Franz Kurfess: Knowledge Retrieval Computer Science Department California Polytechnic State...

Franz Kurfess: Knowledge Retrieval

Computer Science DepartmentCalifornia Polytechnic State University

San Luis Obispo, CA, U.S.A.

Franz J. Kurfess

OWL-2 and Law

2Franz Kurfess: OWL and Law

Overview

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❖Knowledge Representation in the Legal Domain❖interesting aspects of the legal domain❖KR methods used

❖OWL and the Law❖versioning❖“Nomic” Game


KR and LawKR and Law

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Laws and Society

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❖Laws as a guideline for the behavior of persons and organizations in a society❖expectation to follow the law❖law enforcement if the law is not followed

❖Law as dispute resolution method❖court❖usually dispute between two parties❖exchange of arguments

❖presentation of a selected set of facts❖prosecution vs. defense

❖judge/jury as arbiter❖not necessarily about “the truth”


Case Law

❖a judge or jury makes a decision about a case❖weighing the arguments presented by the prosecution and defense

❖assessment and interpretation of the facts❖legal aspects

❖ laws that may be violated❖potential conflicts between selections, interpretations of laws

❖causal analysis❖sequence of events❖dependencies and relations between events❖motivation

❖comparison to written law❖comparison to similar cases

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Legal Decisions

❖precedents for new cases❖as a domain, law is self-reflexive

❖decisions are changes in the “real world”❖the “world of the law” has changed ❖not only the application of the law to the defendant

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Legislation

❖creation of laws by bodies outside of the judiciary system❖possible conflicts with case law

❖idealistic assumptions❖every citizen should know the law

❖practically impossible

❖persons and organizations should abide by the law❖unambiguous and clear specification

❖often intentionally cryptic and vague❖often written by the legal profession for the legal profession

❖fair and impartial❖in reality, often tainted by political considerations

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Inconsistencies in the Law

❖application of the law is not necessarily a reasoning process❖the outcome of a case may not follow from the premises

❖selective considerations of facts and laws❖selection and interpretation of laws

❖conflict resolution methods❖lex specialis => specificity❖lex superior => authority❖lex posterior => temporal aspects

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A few good things about the Law

❖complex domain ❖based almost entirely on human contributions

❖not a model created to simulate or explain the “real world”

❖reasonably well structured❖at least for domain experts

❖widely used❖applicable to everybody

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Franz Kurfess: OWL and Law

KR Methods for KR Methods for LawLaw

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Legal Theory vs. the Law

❖formal representation of legal theory❖not intended for practical use❖dialectic, defeasible, non-monotonic❖completeness, tractability no major concerns

❖formal representation of the law ❖intended for practical use❖tractability and completeness are important

❖not necessarily at the time of creation

❖open world

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KR for Legal Theory

❖Case-Based Reasoning❖repository of cases❖retrieval of similar cases❖decisions made in reference to previous cases❖does not attempt to encode the “letter of the law”

❖deontic logic❖norms, exceptions

❖argument theory❖dispute resolution theories and methods

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KR for Laws

❖legal knowledge representation❖computer-based representation of laws

❖conversion of “legalese” into a format suitable for computer-based storage and manipulation (reasoning)

❖inherently difficult❖application of the law relies strongly on interpretation

❖assessment, planning, ontology, harmonization❖legal annotation

❖cross-references, versioning, authority, interpretation❖applications

❖decisions of legal cases❖law enforcement, legal advice

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Law and Semantic Web Technologies

❖representation of structure in legal texts via XML❖versions

❖time,language

❖cross-references❖identification

❖annotation via RDF❖authority❖concepts ❖typed references

❖content representation via OWL❖concept definitions, norms

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MetaLex

❖XML-based interchange format for legal and legislative resources❖http://www.metalex.eu

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http://www.metalex.eu/

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OWL and LawOWL and Law

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Functional Ontology of Law (Valente, 1995)

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Concept Definitions

❖relies on the relation between the “real world” and the law❖common understanding of reality❖may require commonsense reasoning

❖scoping❖jurisdiction

❖countries, regions

❖classes of persons, organizations❖“deeming” provisions

❖clarifications of the scope and applicability of the law❖e.g. minor vs. adult

❖related to name spaces in computer science18

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Actions

❖activities of persons and organizations require the representation of❖action❖belief❖intention❖roles❖situations

❖can be difficult to capture in a formal KR

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Situations

❖situation❖identification of subjects, objects, relations❖Example: Freezer full of cash

❖action❖activities related to the subjects and objects in a situation❖Example: “Buying”

❖actor some (Buyer and (owns some Money))❖ recipient some (Seller and (owns some Good))❖ object some Good❖ instrument some Money❖ result some (Buyer and (owns some Good))

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Norms

❖very critical for the representation of laws❖describe expected human behavior

❖allowing and disallowing certain situations❖express preferences between situations

❖captured via deontic operators❖permission❖obligation❖prohibition

❖legal assessment❖human or automatic classification of situations

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Norm Examples: Freezer Contents

❖Permission❖Freezer_Contents_Ok is an Obligation

❖allows some Freezer_Contents❖allows only Freezer_Contents

❖Prohibition❖No_Cash_in_Freezer is a Prohibition

❖allows some not Cash_in_Freezer❖allows only not Cash_in_Freezer❖disallows some Cash_in_Freezer❖disallows only Cash_in_Freezer

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Norm Examples: More Freezer Contents

❖Obligation❖Always_Cash_in_Freezer is an Obligation

❖allows some Cash_in_Freezer❖allows only Cash_in_Freezer❖disallows some not Cash_in_Freezer❖disallows only not Cash_in_Freezer

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Norms and Conflicts

❖Lex Specialis❖more specific override generic norms❖norms can be classified by a reasoner

❖Lex Superior❖higher authority norms override lower ones❖solution in OWL unclear

❖Lex Posterior❖newer versions override older ones❖versioning in OWL is an obvious candidate

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LKIF Core Ontology

❖ontology of basic legal concepts❖developed in a European research project

❖http://www.estrellaproject.org/lkif-core

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http://www.estrellaproject.org/lkif-core

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Versioning in OWL

❖“Nomic” Game❖rules of Nomic❖Nomic in OWL

❖Instances and Dynamic Concepts

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Nomic Overview

❖proposed by Peter Suber, 1980❖see http://www.nomic.net

❖two sets of rules❖immutable rules❖mutable rules

❖makes the game self-modifying

❖multiplayer game❖turn-based game❖hard to model❖good stand-in for self-reflexive, self-modifying legislation

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Nomic Rules Examples

101 All players must always abide by all the rules then in effect, in the form in which they are then in effect. The rules in the Initial Set are in effect whenever a game begins. The Initial Set consists of Rules101-116 (immutable) and 201-213 (mutable).

103 A rule-change is any of the following:

(1) the enactment, repeal, or amendment of a mutable rule;

(2) the enactment, repeal, or amendment of an amendment of a mutable rule; or

(3) the transmutation of an immutable rule into a mutable rule or vice versa.

104 All rule-changes proposed in the proper way shall be voted on. They will be adopted if and only if they receive the required number of votes.

105 Every player is an eligible voter. Every eligible voter must participate in every vote on rule-changes.

109 Rule-changes that transmute immutable rules into mutable rules may be adopted if and only if the vote is unanimous among the eligible voters. Transmutation shall not be implied, but must be stated explicitly in a proposal to take effect.

110 In a conflict between a mutable and an immutable rule, the immutable rule takes precedence and the mutable rule shall be entirely void. For the purposes of this rule a proposal to transmute an immutable rule does not “conflict” with that immutable rule.

Rinke Hoekstra28

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Nomic in OWL

❖knowledge representation and reasoning challenges❖knowledge changes over time

❖new concept variants are introduced as defined classes, subsumed by the dynamic concept class

❖concept variants are valid within some interval❖delimited by game turns

❖a reasoner classifies individuals as class members❖based on the “current turn”

❖relies on owl:sameAs

29Szymon Klarman, Marc Bron, Abdallah El-Ali and Xingrui Ji, via (Hoekstra, 2008)

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Dynamic Concepts and Individuals 0

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Summary

❖legal knowledge representation with OWL❖facilitates legal assessment❖accommodates definitions, situations, norms, versioning❖limited expressiveness

❖Legal Knowledge Interchange Format (LKIF)❖interchange between different legal systems❖OWL as foundation, with

❖additional layers of expressiveness❖connection to legal theory

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References

❖ [Hoekstra 2007] Rinke Hoekstra. “Knowledge Representation in the Legal Domain,” Leibniz Center for Law, Faculty of Law, University of Amsterdam; http://www.leibnizcenter.org, KR Course, Manchester, 2007

❖ [Visser] Pepijn R.S. Visser and Trevor J.M. Bench-Capon. “Ontologies in the Design of Legal Knowledge Systems; Towards a Library of Legal Domain Ontologies,” LIAL - Legal Informatics at Liverpool, University of Liverpool - Department of Computer Science, PO Box 147, Liverpool, L69 7ZF, United Kingdom; http://www.csc.liv.ac.uk/~lial/ and https://eprints.kfupm.edu.sa/55792/1/55792.pdf

❖ [Walter and Pinkal] Stephan Walter and Manfred Pinkal. “Computational Linguistic Support for Legal Ontology Construction,” Dept. of Computational Linguistics and Phonetics, Universität des Saarlandes, 66123 Saarbrucken, Germany.

❖ [van de Ven et al, 2008] Saskia van de Ven, Rinke Hoekstra, Joost Breuker, Lars Wortel, and Abdallah El-Ali. Judging Amy: Automated legal assessment using OWL 2. In Proceedings of OWL: Experiences and Directions (OWLED 2008 EU), October 2008.

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http://www.leibnizcenter.org/

http://www.csc.liv.ac.uk/~lial/

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