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Semantics In The Legal Domain. By Angela Maduko. Introduction. This presentation looks into: Different ontologies in the legal domain and the motivations for using using ontologies in legal information/knowledge systems
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Semantics In The Legal Domain By Angela Maduko
Introduction This presentation looks into: • Different ontologies in the legal domain and the motivations for using using ontologies in legal information/knowledge systems • Applications of some of the legal ontologies and a comparison of two such ontologies • Metadata standards in the legal domain. • Some tools and applications of the legal ontologies/metadata.
Overview of KBS in the Legal Domain • Original Concept was: • A set of empirical associations formed by an expert in the course of practising in the domain • This is encoded in some executable formalism typically production rules • Problems: • Knowledge Acquisition: Experts often had difficulties in making their expertise explicit and stating their empirical associations with sufficient completeness • Robustness: The systems were not able to deal with situations not anticipated/overlooked by the experts • Maintenance and reuse: Was built for a particular task and so was difficult to adapt to other tasks • Explanation: Poor quality explanations since the empirical associations did not reflect the underlying causal mechanisms of the domain
Need for Ontology • Knowledge Sharing • Verification of a Knowledge base • Software Engineering considerations • Knowledge Acquisition • Knowledge Re-use • Domain theory development
Need for Ontology A simple example UK SS law’s concept of pensionable age : 65 (man), 60 (woman) c1, pensionable_age(X),:- sex(X, male), age(X, A), A,>= 65. c2, pensionable_age(X),:- age(X, A), A,>= 60. This can also be represented as c1, pensionable_age(X),:- sex(X, male), age(X, A), A,>,64. c2, pensionable_age(X),:- sex(X, female), age(X, A), A,>,59.
Building IR oriented Legal Ontologies • Issues • Identifying domain terms • Lexical phenomenon such as synonymy, polysemy • Controversies existing among experts • Some methods are: • Top-down method • Specifying or generalizing an existing ontology to create a new one • Agreement on a unique point of view on the specialties of domain experts, which becomes the basis of the new ontology • Bottom-up method • Extracting all elements needed to build an ontology from appropriate documents • Selecting an appropriate corpus • Extracting domain terms • Identifying relations among terms
Some Legal Ontologies • Valente’s Functional Ontology of Law • Frame-based Ontology of Van Kralingen and Visser • McCarty’s Language of Legal Discourse(LLD) • Stamper’s Norma
Legal Ontologies • Functional Ontology of law - based on a functional perspective of the legal system. • Main function - reacting to social behaviour - is decomposed into six primitive functions • Normative Knowledge • World Knowledge • Responsibility Knowledge • Reactive Knowledge • Meta-legal Knowledge • Creative Knowledge
Legal Ontologies • Frame-based Ontology - decomposed into • Generic legal ontology • Norms • Acts • Concept descriptions • Statute-specific ontology
Frame-based Ontology • Norms • Norm identifier • Norm type • Promulgation • Scope • Conditions of application • Norm subject • Legal modality • Act identifier
Act identifier Promulgation Scope Agent Act type Modality of means Modality of manner Temporal aspects Spatial aspects Circumstantial aspects Cause of action Aim of action Intentionality of action Final state Frame-based ontology Acts (Events, Processes & institutional acts, Physical acts)
Frame-based ontology • Concept descriptions comprise • Concept to be described • Concept type (definition, deeming provision, factor, meta) • Priority • Promulgation • Scope • Conditions of application • Enumeration of instances
Comparison of the two ontologies Criteria for comparison • Epistemological adequacy (clarity, intuitiveness, relevance, completeness, discriminative power) • Operationality (Encoding bias, coherence, computationality) • Reusability (task-and-method reusability, domain reusability)
Some Applications of legal Ontologies • Functional ontology of law: • ON-LINE (Ontology-based Legal Information Environment) • Frame-based ontology: • An assessment expertise system( Dutch Unemployment Benefits Act(DUBA) ) • A planning expertise system • CLIME ontology(Cooperative Legal Information Management and Explanation): • Maritime Information and Legal Explanation(MILE) • Knowledge Desktop Environment(KDE)
ON-LINE An architecture for storing and retrieving legal information and reasoning with legal knowledge Based on the idea that Legal problem solving is to some extent a global modelling activity in which the practitioner experiments with alternative models(interpretations) of the legislation and/or of a case in order to reason about their consequences Contains reasoning modules based on some models for legal assessment and legal planning as well as on supporting tools for legal modelling and design
ON-LINE • Major functions: • Legal Information Serving • Legal Analysis • Main features: • Integrated storage and representation of legal text and knowledge by using interconnected knowledge and text repositories • Representation of legal knowledge based on the functional ontology of law • Emphasis on legal modelling as a central task in legal practice
ON-LINE (Structure) Source: ON-LINE: An Architecture for Modelling Legal Information
ON-LINE(Modelling Links) • Enables the explicit storage of the modelling process • Definitional links: These keep track of information source that has been used for modelling a certain element of the knowledge base • Referential links: These keep track of multiple references to the same defined concepts
ON-LINE Source: ON-LINE: An Architecture for Modelling Legal Information
ON-LINE(Legal Information Server) • Services directly related to Legal Information textual base • Similar design with legal information databases • Can also search for information using the knowledge base • For eg, one can search for the word software in both the textual base and the knowledge base thereby enabling conceptual retrieval • Search is made using elements in the whole ontology • Retrieval is not only by queries but also based on the description(in knowledge terms) of a case.
ON-LINE(Legal Information Modelling Toolkit) • Contains a number of tools(different browsers and editors) for modelling legal information • The browsers present different view of the elements in the text and knowledge bases • The editors enable adding to and deleting from the knowledge base • Contains the tools for creating and managing the modelling links.
ON-LINE(Legal Analysis Environment) • Contains an extensible number of modules that execute legal reasoning tasks. Two currently supported ones are: • Legal Assessment task accesses a case description(a description of relevant facts in the world) based on a body of legal knowledge. • Case analysis mode: A specific case already modelled and stored in the system is matched against a knowledge base • Goal oriented mode: here conditions which are sufficient to warrant a certain(desired) conclusion is sought. • Legal Planning task generates a plan aimed at achieving a certain legal goal(defined in terms of legal concepts and norms which apply in the final state) starting from an initial state
ON-LINE Some problems and limitations • Architecture is modelling intensive • Most of this modelling work has to be done/checked by a specialist • The scope of the architecture is restricted to model in detail limited amounts of legislation • Epistemological intuitiveness of the ontology
A Legal Ontology tool (LODE) • Gets an initial ontology from a user and refines it using two ontologies (General and Case ontologies) • Two main issues involved: • Determining the best correspondence to a given concept in the general/case ontology • Corrects bugs(missing concepts, existing unnecessary concepts, flawed hierarchical relationships etc) in the initial legal ontology using the extracted concepts • EDR Electronic Dictionary serves as the general ontology • With an extended version of the Sort Taxonomy Tool, the case ontology is built
LODE (EDR Electronic Dictionary) Source: LODE: A Legal Ontology Development Environment
LODE (Sort Taxonomy Tool) • Builds a sort taxonomy, based on facts input by the user • Sort - set of terms that occur in the same argument places of the same predicates • Class a sort or set of sorts that have the same set of terms • The most general class is all, and there could be subclasses and intersection classes For example: With an input of the facts ownership(a, b). ownership(c, d). STT would generate class_1{a,c} and class_2{b,d} Then when fact country(b) is input, it creates class_3{b} as a subset of class_2{b,d}
LODE (SST) Source: LODE: A Legal Ontology Development Environment
LODE (Extended SST) • Creating some sub-nodes of USS when the same USS is assigned to different arguments of predicates • Sort taxonomy process is applied to arguments of functions that are arguments of predicates Source: LODE: A Legal Ontology Development Environment
LODE(Algorithms used for matching) • For general ontology • input: name and definitions of a legal concept • output: the small space that can have the best correspondence in the concept dictionary • Spell match - against the word dictionary • Finds the lower boundary of the small space • Definition match - against the concept dictionary • Finds the upper boundary of the small space • The space between the lower and upper boundaries of the concept dictionary is then extracted • User selects best correspondence to the given legal concept • For case ontology • User finds out the best correspondence of a given legal concept in a case ontology
LODE • Static Analysis • Comparison of the number of immediate sub-nodes • Distance from a root to a concept • Topological relations between two concepts in each hierarchy • Concept definitions
LODE Source: LODE: A Legal Ontology Development Environment
LODE Source: LODE: A Legal Ontology Development Environment
Metadata in the Legal Domain - Benefits • To owners of legal websites • Accurate metadata means that all information on a particular topic is readily accessible • It provides a clear and consistent structure for the storage of information • It promotes regular maintenance of the data through the identification of data that has not been updated since a certain date • It offers indirect evidence of the quality of the data in that an organisation that invests time and money in the creation of accurate metadata is likely to have made a similar investment in the data itself • It increases the visibility of the website to Search Engines • It increases the acceptability of the website to Search Engines
Benefits of metadata • To users of legal websites • Searching for information is easier and more effective with consistent terminology • It allows for an increase in precision and recall • It allows for an indirect assessment to be made of the quality of the information.
Justice Sector Metadata Standard • Based on Australian Government Locator Service (AGLS) • Designed for organizations publishing legal materials on the web in NSW • Objectives include: • To improve quality of access • To reduce costs
DC.Title DC.Creator DC.Publisher DC.Rights DC.Subject Keywords DC.Description Description DC.Language DC.Coverage DC.Coverage.Jurisdiction DC.Coverage.Region DC.Date.Created DC.Date.Modified JSMS.Category DC.Type DC.Format DC.Identifier AGLS.availability Admin.Creator Admin.DateCreated Admin.DateValidTo Justice Sector Metadata Standard Standard metadata fields for the Justice Sector are:
Mandatory Elements Title Author Subject Description Publisher Date.created Date.modified Resource identifier Language Coverage Optional Elements Contributor Resource type Format Source Relation Rights management Legal and Advice Sectors Metadata Standard Based on Dublin Core The elements include:
Some applications of Legal Metadata • EULEGIS (European User Views to Legislative information in Structured Form) • Legal RDF Dictionary • Lawzone (a metadata enabled search facility)
EULEGIS • Purpose: Providing an integrated access to the numerous European legal databases • Goal: Improving information retrieval through the use of structured documents • Implementation: Relational XML-based metadata database containing data about legal systems and legal databases
EULEGIS Modules of the EULEGIS metadata model Database Documents Actors Process Source: XML Metadata for Accessing Heterogeneous Legal Databases
EULEGIS Legal database metadata • Main functions: • Formation of a unified interface for querying all databases • Unifying the result of the query so as to appear similar to the user, the original database notwithstanding • Includes • Query interfaces • Query fields • Allowed operators • Informative content specified in different languages to make multi-lingual
EULEGIS DTD fragment for describing a query interface DTD fragment for describing query fields Source: XML Metadata for Accessing Heterogeneous Legal Databases
DTD fragment for describing legal actors EULEGIS • Legal Actors metadata Source: XML Metadata for Accessing Heterogeneous Legal Databases
EULEGIS • Document types metadata DTD fragment for describing document types Source: XML Metadata for Accessing Heterogeneous Legal Databases
EULEGIS • Legal processes metadata DTD fragment for describing legal processes Source: XML Metadata for Accessing Heterogeneous Legal Databases
EULEGIS • Metadata visualisations • Actor view • Information sources view • Process view • Acessing Legal data • Graphical views • Choosing one or more databases
Legal RDF Dictionary Concept of legal RDF dictionary: Maps one datastructure DTD or XML schema to another to make them comparable and exchangeable, thereby declaring semantics of DTDs or XML schema Goal: To facilitate cultural diversity in the standardization process of the legal domain thereby taking advantage of the possibility of XML to create one global legal information space, allowing for diversity at the same time Maps key legal terms across language and jurisdiction borders, obviating the problem of literally translating legal terms from one language to the other The concept is applicable at many levels
Legal RDF Dictionary Mapping a term from a document to another jurisdiction(German) occurs as follows: • Establish the DTD/Schema of the document • Establish the interface of the DTD/Schema at the RDF Dictionary • Establish which interfaces have linked German DTD´s/Schemas to the same archetypes • Establish the German term which has the same archetypes Legal RDF Dictionary Projects • LEXML - multi-lingual and multi-jurisdictional rdf dictionary for the legal world (latest version) • LegalXML - English language legal terms • European Legal RDF Dictionary
Some Legal Metadata Tools • Justice Sector Metadata Html Generator • Legal and Advice Sectors Metadata editor
References • Robert Van Kralingen: A Conceptual Frame-Based Ontology for the Law • Joost Breuker, Andre Valente and Rabboud Winkels: Legal Ontologies: A Functional View • Trevor J.M. Bench-Capon and Pepijn R.S. Visser: Ontologies in Legal Information Systems; The Need for Explicit Specifications of Domain Conceptualisations • Murk Muller: Legal RDF Dictionary • Andre Valente and Joost Breuker: ON-LINE: An Architecture for Modelling Legal Information • Chizuru Aoki, Masaki Kurematsu and Takahira Yamaguchi: LODE: A Legal Ontology Development Environment • Pepijn R. S. Visser and Trevor J.M. Bench-Capon: A Comparison of Two Legal Ontologies • Guiraude LAME: Constructing an IR-Oriented Legal Ontology • T.J.M. Bench-Capon and P.R.S. Visser: Deep Models, Ontologies and Legal Knowledge Based Systems • Virpi Lyytikainen, Pasi T. Tiitinen and Airi Salminen: XML Metadata for Accessing Heterogenous Legal Databases • http://www.lcd.gov.uk/consult/meta/metafr.htm#part6: Metadata Scheme for Websites in the Legal and Advice Sectors • http://www.agd.nsw.gov.au/agd.nsf/pages/lawzone: LawZone: A new Way of Searching