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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
Wrapper1 Wrappern
Source1
Wrapper2
Source2 Sourcen
Internet