1. The Potential of Ontologies for Courts Erich Schweighofer University of Vienna, Austria* At present on leave, working for the European Commission. The expressed views are those of the author.

2. Outline 4 Concept and aim of legal ontologies 4 Legal ontologies: state of the art 4 Proposal of a comprehensive legal ontology 4 Steps to take: hybrid information system, lexical ontology, pre-ontology, dynamic electronic commentary 4 LOIS project 4 Potential for courts 4 Conclusions

3. Concept and aim of legal ontologies –Explicit formulation of a legal domain –Conceptual model Abstract, simplified, computable –New form of abstraction and formalisation of law Theory of formalisation (?) –Advantages Computable Links with world ontologies Re-use of existing ontologies Important tool for automation of law –Problems High efforts required for knowledge acquisition Scaling-up (well-known problem in AI & law)

4. Earlier Projects / “Expert Systems” LLA, LLD, NORMA 4 Latent Damage Advisor / Susskind (1988) –Formalisation of “Latent Damage Act” –“Expert system” - simple predicate logic –Result: limits of this logic, cannot be solved by adding existing expert knowledge 4 Language for Legal Discourse LLD / McCarty (1989) –Language for representation of law 4 NORMA / Stamper (1991) –Ideas of formal languages for the description of norms; goal: development of formal languages for the description of norms including semantic issues

5. Frames-Based Ontology 4 Frames-based ontology, van Kralingen and Visser –Common legal ontology; re-useable, 3 classes of model primitives, for each class a frame structure has been defined with all relevant attributes: –Norm: 8 elements (norm identifier, norm type, promulgation, scope, conditions of application, subject, legal modality, act identifier) –Act: 14 elements (act identifier, promulgation, scope, agent, act type, modality of means, manner, temporal and spatial aspects, circumstances, cause, aim, intentionality, final state) –Concept: 7 elements (concept, concept type, priority, promulgation, scope, conditions, instances) Vocabulary: notions for actions, agents, objects, relations, properties, words indicating place, source, textual constructions, arithmetical operations and legal modality –Application: Dutch Unemployment Benefits Act 4 Good representation model, very different for scaling-up from a small ontology

6. Functional Ontology (1) 4 Functional ontology / Valente –Aim: organisation and linking of legal knowledge, in particular in respect to conceptual information retrieval –6 basic categories of legal knowledge Normative knowledge, meta-legal knowledge, world knowledge, responsibility knowledge, reactive knowledge, creative knowledge –Follow-up: ON-LINE (architecture of legal case-solving) CLIME/MILE (legal information server) PROSA (training system for legal case-solving) –Problems: modelling of world knowledge; scaling-up

7. Functional Ontology (2) Functional Ontology / Valente

8. E-Court, LRI-Core (1) 4 Project E-Court/University of Amsterdam –Goal: semi-automated multi-lingual information management for various sources (audio, video, text); application area: penal law –Main functions: audio, video and text synchronisation, advanced IR, database management, workflow management, security management –LRI-Core: broad concept structure with typical legal main concepts Basic assumptions: –Objects and processes are basic entities in the physical world –Mental entities behave mostly like physical objects –Communication is done over physical objects (documents) and actions (language) –Mental und physical world overlap in the concept of “agent” –Social order and processes consist of rules and functions that are implemented by identifiable agents as individual persons –Time and place have a two-dimensional status (position, supplementary attributes) About 200 concepts, in development

9. E-Court, LRI-Core (2) Structure LRI-Core/E-Court University of Amsterdam

10. E-Court, LRI-Core (3) 4 Anchors –Links between foundational (upper) ontology (= world knowledge) and legal core ontology (legal concepts) –Support legal subsumption –Select/direct from various acts or agents to the legally relevant ones 4 Important aspect for improving legal commentaries

11. E-Power 4 E-Power, project of the Dutch Tax and Customs Administration –Application-oriented knowledge system; formalisation of laws and regulations as conceptual models –Automated tasks (e.g. subsumption, calculation, document assembly); comprehensive support from legislation to application –Unified Modeling Language (UML)/Object Contraint Model (OCL) –Prototype: Dutch income tax law; used by Fortis Banque, Belgium, and the Pension Administration of the Dutch Finance Ministry

12. Semantic links between words and meanings 4 Automated Text Analysis / Conceptual Indexing –Text corpora are analysed for legal meanings 4 Many projects, e.g. –KONTERM/LabelSOM/GHSOM (Schweighofer et al. 1993-), Vienna University/ Vienna University for Technology –FLEXICON (Smith et al. 1990-1997), University of British Columbia –SALOMON (Moens et al. 1997-), University of Leuven –SMILE (Brünninghaus/Ashley 1999-); University of Pittsburgh 4 Advantage: high knowledge in working with text corpora 4 Problems: knowledge acquisition, scaling-up from small applications

13. WordNet (1) 4 English lexical database –Linguist George Miller/Princetone University –http://www.cogsci.princeton.edu/~wn/ 4 EuroWordNet EWN –Goal: mono and cross-lingual information retrieval –WordNet lexica for different European languages, linked by an inter-lingual index (ILI) –Basis structure of the American WordNet –Extended seminatic-lexical relations (in particular synonymy, antonymy or hyponomy) –Three top level categories ("top-ontology" with 63 semantic distinctions – 1st, 2nd, 3rd Order Entity) -

14. WordNet (2) –form together the common semantic framework for all European languages http://www.illc.uva.nl/EuroWordNet/ http://www.illc.uva.nl/EuroWordNet/ –German variant: GermaNet http://www.sfs.nphil.uni-tuebingen.de/lsd/ 4 Global WordNet –Based on WordNet and European World Net http://www.globalwordnet.org http://www.globalwordnet.org 4 WordNet = world ontology or upper level ontology (?)

15. Proposal for a Comprehensive Ontology (1) 4 Real world (world knowledge) –Subjects = persons (agents) –Objects = things –Acts or omissions (intention, negligence), processes –Formalisation using existing world ontologies (zB WordNet or CYC) 4 Legal system as a order of norms : socio-economic governance by law with the goal of risk reduction –Formalisation with a frames-based ontology –Frames for subjects (agents), objects, acts, concepts, norms, anchors

16. Proposal for a Comprehensive Ontology (2) –Extension of norm frame: including evaluation criteria of the legal order –Purpose of legal order: risk reduction –Efficiency and reasonableness as essential criteria –Criteria (bench-marking) –How high is the probability of compliance? –How high is the probability of acceptance? –How strong is the law enforcement? –How high is the required control (surveillance and sanctions)? –How high is the risk of non-compliance? –How easy can be norm be understood? –How easy is the norm to be applied? –How good is the contribution to stabilisation of behaviour? (Luhmann)

17. Proposal for a Comprehensive Ontology (3) 4 Anchor frames –Subsumption between real world and legal system 4 Dynamic and electronic commentary replacing traditional paper commentary –Legal concepts linked with: Norms –Formal rules »Application of law (procedures, execution) »Procedural charts –Material rules »Acts and omissions with legal consequences »Frames Anchors World ontology

18. Steps towards a Comprehensive Ontology 4 Start: information system (text archive) Published, communicated and documented legal order; now in the form of a legal information and search machine 4 Hybrid knowledge-based system 4 Advanced vocabulary 4 Pre-ontology

19. Hybrid knowledge-based system 4 Concept proposed by Schweighofer (1996) 4 Information system should be transformed into such a system by (semi)automatic analysis –Norms as logical sentences or process diagrams (e.g. SoftLaw) –Classification (e.g. GHSOM, LabelSOM) –Cross-references (e.g. AustLII, SiteSeer) –Concept analysis (e.g. KONTERM) –Summaries (e.g. KONTERM, FLEXICON) –(Semi)automatic text analysis 4 Result: semantic description of the legal order; some “primitive” anchors to legal system and world knowledge

20. Advanced lexical ontologies 4 Vocabularies and thesauri, classifications –Anchors between world and legal order 4 Types –Verbal, non-verbal –Different levels of thesauri (lawyers, laymen, librarians) 4 Advantages Reduction of world complexity Description of structure of vocabulary: synonymy, homonymy, polysemy, antinomy, generic terms, sub terms Linking of different linguistic levels Linking of different languages Legal input: Linking of legal concepts with facts (world knowledge)

21. LOIS Lexical Ontologies for legal Information Serving –10 European partners (universities and enterprises) –Multi-lingual access to European legal databases –Formal representation of legal concepts in all languages on the basis of the WorldNet technology; similar concepts –6 languages should be linked (synsets, EWN) Italian, Dutch, Portuguese, German, Czech, English –Project duration: 24 months; result: 5000 synsets in each language –Further research: Information retrieval: improved techniques Document standards: common XML standard for the representation of legal documents Commercial use of public sector information Showcase Applications: test and demonstration purposes Product integration: integration in commercial applications

22. Pre-ontology 4 Transformation of hybrid knowledge-based system in a frame structure for norms using advanced vocabularies Norm frame (e.g. van Kralingen) –Type of norm (typology of Hohfeld or better Herrestad) –Links to the advanced vocabularies (e.g. for subsumption) –Links to concept frames Concept frames Extension: socio-economic description of norm (risk reduction)

23. Potential for Courts (1) 4 Improving existing legal information systems –Hybrid knowledge based system –Advances lexical ontologies Improved access; better description –Pre-ontologies Formalisation of laws and court decisions –Norms will be formalized in a frame-based structure –Procedures will be presented as procedural models

24. Potential for Courts (2) 4 Final goal: dynamic electronic commentary –Comprehensive description of the legal order –Precise links from legal concepts to world knowledge Lexical ontologies –Dynamic and (semi)automatic description –Efficiency criteria for each norm (risk reduction) 4 Advantages –Better description of world and its legal consequences –Legal subsumption easier and quicker

25. Conclusions 4 Ontologies are the key for a computer-useable formalisation of the world and the legal system 4 Integration of all existing ontologies required 4 Comprehensive model necessary 4 Intermediate steps necessary: legal information system, hybrid knowledge system, thesauri, pre- ontologies 4 Ontology will be a new form of a legal commentary 4 Ontology will be comprehensive instrument of analysis of legal order; risk reduction is central element of efficiency evaluation