NomosT: Building large models of law with a tool-supported process

被引:6
|
作者
Zeni, N. [1 ]
Seid, E. A. [1 ]
Engiel, P. [2 ]
Mylopoulos, J. [1 ]
机构
[1] Univ Trento, Dept Informat Engn & Comp Sci, Trento, Italy
[2] Pontificia Univ Catolica Rio de Janeiro, Programa Posgrad Informat, Rio de Janeiro, Brazil
关键词
LEGAL; EXTRACTION;
D O I
10.1016/j.datak.2018.04.009
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Laws and regulations impact the design of software systems, as they introduce new requirements and constrain existing ones. The analysis of a software system and the degree to which it complies with applicable laws can be greatly facilitated by models of applicable laws. However, laws are inherently voluminous, often consisting of hundreds of pages of text, and so are their models, consisting of thousands of concepts and relationships. This paper studies the possibility of building models of law semi-automatically by using the NomosT tool. Specifically, we present the NomosT architecture and the process by which a user constructs a model of law semi-automatically, by first annotating the text of a law and then generating from it a model. We then evaluate the performance of the tool relative to building a model of a fragment of law manually. In addition, we offer statistics on the quality of the final output that suggest that tool supported generation of models of law reduces substantially human effort without affecting the quality of the output.
引用
收藏
页码:407 / 418
页数:12
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