  Knowledge representation and reasoning in law are essential to facilitate the
automation of legal analysis and decision-making tasks. In this paper, we
propose a new approach based on legal science, specifically legal taxonomy, for
representing and reasoning with legal documents. Our approach interprets the
regulations in legal documents as binary trees, which facilitates legal
reasoning systems to make decisions and resolve logical contradictions. The
advantages of this approach are twofold. First, legal reasoning can be
performed on the basis of the binary tree representation of the regulations.
Second, the binary tree representation of the regulations is more
understandable than the existing sentence-based representations. We provide an
example of how our approach can be used to interpret the regulations in a legal
document.
