Legal information retrieval is in need of the provision of legal knowledge for the improvement of search strategies. For this purpose, the LOIS project is concerned with the construction of a multilingual WordNet for cross-lingual information retrieval in the legal domain. In this article, we set out how a hybrid approach, featuring lexically and legally grounded conceptual representations, can fit the cross-lingual information retrieval needs of both legal professionals and laymen.

In the legal domain, ontologies enjoy quite some reputation as a way to model normative knowledge about laws and jurisprudence. This paper describes the methodology followed when developing the ontology used by the second version of the prototype Iuriservice, a web-based intelligent FAQ for judicial use. This modeling methodology has had two important requirements: on the one hand, the ontology needed to be extracted from a repository of professional judicial knowledge (containing nearly 800 questions regarding daily practice). Thus, the construction (...) of ontologies of professional judicial knowledge demanded the description of this knowledge as it is perceived by the judge. On the other hand, due to the distributiveness of the environment, there was a need for controlled discussion and traceability of the arguments used in favor or against the introduction of a concept X as part of the domain ontology. This paper presents the Ontology of Professional Judicial Knowledge (OPJK), extracted manually from the selection of relevant terms from judicial practice questions and modeled according to the DILIGENT methodology. We will show that DILIGENT has proved to be a methodology that facilitates the ontology engineering in a distributed environment, although appropriate tool support needs to be developed. (shrink)

A variety of legal documents are increasingly being made available in electronic format. Automatic Information Search and Retrieval algorithms play a key role in enabling efficient access to such digitized documents. Although keyword-based search is the traditional method used for text retrieval, they perform poorly when literal term matching is done for query processing, due to synonymy and ambivalence of words. To overcome these drawbacks, an ontological framework to enhance the user’s query for retrieval of truly relevant legal judgments has (...) been proposed in this paper. Ontologies ensure efficient retrieval by enabling inferences based on domain knowledge, which is gathered during the construction of the knowledge base. Empirical results demonstrate that ontology-based searches generate significantly better results than traditional search methods. (shrink)

In this article we describe two core ontologies of law that specify knowledge that is common to all domains of law. The first one, FOLaw describes and explains dependencies between types of knowledge in legal reasoning; the second one, LRI-Core ontology, captures the main concepts in legal information processing. Although FOLaw has shown to be of high practical value in various applied European ICT projects, its reuse is rather limited as it is rather concerned with the structure of legal reasoning (...) than with legal knowledge itself: as many other “legal core ontologies”, FOLaw is therefore rather an epistemological framework than an ontology. Therefore, we also developed LRI-Core. As we argue here that legal knowledge is based to a large extend on common-sense knowledge, LRI-Core is particularly inspired by research on abstract common-sense concepts. The main categories of LRI-Core are: physical, mental and abstract concepts. Roles cover in particular social worlds. Another special category are occurrences; terms that denote events and situations. We illustrate the use of LRI-Core with an ontology for Dutch criminal law, developed in the e-Court European project. (shrink)

I shall compare two views of legal concepts: as nodes in inferential nets and as categories in an ontology (a conceptual architecture). Firstly, I shall introduce the inferential approach, consider its implications, and distinguish the mere possession of an inferentially defined concept from the belief in the concept’s applicability, which also involves the acceptance of the concept’s constitutive inferences. For making this distinction, the inferential and eliminative analysis of legal concepts proposed by Alf Ross will be connected to the views (...) on theoretical concepts in science advanced by Frank Ramsey and Rudolf Carnap. Consequently, the mere comprehension of a legal concept will be distinguished from the application of the concept to a particular legal system, since application presupposes a doctrinal commitment, namely, the belief that the inferences constituting the concept hold in that system. Then, I shall consider how concepts can be characterised by defining the corresponding terms and placing them within an ontology. Finally, I shall argue that there is a tension between the inferential and the ontological approach, but that both need to be taken into account, to capture the meaning and the cognitive function of legal concepts. (shrink)

This article provides an overview of, and thematic justification for, the special issue of the journal of Artificial Intelligence and Law entitled “E-Discovery”. In attempting to define a characteristic “AI & Law” approach to e-discovery, and since a central theme of AI & Law involves computationally modeling legal knowledge, reasoning and decision making, we focus on the theme of representing and reasoning with litigators’ theories or hypotheses about document relevance through a variety of techniques including machine learning. We also identify (...) two emerging techniques for enabling users’ document queries to better express the theories of relevance and connect them to documents: social network analysis and a hypothesis ontology. (shrink)