Building a Semantically Rich Legal Case Repository in OWL

Yueting Shen, Research Assistant, Department of Computer Systems, Faculty of Information Technology, University of Technology, Sydney. Email: ritashen@it.uts.edu.au

Robert Steele, Associate Professor, Department of Computer Systems, Faculty of Information Technology, University of Technology, Sydney. Email: rsteele@it.uts.edu.au

John Murphy, PhD Candidate, Department of Computer Systems, Faculty of Information Technology, University of Technology, Sydney. Email: John.E.Murphy@it.uts.edu.au

Keywords

Legal case,ontology, conceptual retrieval, OWL, knowledge representation

Abstract

The retrieval of conceptual information from legal documents depends on the construction of a knowledge representation of the document. A number of interesting research works on legal case knowledge representation have been proposed including frame-like structures, semantic nets and dimensions. However some limitations exist in these works. For instance, some render little inferencing capabilities, some ignore contextual information essential to conceptual retrieval and some give no consideration to semantic interoperability. Our work addresses these limitations by using an open standard ontology language and a refined ontology architecture. Our ontology is easy to maintain, reuse, extend and renders rich inferencing and reasoning capabilities. In addition, a framework is proposed in our work in order to integrate heterogeneous knowledge representations and to reduce the manual effort required for the annotation process by enabling semi-automation of the annotation process.