Розширення можливостей онтологiчного моделювання правових знань з допомогою елементiв нечiткої логiки

Lawyers use a reasoning process known as legal reasoning to solve legal problems. Legal expert systems could potentially help lawyers solve legal problems more quick and adequately, enable students to study law at school or at home more easily, and help legal scholars and professionals analyze the law and legal systems more clearly and precisely.In 1992, Hajime Yoshino of Meiji Gakuin University started a “Legal Expert Systems” project. This “Legal Expert” project is funded by the Japanese Ministry of Education, Science and Culture and is scheduled to run from May 1992 to March 1998. Yoshino organized over 30 lawyers and computer scientists to clarify legal knowledge and develop legal expert systems.This project covers a wide range of technologies such as the analysis of legal knowledge, the analysis of legal rules on international trade (United Nations Convention on Contracts for International Sale of Goods (CISG)), legal knowledge representation, legal inference models, utility programs to develop legal knowledge bases, and user interfaces. This project, which ends in March 1998, will focus on developing comprehensive legal expert systems as the final product. In this issue, we present 12 papers written by “Legal Expert” project members.In this number, Hajime Yoshino gives are overview of the legal expert systems project, explaining its aims, objectives, and organization. Six papers that follow his introduction include three on case-based reasoning. Legal rules are given by ambiguous predicates, making it difficult sometimes to determine whether conditions for rules are satisfied by the facts given of an event. In such cases, lawyers often refer to old cases and generate hypotheses through analogical reasoning.Kaoru Hirota, Hajime Yoshino and Ming Qiang Xu apply fuzzy theory to case-based reasoning. A number of related systems have been developed, but most focus on qualitative similarities between old cases and the current case, and cannot measure quantitative similarities. Hirota et al. treat quantitative similarity by applying fuzzy theory, explaining their method using CISG examples.Ken Satoh developed a way to compute an interpretation of undefined propositions in a legal rule using adversarial case-based reasoning. He translated old cases giving possible interpretations for a proposition into clauses in abductive logic programming and introduced abducibles to reason dynamically about important factors in an old case to the interpretation suiting the user’s purpose.Yoshiaki Okubo and Makoto Haraguchi formalized a way of attacking legal argument. Assume that an opponent has constructed a legal argument by applying a statute with an analogical interpretation. From the viewpoint of legal stability, the same statue for similar cases should be applied with the same interpretation. We thereby create a hypothetical case similar to the case in question and examine whether the statue can be interpreted analogically. Such a hypothetically similar case is created with the help of a goal-dependent abstraction framework. If a precedent in which a statue has been applied to a case with a different interpretation – particularly complete interpretation – can be found, the opponent’s argument is attacked by pointing out the incoherence of its interpretation of the statue.Takashi Kanai and Susumu Kunifuji proposed a legal reasoning system using abductive logic programming that deals with ambiguities in described facts and exceptions not described in articles. They examined the problems to be solved to develop legal knowledge bases through abductive logic programming, e.g., how to select ambiguities to be treated in abductive reasoning, how to describe time relationships, and how to describe an exception in terms of the application of abductive logic programming to legal reasoning.Toshiko Wakaki, Ken Satoh, and Katsumi Nitta presented an approach of reasoning about dynamic preferences in the framework of circumscription based on logic programming. To treat dynamic preferences correctly is required in legal reasoning to handle metarules such as lex posterior. This has become a hotly discussed topic in legal reasoning and more general nonmonotic reasoning. Comparisons of their method, Brewka’s approach, and Prakken and Sartor’s approach are discussed.Hiroyuki Matsumoto proposed a general legal reasoning model and a way of describing legal knowledge systematically. He applied his method to Japanese Maritime Traffic Law.Six more papers are to be presented in the next number

The goal of the present research is to define a Semantic Web framework for precedent modelling, by using knowledge extracted from text, metadata, and rules, while maintaining a strong text-to-knowledge morphism between legal text and legal concepts, in order to fill the gap between legal document and its semantics. The framework is composed of four different models that make use of standard languages from the Semantic Web stack of technologies: a document metadata structure, modelling the main parts of a judgement, and creating a bridge between a text and its semantic annotations of legal concepts; a legal core ontology, modelling abstract legal concepts and institutions contained in a rule of law; a legal domain ontology, modelling the main legal concepts in a specific domain concerned by case-law; an argumentation system, modelling the structure of argumentation. The input to the framework includes metadata associated with judicial concepts, and an ontology library representing the structure of case-law. The research relies on the previous efforts of the community in the field of legal knowledge representation and rule interchange for applications in the legal domain, in order to apply the theory to a set of real legal documents, stressing the OWL axioms definitions as much as possible in order to enable them to provide a semantically powerful representation of the legal document and a solid ground for an argumentation system using a defeasible subset of predicate logics. It appears that some new features of OWL2 unlock useful reasoning features for legal knowledge, especially if combined with defeasible rules and argumentation schemes. The main task is thus to formalize legal concepts and argumentation patterns contained in a judgement, with the following requirement: to check, validate and reuse the discourse of a judge - and the argumentation he produces - as expressed by the judicial text.

Since the emergence of the Semantic Web building ontologies have become quite popular and almost every conference on information science including artificial intelligence and e- Government have tracks that cover (legal) ontologies. Ontologies are the vocabularies that can be used to describe a universe of discourse. In this chapter we want to explain the roles (legal) ontologies play in the field of legal information systems and (juridical) knowledge management. We emphasize the fact that these ontologies are social constructs that can be used to express shared meaning within a community of practice and also have a normative character. Many different ontologies have been created for similar and different purposes and two of them, both core ontologies of law that specify knowledge that is common to all domains of law, will be explained in more detail. The first one, is a Functional Ontology for Law (FOLaw). This ontology describes and explains dependencies between types of knowledge in legal reasoning. FOLaw is rather an epistemological framework than an ontology, since it is concerned with the roles knowledge plays in legal reasoning rather than with legal knowledge itself. Nevertheless FOLaw has shown some practical value in various applied European ICT projects, but its reuse is rather limited. We will also explain some aspects of the LRI-Core ontology which captures the main concepts in legal information processing. LRI-Core is particularly inspired by research on abstract commonsense concepts. Legal knowledge is based upon these commonsense concepts. Since legal knowledge always refers to the ‘real world’, although in abstract terms, the main categories of LRI-Core are physical, mental and abstract concepts. Roles cover in particular social worlds. Another special category is occurrences; terms that denote events and situations. In this chapter we illustrate the use of LRI-Core with an ontology for Dutch criminal law, developed in the e- Court European project and an ontology for Dutch administrative law developed in a project for the Dutch State Council.

Legal language, as a language for special purposes, contains terms or concepts that are peculiar to that language because of the history and cultural development of the legal system to which that language pertains. This means that there are terms that can only be understood (or have meaning) in the context of that legal culture and language. Furthermore, a legal term or concept in one language may not have a corresponding term (or referent) in another language. Thus, legal concepts or terms have a particular meaning to readers of a particular legal culture, as well as having a referential function, in that they denote a certain legal concept or notion that has developed in that culture, which emphasizes the specialized nature of the relevant legal language. For this reason, scholars have defined legal terms as “cultural items”. Legal translators are faced with the asymmetry of legal systems and the resulting incongruity of legal concepts and terms. This problem arises as legal terms are embedded in the legal culture in which they have developed. Many scholars now assert that a detailed knowledge of both source and target legal terminology and cultures is essential when translating legal texts. As a key to obtaining the required knowledge that such an approach demands, this paper will explore the possibility that legal concepts and terms, are able to be viewed or treated as if they were proper names, as they have a specific meaning and a referential function to a specific concept, in a given legal language or culture. This possibility emerges from a re-evalution of the definition of proper names that has been undertaken in recent times. From this re-evaluation a theory has emerged that posits that words or expressions previously not considered as proper names, can now potentially be viewed as such. With particular regard to the concepts of sense and reference, I will apply this hypothesis in analysing the translation of legal documents from English to Italian and vice versa.

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

This paper describes ON-LINE (ONtology-based Legal Information Environment), an architecture for a legal workbench which combines two major functions: legal information serving and legal analysis. Some of the main features of ON-LINE are: the integrated storage and representation of legal text and knowledge by using interconnected knowledge aud text repositories; a representation of legal knowledge based on a functional ontology of law; the emphssis on legal modelling as a central task in legal practice. ON-LINE comprises three main modules. The Legal Information Server is able to retrieve legal information baaed on either textnal or conceptual search. The Legal Information ModelZing Toolkit is a collection of integrated tools to transform legaJ text into legal knowledge. The Legal Analysis Environment contains reasoning tools to perform two of the central legal tasks: assessment and planning. The architecture is intended to be a basis for experimentation, and it is therefore highly extensible. ONLINE is partially implemented in Common Lisp and it is supported by the LOOM system.

INTRODUCTION As Part I indicates, knowledge representation has been a key focus of AI & Law research and a key challenge for implementing systems robust enough to serve as real-world legal practice tools. Ontologies help to meet that challenge. An ontology specifies the fundamental types of things or concepts that exist for purposes of a system and sets out the relations among them. After introducing some basic information about ontologies, this chapter surveys some historically influential legal ontologies and explains some modern techniques for constructing ontologies semiautomatically. It then turns to ontological supports for statutory reasoning and for legal argumentation. In connection with the latter, an extended example illustrates ontological supports for making arguments with a small collection of cases. Finally, the chapter introduces a specialized kind of ontology, “type systems,” which are a basic text analytic tool. Type systems support automatically marking-up or annotating legal texts semantically in terms of concepts and their relations. They will play key roles in conceptual legal information retrieval and in cognitive computing. This chapter addresses the following questions. What is a legal ontology and how are legal ontologies used? What is semantic annotation? What are text annotation pipelines and what role does a type system play? What is a UIMA framework? How are legal ontologies and UIMA type systems constructed? How can developers of legal type systems take advantage of existing legal ontologies and of ontologies already developed for medicine, or for other real world domains that have legal implications? ONTOLOGY BASICS Despite its metaphysical connotations, the term “ontology” is not quite so imposing in the context of computational models. An ontology is an “explicit, formal, and general specification of a conceptualization of the properties of and relations between objects in a given domain” (Wyner, 2008). In other words, ontologies make concepts in a domain explicit so that a program can reason with them. For example, Figure 6.1 shows a simple ontology for the legal concept of contract formation. This kind of an ontology might have been useful for Ann Gardner's first-year contracts problem analyzer (Section 1.4.2) and captures concepts and relations described in Gardner (1987, pp. 121–3) such as “Manifestation of mutual consent” and “Acceptance by verbal promise.”

Today, most e-government Web sites are limited to providing and disseminating legal or legally relevant information (hereafter legal information; see “Key Terms” section). Generally speaking, the online provision of legal information is not made in line with sound educational principles. Most likely, this could be said about the provision of all kinds of information on e-government Web sites. As I am a lawyer, I only feel entitled to assess legal information. Hence, I would like to limit my reflections in this article to legal information. As a number of examples suggest, e-government Web sites are not conceived as legal e-learning environments (e.g., http://www.ch.ch, http://www.admin.ch, http://www.bund.de, http://bundesregierung.de, http://www.help.gv.at, http://europa.eu.int, http://www.firstgov.gov. All visited January 4, 2005). Problems (Mis)conceiving the state’s online presence is detrimental since the lack of educational design fails to ensure that users can assimilate and process the legal information which e-government Web sites provide in an effective and sustainable manner. Within the communicative framework applied here, mere provision means that so-called e-government addressees (see “Key Terms” section) are not assisted in their efforts to assimilate and process the legal information they find on e-government Web sites. Their chances of building up legal or legally relevant knowledge (hereafter legal knowledge) are compromised as a result. There is good reason to doubt that the prevalent uneducational design of legal information can arouse the interest of the envisaged target audience(s), let alone evoke positive emotions. Furthermore, it is to be doubted whether current design can do proper justice to the cognitive and emotional needs which e-government addressees undoubtedly have. Moreover, the lack of appropriate educational design would appear to call into question the mid- to long-term success of managing legal information on e-government Web sites in an uneducational fashion. Questions These problems raise several questions: How can e-government addressees assimilate and process legal information in a sustainable manner? How can e-government Web sites be designed such that their addressees can build up their legal knowledge more effectively? How should legal information on e-government Web sites be designed to arouse (and sustain) their target audience’s interest, offer it pleasure, and meet its cognitive and emotional needs? How should legal information management on such Web sites be practiced to assure mid- to long-term success? How might the e-government actors responsible for creating such sites reconceive what is now mere legal information dissemination as legal information communication? Would legal information on e-government Web sites need to be scripted in line with educational principles? Should such sites be designed as legal e-learning environments? Given the broad range of electronic learning environments, how would legal e-learning scenarios need to be designed in the context of e-government Web sites? Which specific requirements of what I have called legal (information) design (Brunschwig, 2001; see “Key Terms” section) would apply to legal e-learning environments on e-government Web sites? Relevance of Questions Resolving the previous problems would have a number of significant benefits: E-government addressees would be able to assimilate and process legal information in a sustainable manner. They would be able to build up their legal knowledge with fewer constraints. They would absorb legal information with greater interest, pleasure, and gratification, thereby inducing a learning curve. Their cognitive and emotional needs would be met more adequately. Moreover, the image of those responsible for managing online legal information would improve in the mid- to long term because they could no longer be (dis)qualified as merely disseminating legal information but would be acknowledged for their efforts to communicate it. In creating e-government Web sites along stringent educational principles, these sites would be conceived as legal e-learning environments much more effectively, aligning them with the specific context of e-government Web sites and their addressees’ needs. Hypothesis Designing e-government Web sites as legal e-learning environments would benefit all those concerned in the ways sketched previously above.

With the explosive growth in cloud based services, businesses are increasingly maintaining large datasets containing information about their consumers to provide a seamless user experience. To ensure privacy and security of these datasets, regulatory bodies have speci ed rules and compliance policies that must be adhered to by organizations. These regulatory policies are currently available as text documents that are not machine processable and so require extensive manual e ort to monitor them continuously to ensure data compliance. We have developed a cognitive framework to automatically parse and extract knowledge from legal documents and represent it using an Ontology. The framework captures knowledge in form of key terms, rules, topic summaries, relationships between various legal terms, semantically similar terminologies, deontic expressions, and cross-referenced legal facts and rules. We built the framework using Deep Learning technologies like Tensorflow, for word embeddings and text summarization, Gensim for topic modeling and Semantic Web technologies for building the knowledge graph. We have applied this framework to the United States government's Code of Federal Regulations (CFR) which includes facts and rules for individuals and organizations seeking to do business with the US Federal government. In this paper, we describe our framework in detail and present results of the CFR legal knowledge base that we have built using this framework. Our framework can be adopted by businesses to build their automated compliance monitoring system.

Modelling argumentation based on legal cases has been a central topic of AI and Law since its very beginnings. The current established view is that facts must be determined on the basis of evidence. Next, these facts must be used to ascribe legally significant predicates (factors and issues) to the case, on the basis of which the outcome can be established. This thesis aims to provide a method to encapsulate the knowledge of bodies of case law from various legal domains using a recent development in AI knowledge representation, Abstract Dialectical Frameworks (ADFs), as the central feature of the design method. Three legal domains in the US Courts are used throughout the thesis: The domain of the Automobile Exception to the Fourth Amendment, which has been freshly analysed in terms of factors in this thesis; the US Trade Secrets domain analysed from well-known legal case-based reasoning systems (CATO and IBP); and the Wild Animals domain analysed extensively in AI and Law. In this work, ADFs play a role akin to that of Entity-Relationship models in the design of database systems to design and implement programs intended to decide cases, described as sets of factors, according to a theory of a particular domain based on a set of precedent cases relating to that domain. The ADFs in this thesis are instantiated from different starting points: factor-based representation of oral dialogues and factor-based analysis of legal opinions. A legal dialogue representation model is defined for the US Supreme Court Oral Hearing dialogues. The role of these hearings is to identify the components that can form the basis of an argument that will resolve the case. Dialogue moves used by participants have been identified as the dialogue proceeds to assert and modify argument components in term of issues, factors and facts, and to produce what are called Argument Component Trees (ACTs) for each participant in the dialogue, showing how these components relate to one another. The resulting trees can be then merged and used as input to decide the accepted components using an ADF. The model is illustrated using two landmark case studies in the Automobile Exception domain: Carney v. California and US v. Chadwick. A legal justification model is defined to capture knowledge in a legal domain and to provide justification and transparency of legal decisions. First, a legal domain ADF is instantiated from the factor hierarchy of CATO and IBP, then the method is applied to the other two legal domains. In each domain, the cases are expressed in terms of factors organised into an ADF, from which an executable program can be implemented in a straightforward way by taking advantage of the closeness of the acceptance conditions of the ADF to components of an executable program. The proposed method is evaluated to test the ease of implementation, the efficacy of the resulting program, the ease of refinement, transparency of the reasoning and transferability across legal domains. This evaluation suggests ways of improving the decision by incorporating the case facts, and considering justification and reasoning using portions of precedents. The final result is ANGELIC (ADF for kNowledGe Encapsulation of Legal Information from Cases), a method for producing programs that decide the cases with a high degree of accuracy in multiple domains.

This article represents consideration of the creation process of legal knowledge ontology for study purposes. The peculiarities of legal information and experience of legal knowledge formalization have been scrutinized. The peculiarities of complex systems self-organization have been considered and application of these principles to legal information on the basis of four features of self-organization has been proved. It has been determined that the most reasonable way of legal knowledge description is ontology, as a basis for forming of knowledge structure. The review of existing ontologies that are used in the field of law has been carried out. Mathematical description of the knowledge base structure has been introduced. The software package has been developed for working with legal knowledge ontology. This package of programs is used by students at the Yaroslav Mudryi National Law University. The method of collective filling and editing of the knowledge base is proposed to be used as the basis of methodology for working with the knowledge base. The ontology of legal knowledge at the University has been created not only by experts but by all the users. Principles of crowdsourcing are considered as a basic technique of technological process of the ontology filling. Results of filling of this ontology by a number of users have been briefly reviewed. The legal knowledge ontology that is being created is proposed to be used for forming an individual learning style of students.

Knowledge graphs play an important role in many applications, such as data integration, natural language understanding and semantic search. Recently, there has been some work on constructing legal knowledge graphs from legal judgments. However, they suffer from some problems. First, existing work follows the Western legal system, thus cannot be applied to other legal systems, such as Asian legal systems; Second, existing work intends to build a precise legal knowledge graph, which is often not effective, especially when constructing the precise relationship between legal terms. To solve these problems, in this paper, we propose a framework for constructing a legal hybrid knowledge network from Chinese encyclopedia and legal judgments. First, we construct a network of legal terms through encyclopedia data. Then, we build a legal knowledge graph through Chinese legal judgments which captures the strict logical connections in the legal judgments. Finally, we build a Chinese legal hybrid knowledge network by combining the network of legal terms and the legal knowledge graph. We also evaluate the algorithms which are used to build the legal hybrid knowledge network on a real-world dataset. Experimental results demonstrate the effectiveness of these algorithms.

This study aims to explore different causes for the mistranslation of legal terminology in international agreements that are enforced through domestic legislation, and attempt to provide some solutions. It is said that legal training will help legal translators to render terminology correctly. This should be held true because many legal terms from different legal systems are ‘false friends’, in that even a well-trained lawyer may need to undertake extensive legal and linguistic research to render them in another language or legal system. This study, by use of a comparison of several translated legal terms from People’s Republic of China (PRC) and Taiwan, shows that besides the cause of ‘legal knowledge’, the disparities between international law and national law and different legal traditions can also lead to an improper transfer of legal terminology. Examples of these terms are “Copyright piracy” (Daoban 盗版 vs. qinhai zhuzuoquan 侵害著作权), “Good Faith” (Chengshi shouxin 诚实守信 vs. shanyi 善意), and “Inventive Step” (Famingxing de buzhou 发明性的步骤 vs. jinbuxing 进步性). In order to enhance translators’ legal knowledge, it is proposed that they be presented with some substantive laws together with simple illustrations of their structures. Translators should crosscheck their translations against a wide range of sources at work.

The increasing development of legal ontologies seems to offer satisfactory solutions to legal knowledge formalization, which in past experiences lead to a limited exploitation of legal expert systems for practical and commercial use. The paper describes some ontology-based tools that enable legal knowledge formalization. Jurwordnet is an extension to the legal domain of the Italian version of EuroWordNet. It is a content description model for legal information and a lexical resource for accessing multilingual and heterogeneous information sources. Its concepts are organised according to a “Core Legal Ontology” (CLO), based on DOLCE+, an extension of the DOLCE foundational ontology. Jurwordnet and CLO are also used to represent the assessment of legal regulatory compliance across different legal systems or between norms and cases. An example is discussed concerning compliance between EC directives and national legislations.KeywordsLegal KnowledgeLegal SubjectLegal DomainConstitutive NormLegal OntologyThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Full text search in the legal domain is not enough, because there is a gap between common sense and legal knowledge. We want to present some possible directions to solve the problem of full text search in legal domain. The gap can be bridged using a model that mixes tags from Eurovoc Thesaurus Schema Ontology and legal ontology in order to enrich information retrieval capabilities in the legal domain.