the 2 above and Confirm)

• Confirmations are integrated by assuming that the Confirmations are integrated by assuming that the current top-most action of the shared.actions has current top-most action of the shared.actions has been performed been performed

• rule integrateUsrConfirm rule integrateUsrConfirm (slightly simplified)(slightly simplified)

pre:

eff:

val(SHARED.ACTIONS, A)

pop(SHARED.ACTIONS) add(SHARED.BEL, done(A))

val(SHARED.LM, confirm(usr) )


RINDI Example from a Xerox manual (repeated)Example from a Xerox manual (repeated)Example from a Xerox manual (repeated)Example from a Xerox manual (repeated)

• Reinstalling the print headReinstalling the print head

• Caution: make sure that the green carriage lock lever is STILL moved all Caution: make sure that the green carriage lock lever is STILL moved all the way forward before you reinstall the print headthe way forward before you reinstall the print head

• 1. Line up the hole in the print head with the green post on the printer 1. Line up the hole in the print head with the green post on the printer carriagecarriage

• Lower the print head down gently into positionLower the print head down gently into position

• 2. Gently push the green carriage lock lever up until it snaps into place2. Gently push the green carriage lock lever up until it snaps into place

• This secures the print headThis secures the print head

• 3. Close the tops cover and re-attach the scanner3. Close the tops cover and re-attach the scanner

• 4. Press and release the yellow LED button4. Press and release the yellow LED button

• The printer will prepare the cartridge for printingThe printer will prepare the cartridge for printing

• Note: if the carriage does not move from the center position after you Note: if the carriage does not move from the center position after you press the carriage change button, remove and reinstall the print headpress the carriage change button, remove and reinstall the print head


RINDI

Simple task planSimple task planSimple task planSimple task plan

EFFECT: reinstalled (print_head)

NAME: reinstall(print_head)

PRECOND: moved_forward(carriage_lock)

close(top_cover)

reattach(scanner)

press_and_release(button)

remove(print_head)

reinstall(print_head)

Final

state

Action

line_up(hole, post)

moved_from_center(carriage)NY

lower(print_head)

push(lever)

condition


RINDIFrom domain task plan to monologue From domain task plan to monologue and dialogue plansand dialogue plansFrom domain task plan to monologue From domain task plan to monologue and dialogue plansand dialogue plans

DOMAIN MONOLOGUE DIALOGUE

precondition P Instruct (check(P)) findout(P ); if not(P ) then Instruct(achieve(P))

action A Instruct( A ) Instruct( A )

if C then A Inform(if C then A ) findout( C );

if C then Instruct( A )

effect E Inform( E ) Inform( E )


RINDI SampleSample IMDiS information stateIMDiS information stateSampleSample IMDiS information stateIMDiS information state

PRIVATE = PLAN =

AGENDA = { findout(?moved(carriage)) }

SHARED =

if_then( not moved( carriage ), [ remove(print_head),

reinstall(print_head) ] )

COM = moved_forward(carriage_lock)

done(secure(print_head)) done(close(top_cover)) done(reattach(scanner))

QUD = < > LM = { instruct(sys, press_and_release(yellow_button) }

BEL = { }

TMP = (same structure as SHARED)

ACTIONS= < press_and_release(yellow_button) >


RINDI Monologue and dialogue behaviorMonologue and dialogue behaviorin IMDiSin IMDiSMonologue and dialogue behaviorMonologue and dialogue behaviorin IMDiSin IMDiS

• interactivity level 1 – (spoken) monologue interactivity level 1 – (spoken) monologue – the text you have seen above but presented orally so the the text you have seen above but presented orally so the

user can direct her attention to the taskuser can direct her attention to the task


RINDIlevel 2 - dialogue behavior with minimal level 2 - dialogue behavior with minimal interactivityinteractivitylevel 2 - dialogue behavior with minimal level 2 - dialogue behavior with minimal interactivityinteractivity

• yes/no questionsyes/no questions

• confirm (”ok”)confirm (”ok”)

• requestRepeat (”what?”)requestRepeat (”what?”)

• grounding and avoidance of irrelevant informationgrounding and avoidance of irrelevant information

• example:example:• S: Press and release the yellow buttonS: Press and release the yellow button

• U: okU: ok

• S: Has the carriage moved from the center position?S: Has the carriage moved from the center position?

• U: yesU: yes

• S: the print head is now installedS: the print head is now installed

• U: what?U: what?

• S: the print head is now installedS: the print head is now installed


RINDI Complex task planComplex task planComplex task planComplex task plan

EFFECT: reinstalled (print_head)

NAME: reinstall(print_head)

PRECOND: moved_forward(carriage_lock)

close(top_cover)

reattach(scanner)

press_and_release(button)

remove(print_head)

reinstall(print_head)

Final state

Complex action

Action

secure(print_head)

moved_from_center(print_head)

Condition

NY


RINDI Subtask plan for complex actionSubtask plan for complex actionSubtask plan for complex actionSubtask plan for complex action

EFFECT: secured (print_head)

NAME: secure(print_head)

PRECOND: -

line_up (hole, post)

lower(print_head)

push(lever)


RINDI level 3: increased interactivity level 3: increased interactivity level 3: increased interactivity level 3: increased interactivity

• skipping subtask instructionsskipping subtask instructions– S: Put the print head in placeS: Put the print head in place

– U: Ok, done, what now?U: Ok, done, what now?

– S: Close the top coverS: Close the top cover

• requesting subtask instructions; popping out of requesting subtask instructions; popping out of subdialoguesubdialogue– S: Put the print head in placeS: Put the print head in place

– U: how?U: how?

– S: Line up the hole in the print head with the green post on S: Line up the hole in the print head with the green post on the printer carriagethe printer carriage

– U: done, I now remember the rest, the print head is securedU: done, I now remember the rest, the print head is secured


RINDI Domain task plans Domain task plans – where do they come from?– where do they come from?Domain task plans Domain task plans – where do they come from?– where do they come from?

• What we did: read the text and construct a What we did: read the text and construct a corresponding domain plan that seems plausible; this corresponding domain plan that seems plausible; this is not a principled approachis not a principled approach

• Alt.1: Annotating existing manuals with procedural Alt.1: Annotating existing manuals with procedural relations (Scott et. al. 1995); use this to reconstruct relations (Scott et. al. 1995); use this to reconstruct domain plandomain plan

• Alt.2: Author uses authoring tool to specify domain Alt.2: Author uses authoring tool to specify domain plan (“knowledge model”); this has been done in the plan (“knowledge model”); this has been done in the context of multilingual manual authoring (Scott 1996, context of multilingual manual authoring (Scott 1996, DRAFTER project, GIST project)DRAFTER project, GIST project)


RINDIConclusionsConclusionsConclusionsConclusions

• We provide a simple schema modeling the relation We provide a simple schema modeling the relation between task plan and discourse plans for between task plan and discourse plans for intermediate interactivity levelintermediate interactivity level– The schema also gives a model of how different levels of The schema also gives a model of how different levels of

interactivity (from monologue to dialogue) are relatedinteractivity (from monologue to dialogue) are related

– The degree of interactivity is limited by the level of detail with The degree of interactivity is limited by the level of detail with which the manual encodes the underlying taskwhich the manual encodes the underlying task

• Document transformation requires separation of task Document transformation requires separation of task plans and assumptions about interactions plans and assumptions about interactions – Task plans can be obtained either by marking up existing Task plans can be obtained either by marking up existing

manuals, or by constructing them using authoring toolsmanuals, or by constructing them using authoring tools

• Extended existing information-seeking dialogue Extended existing information-seeking dialogue system to handle instructional dialogue (reusability!); system to handle instructional dialogue (reusability!); based on information state approachbased on information state approach


RINDI ProspectProspectProspectProspect

• Use existing domain task plans produced by Use existing domain task plans produced by annotating text or using authoring toolsannotating text or using authoring tools

• TrindiKit dialogue system for information seeking TrindiKit dialogue system for information seeking dialogue, adapted to instructional dialogue; uses dialogue, adapted to instructional dialogue; uses dialogue plans (NB: current system very simple)dialogue plans (NB: current system very simple)

• Our model sketches a mapping from the domain plans Our model sketches a mapping from the domain plans to dialogue plansto dialogue plans

• So, building on existing components, this indicates a So, building on existing components, this indicates a possible way to get instructional dialogue systems possible way to get instructional dialogue systems without a lot of extra workwithout a lot of extra work


RINDI Possible future workPossible future workPossible future workPossible future work

• Explore and implement further levels of interactivityExplore and implement further levels of interactivity

• Scale up experiment, e.g. a complete manualScale up experiment, e.g. a complete manual

• Explore use of domain plans generated using existing Explore use of domain plans generated using existing toolstools

• Extend IMDiS (and GoDiS) to handle referent Extend IMDiS (and GoDiS) to handle referent resolution subdialogues, asynchronous turntaking etc.resolution subdialogues, asynchronous turntaking etc.

• Do real NL generation, possibly using existing Do real NL generation, possibly using existing componentscomponents


RINDI extra slides...extra slides...extra slides...extra slides...

• Relation to previous workRelation to previous work– Carlson, KuppeveltCarlson, Kuppevelt

– M. YoungM. Young

– Smith & HippSmith & Hipp

– Interactive tutoring (Lester, Rickel & Johnson)Interactive tutoring (Lester, Rickel & Johnson)

– N.B. We have not read all papers by everyone...N.B. We have not read all papers by everyone...


RINDI Relation to previous work: Relation to previous work: Kuppevelt, CarlsonKuppevelt, CarlsonRelation to previous work: Relation to previous work: Kuppevelt, CarlsonKuppevelt, Carlson

• monologue as a special case of dialogue where all monologue as a special case of dialogue where all moves are answers to implicit questions resulting from moves are answers to implicit questions resulting from the previous move(s)the previous move(s)

• exampleexample– The printer will prepare the cartridge for printingThe printer will prepare the cartridge for printing

– Q: What if the carriage does not move ...Q: What if the carriage does not move ...

– A: If the carriage doesn’t move, ...A: If the carriage doesn’t move, ...

• but this is not a processing theory, and it is unclear but this is not a processing theory, and it is unclear how it could be implemented; the number of possible how it could be implemented; the number of possible questions that questions that could could arise at any given moment is too arise at any given moment is too bigbig

– –


RINDI Relation to previous work:Relation to previous work:YoungYoungRelation to previous work:Relation to previous work:YoungYoung

• Young (1997) deals with how to give the right amount Young (1997) deals with how to give the right amount of information in a (monologue) text, given a of information in a (monologue) text, given a dynamically (automatically) generated task plan which dynamically (automatically) generated task plan which may be very complexmay be very complex

• Young deals only with monologueYoung deals only with monologue

• We deal with both monologue and dialogueWe deal with both monologue and dialogue

• Our plans are not automatically generated, and not as Our plans are not automatically generated, and not as complexcomplex


RINDI Relation to previous work: Smith & HippRelation to previous work: Smith & HippRelation to previous work: Smith & HippRelation to previous work: Smith & Hipp

• Handles similar type of dialogue (problem solving) Handles similar type of dialogue (problem solving) using “Missing Axiom Theory”, using general inference using “Missing Axiom Theory”, using general inference over FOL representationover FOL representation

• Handles some phenomena which we don’t (e.g. Handles some phenomena which we don’t (e.g. referent disambiguation)referent disambiguation)

• S&H do not generate monologue, or explore several S&H do not generate monologue, or explore several levels of interactivity; however, they allow mixed levels of interactivity; however, they allow mixed initiative to a larger extent than we doinitiative to a larger extent than we do

• S&H assume complex representation of the domain S&H assume complex representation of the domain task plan (?)task plan (?)

• Our approach is less complex and therefore easier to Our approach is less complex and therefore easier to implement and more computationally tractableimplement and more computationally tractable

• We provide an explicit model of the relation between We provide an explicit model of the relation between monologue and simple dialoguemonologue and simple dialogue


RINDI Dialogue models and monologueDialogue models and monologueDialogue models and monologueDialogue models and monologue

• Unfortunately, dialogue models don’t look at Unfortunately, dialogue models don’t look at monologuesmonologues

• Fortunately, dialogue models based on information Fortunately, dialogue models based on information states can be extended to account for monologuesstates can be extended to account for monologues

• Ways to adapt dialogue models to monologueWays to adapt dialogue models to monologue– General theory of action and communicationGeneral theory of action and communication

– Monologue as a degenerate case of dialogueMonologue as a degenerate case of dialogue


RINDI Relation to previous work:Relation to previous work:interactive tutorials using textinteractive tutorials using textRelation to previous work:Relation to previous work:interactive tutorials using textinteractive tutorials using text


RINDI Similarities between Similarities between monologue and dialoguemonologue and dialogueSimilarities between Similarities between monologue and dialoguemonologue and dialogue

• Hierarchically structuredHierarchically structured

• Can be represented as a sequence of questions and Can be represented as a sequence of questions and answers: Carlson, Van Kuppeveltanswers: Carlson, Van Kuppevelt


RINDI Importance of Information StatesImportance of Information StatesImportance of Information StatesImportance of Information States

• The main difference between monologue and dialogue The main difference between monologue and dialogue lies in what each participant knows about what the lies in what each participant knows about what the others knowothers know

• Instructional manuals as a genre make assumptions Instructional manuals as a genre make assumptions about information states (as do other text genres)about information states (as do other text genres)

• Between monologue and full-blown ‘natural’ dialogue Between monologue and full-blown ‘natural’ dialogue one can devise various modes of interaction: one can devise various modes of interaction: everything is a question of style and genreeverything is a question of style and genre


RINDI theoretical aside: plan representationtheoretical aside: plan representationtheoretical aside: plan representationtheoretical aside: plan representation

• traditionally, plans are represented as decomposition traditionally, plans are represented as decomposition treestrees

• we add we add conditionalsconditionals to the plan representation format, to the plan representation format, adding expressivityadding expressivity

• plans are interpreted dynamically by information state plans are interpreted dynamically by information state update rulesupdate rules

• our domain task plans are not constructed dynamically our domain task plans are not constructed dynamically by a planner; rather, we assume that they are by a planner; rather, we assume that they are constructed by a human (the author of the manual), constructed by a human (the author of the manual), possibly using some markup languagepossibly using some markup language

• discourse plans are generated from task plans using a discourse plans are generated from task plans using a simple schema which encapsulates the different levels simple schema which encapsulates the different levels of interactivityof interactivity


RINDI Sample GoDiS information stateSample GoDiS information state(travel agency domain)(travel agency domain)Sample GoDiS information stateSample GoDiS information state(travel agency domain)(travel agency domain)

PRIVATE = PLAN =

AGENDA = { findout(?return) }

SHARED =

findout(?x.month(x))findout(?x.class(x))

respond(?x.price(x))

COM = dest(paris) transport(plane) task(get_price_info)

QUD = < x.origin(x) >LM = { ask(sys, x.origin(x)) }

BEL = { }

TMP = (same structure as SHARED)


RINDI What we have not doneWhat we have not doneWhat we have not doneWhat we have not done

• NL generation – instead, we used canned text derived NL generation – instead, we used canned text derived from manuals from manuals

• referent disambiguation issuesreferent disambiguation issues

• more complex user utterances, e.g. alternative more complex user utterances, e.g. alternative questions (though latest version of GoDiS handles this questions (though latest version of GoDiS handles this partially)partially)


RINDI Possible extensionsPossible extensionsPossible extensionsPossible extensions

• Larger scale experimentsLarger scale experiments

• More descriptive work, including on more fine- More descriptive work, including on more fine- grained linguistic aspectsgrained linguistic aspects

• Implementation of more complex dialogue Implementation of more complex dialogue behaviours, e.g. referent resolution subdialogues, behaviours, e.g. referent resolution subdialogues, explanatory subdialoguesexplanatory subdialogues

• Explore higher levels of interactivityExplore higher levels of interactivity

• Build tools to make the creation of multi-purpose Build tools to make the creation of multi-purpose documents possibledocuments possible

• Mark-up schemes (XML) Mark-up schemes (XML)

Document Transformations and Information States

Documents

Transcript of Document Transformations and Information States