Evolució dels sistemes de diàleg

• Millorar el procés de desenvolupament del sistema

• Millorar la funcionalitat – Utilizació en aplicacions més complexes– Expansió de la cobertura lingüística– Millora del controlador de diàleg

• Utilització del model del diàleg• Utilització del model de tasques del sistema

– Integració amb altres modes: multimodalitat

Millorar el procés de desenvolupament del sistema

• Transportables a dominis diferents

• Sistemes i eines per desenvolupar mòduls comunicatius– INKA: Interfícies per construir Sistemes Experts

• Utilitza un Llenguate Structurat d’Interfícies

– NL-MENU: Interfícies per consultar bases de dades

– NAT: Interfícies per diferents llenguatges i aplicacions

Evolució

Utilizació en aplicacions més complexes

• El coneixement conceptual implicat és més complexe

• Es necessiten noves functionalitats– Preguntes sobre l’aplicació

• El coneixement lingüístic necessari és més gran

Interfícies en LN per sistemes basats en el coneixement

Evolució

Incorporació

de la representació del domini

Expansió de la cobertura linguística

Evolució

Eficiència Cobertura Reusabilitat

Bona Pobre Difícil

Bona Rica Fàcill

Pobre Rica Fàcil

Recursos generals adaptables a diferents aplicacions

Recursos generals

Basats en templetes orientats a la tasca

Integració amb altres modes: multimodalitat

• La integració de speech permet una comunicació més amistosa i noves aplicacions –VOYAGER (MIT), Office Manager (CMU), MASK (Multimodal Multimedia Automated Service Kiosk), ATIS (MIT, CMU), Railtel, Sundial, Verbmobil

• La integració amb menus, gràfics i gest millora la communicació en moltes aplicacions–MMI2 (Multimodal Interface for Man Machine Interaction)–MATIS (Multimodal Airline Travel Information System) –COMET (Coordinated Multimedia Explanation Testbed), ALFresco, CUBRICON

GISE: Generador de Interfaces para Sistemas

Expertos

• It supports NL communication with KBSs

• It automatically adapts– General linguistic knowledge

•Represented in a Linguistic Ontology

– To application communication tasks•Represented in a Conceptual Ontology

The functionality of GISE

Aim of the study

GISE, a system for improving NL Interaction with Knowledge Based

Systems• Reducing the run-time requirements for

processing user interventions• Guiding the user about the system capabilities• Reducing the cost of developing the grammar

and lexicon

• The GISE NLI uses: - An application-restricted grammar and lexicon - A menu-system• GISE automatically adapts - General linguistic knowledge to the application knowledge represented in a Conceptual Ontology

The different types of knowledge involved in the generation process

• Conceptual knowledge:– Application knowledge appearing in

communication– Communication tasks: general and specific

• Linguistic knowledge: – Linguistic structures expressing the

communication tasks

• Control knowledge: – Controlling the process of relating general

linguistic knowledge to application knowledge

Conceptual Ontology

Linguistic Ontology

Control Rules

GISE

Obtaining the application-restricted linguistic

resources

Step 1. Providing the application domain-specific knowledge

Step 2. Adapting the general communication tasks to cover application knowledge

GISE

Step 3. Adapting general linguistic knowledge to express the application communication tasks

Obtaining the application-restricted linguistic resources

Conceptual Ontology

Application knowledge

Dialoguesystem

Data Description

Control Description

General knowledge

Control rules

The functionality of GISE

Linguistic Ontology

Application lexicon

General knowledge

Application grammar

Application lexicon

The Conceptual Ontology

• There are 3 basic entities represented in 3 separated taxonomies– Concepts– Attributes

• Describing the concepts • They are classified according to a syntacico-

semantic taxonomy

– Operations • The communication tasks consist of the

expression of allowed operations over the CO concepts

The architecture of GISE

The syntactico-semantic taxonomy of attributes

• Generalization of the relations between– Application knowledge in the Conceptual

Ontology– Linguistic knowledge in the Linguistic

Ontology

• Each class is related to the linguistic structures expressing the consulting and filling of the attributes in the class

Conceptual Ontology

The basic attribute taxonomy

• participants :

• being:• possession:• descriptions and relationships between

two or more objects : • related processes:

Conceptual Ontology

who_does

is

has

of

does

who_object

what_object

TOP

CONCEPT ATTRIBUTE

TRANSPORTlex: (transporte)departurearrivaldeparturetimearrivaltimeprice

TRAIN

OPERATION

Conceptual Ontology

BUS

ATTRIBUTE

OF_QUANTITY

OF_TIME

ARRIVALTIMElex: (llegar,...)unit: h/m

DEPARTURETIMElex: (hora_salida, salir,..)unit: h/m

PRICElex: (precio,..)unit: Euro

Conceptual Ontology

OF_COST

OF

TOP

CONCEPT ATTRIBUTE

TRAINlex: (tren)departurearrivaldeparturetimearrivaltimeprice

OPERATION

Conceptual Ontology

MINIMUM_ATTRIBUTE_VALUE_Oconceptattribute

Which train arrives first?

Which is the cheapest train?

Which train departures first?

OF_TIME OF_COST

Which <concept_name> <attribute_verb> first?

Which is the cheapest <concept_name> ?

Operations

• Operations are represented as CO objects– The attributes describing these objects

represent their parameters and their preconditions (the conditions that must hold for an operation to be executed)

• They are classified asConstructive Creating a conceptual instance, filling attributes Consultative Consulting the value of an instance attribute

Simple or complex

Conceptual Ontology

The Linguistic Knowledge

• It is organized following the basic principles of the Nigel grammar

• It covers the Spanish communication with KBSs

• It is represented as an ontology

The architecture of GISE

A large systemic functional grammar of EnglishIt is based on Hallidays’s workIt has been used with GUM to generate NL

The grammar and lexicon generated

• Their size is not large -> Simple parsing– They cover only the domain communication

tasks– They incorporate dynamic categories

• They incorporate information from the Conceptual Ontology -> Simple semantic interpretation– In the lexical entries– In the features augmenting the categories– In the preconditions associated with the rules

• Linguistic knowledge is organized in two dimensions:– Rank: The scale of the grammatical structures

represented• Clause• Group• Word

– Metafunction: The type of meaning

• Interpersonal: The type of interaction • Ideational: The propositional meaning and content

• Textual: The information organization

Linguistic Ontology

The control rules

• They control the process of adapting the general linguistic knowledge to applications

• They establish general relations between:

• They are implemented in PRE (Production Rules Environment)

The architecture of GISE

Concepts and operations in the COCO and LO objects• Their form is: conditions ---->

actions

Adapting the general communication tasks to cover application

knowledge

The control rules

for each CONCEPT in ONTOLOGY do

generate_CO_operations_ instance_modifying_concept (CONCEPT)

generate_CO_operations_ instance_consulting_concept (CONCEPT)

endfor

Adapting general linguistic knowledge to express the application communication

tasks

The control rules

for each OPERATION_INSTANCE in ONTOLOGY do

generate_CLAUSE_instances (OPERATION_INSTANCE)

for each ARGUMENT in OPERATION_INSTANCE do

generate_GROUP/WORD_instances (OPERATION_INSTANCE , ARGUMENT)

endfor

endfor

The basic set of rules

• It controls the generation of grammars and lexicons for each application

• It contains 48 rules organized in 8 rulesets

• It covers different types of interfaces

• It can be enlarged easily

Interfaces supporting descriptions

Interfaces supporting consults

Interfaces supporting consults and descriptions

The control rules

A rule of the ruleset creating_instanceThe control rules

(rule cio ruleset creating_instance priority 1 control forever (object ^con ?con ^pcc ?pcc) ---> (?crinno := (create-name ‘criwno ?con) (?concrinno := (create-object ?crinno ‘crinno)) (?oparg := (add-slots ?crinno ‘((con ?con)(pcc ?pcc)))) ...)

Menu system

Parser

Dialogue Controller

GrammarLexicon

Communication ManagerApplication

User

Conceptual Ontology

Dialogue sytem

The dialogue system

The grammar and lexicon

• They are obtained from the LO objects• They are represented in the definite-

clause grammar (DCG) formalism because:– Definite-clause grammars are more

expressive than conventional context-free grammars

– They can be efficiently parsed– They are automatically generated

String

Category Interpretation

es verbser (((l,X),(l,Y)),(X,Y))

(syn(num(s),tense(p)))

A lexical entry representing the verb ser

The lexicon

syntactic

number singular

tense present

A lexical entry representing the concept ARCHITECT

• String• Category

• Semantic Interpretation

indefngcon(syn(gen(m),num(s)),sem(con(architect)))

un_arquitecto

architect

The lexicon

syntacticgender masculinenumber singular

semanticconcept architect

The lexicon

Category function

pngi(sem(con(person))) instance_of(person)

Category function

defngattrof(sem(con(person), attr(name))) name defngvalofcause(sem(con(requirementobuild),attr(reasonot

built)))

Representing instances of concepts

Representing values of attributes requested to the user during communication

Representing all possible values of an attribute

menu(reasonotbuilt)

Dynamic entries

Dynamic entries

• The number of lexical entries to be considered is reduced

• They allow the introduction of new values during communication

• They guide the user to introduce specialized terms

The lexicon

The parser

• It is based on the Ross version of the Left-corner algorithm

• It assures there is always a correct choice to continue from a correct prefix (prefix correctness)

• It can parse– A word and predicts the set of all

possible next words

The Dialogue Controller (DC)

• The DC completes and disambiguates the semantic interpretation of the user request– The result is a complete specification of an

operation over the Conceptual Ontology

• The DC controls the execution of the operation

• The DC passes the resulting information to the interface

• The DC completes and disambiguates the semantic interpretation of the user request using:– History of dialogue

• Concept and parameters of the previous operations

– The Conceptual Ontology• The definition of the operation: mandatory

arguments, default values,...

• This process is simple when users build the requests using the NL options shown in the screen– Mistakes and misunderstandings are avoided

The Dialogue Controller

SIREDOJ, an expert system in law

• Previously its communicative tasks– were fully integrated with functional tasks– were based on a set of menus

• Applying GISE improves the communication:– Complex concepts can be expressed in one

sentence– User-initiative dialogues are allowed– The size of the linguistic resources is not big:

26 grammar rules and 112 lexical entries

Applications of GISE

Conclusions

• Main contribution: – Proposing an organization of the

knowledge involved in communication that improves the obtaining of the linguistic resources most appropriate for each application

Proposing a reusable organization

• The Conceptual Ontology– It provides a general framework for

representing application communication tasks

– It includes a syntactic-semantic taxonomy of attributes•Capturing the relations between

application communication tasks and their linguistic realization

Conclusions

Proposing a reusable organization

• The Linguistic Ontology– It is an adaptation of NIGEL grammar for

communication with KBSs in Spanish

• The Control Rules– They control the process of adapting

linguistic knowledge to each application– A basic set of rules controls this process

for different types of applications

Conclusions

Improving the NL processing

• Their size is not large: The parsing is simple – Dynamic categories are used– A menu-system is integrated in the NLI

• They incorporate information from the Conceptual Ontology: The interpretation is simple

• In the lexical entries• In the features augmenting the categories• In the preconditions associated with the rules

Conclusions

Using grammars and lexicon restricted to the application communication tasks

Improving communication and user satisfaction

• Using an easy and clear language– Guiding the user about application specific

information

• Using a menu-system to introduce NL – The user is guided about the system

requirements– The user can avoid typing sentences

• Tools helping the user are incorporated into the interface

Conclusions

Interface

Parser

Dialogue Controller

GrammarLexicon

User

Conceptual Ontology

GIWEB

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