Towards Annotating and Extracting
Textual Legal Case Elements
ADAM WYN ER∗
SUMM ARY:1. Introduction – 2. Background and Materials – 3. Methodology Using
GATE – 3.1. Gazetteer Lists – 3.2. JAPE Rules – 3.3. Results – 4. Conclusion
1. INT RODU CTI ON
In common law contexts, judges and juries decide a legal case to follow
previously decided cases (precedents) rather than legislation as in civil law
contexts1. The set of such cases is the legal case base. Legal professionals
must ﬁnd, analyse, and reason with and about cases drawn from the case
base in the course of arguing for a decision in a current undecided case.
A range of elements of cases may be relevant to query and extract such as
the citation index, participants, locale, jurisdiction, representatives, judge,
prototypical fact patterns (factors), applicable law, and others. Commercial
providers of legal information allow legal professionals to search the case
base by keywords and meta data. However, the case base and search tools are
proprietary, of limited, non-extensible functionality, and are restricted ac-
cess. Moreover, no provider works with Semantic Web functionalities such
as ontologies or rich XML annotations, nor are natural language processing
techniques applied to the cases to support analysis to acquire information.
Text annotation of unstructured linguistic information is a signiﬁcant,
difﬁcult aspect of the “knowledge bottleneck” in legal information process-
ing. In this paper, we apply natural language processing tools to textual
elements in cases, which are unstructured text, to produce annotated text,
from which information can be extracted, thus contributing to overcoming
the bottleneck. The extracted information can then be submitted to further
processes. Where the annotations are associated with an ontology2along
∗The Author is ResearchAssociate at University of Liverpool, Department of Computer
1Correspondence to Adam Wyner firstname.lastname@example.org.
2A. WYNE R, R. HOE KSTR A,A Legal Case OWLOntology with an Inst antiation of Popov
v. Hayashi, in “Knowledge Engineering Review”,Vol. 14, 2010, n. 2, pp. 1-24.