Representing and reusing explanations of legal precedents

ABSTRACT

Precedent-based legal reasoning depends on accurate assessment of relevant similarities between new cases and existing precedents. Determining the relevant similarities between a new case and a precedent with respect to a legal category requires knowing the explanation of the precedent's membership in the category. GREBE is a system that uses both general legal rules and specific explanations of precedents to evaluate legal predicates in new cases. GREBE assesses the similarity of a new case to a precedent of a legal category by attempting to find a pattern of relations in the new case that corresponds to the facts of the precedent responsible for its category membership. Missing relations in the new case are inferred by reusing other explanations from past cases.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.1 Applications and Expert Systems
          Subjects: Law

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.3 Deduction and Theorem Proving
          Subjects: Answer/reason extraction
      I.2.4 Knowledge Representation Formalisms and Methods
          Subjects: Representations (procedural and rule-based)

General Terms:
Design, Legal Aspects