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A knowledge-centered framework for exploration and retrieval of legal documents
Information Systems ( IF 3.7 ) Pub Date : 2021-07-07 , DOI: 10.1016/j.is.2021.101842
Silvana Castano 1 , Mattia Falduti 1 , Alfio Ferrara 1 , Stefano Montanelli 1
Affiliation  

Automated legal knowledge extraction systems are strongly demanded, to support annotation of legal documents as well as knowledge extraction from them, to provide useful and relevant suggestions to legal actors (e.g., judges, lawyers) for managing incoming new cases.

In this paper, we propose CRIKE (CRIme Knowledge Extraction), a knowledge-based framework conceived to support legal knowledge extraction from a collection of legal documents, based on a reference legal ontology called LATO (Legal Abstract Term Ontology). We first introduce LATO-KM, the knowledge model of LATO where legal knowledge featuring documents in the collection is properly formalized as conceptual knowledge, in form of legal concepts and relationships, and terminological knowledge, in form of term-sets associated with legal concepts. Then, we present the bootstrapping cycle of CRIKE that aims to progressively enrich the terminological knowledge layer of LATO by extracting new terms from legal documents to be used for enriching the term-set associated with a corresponding legal concept. Finally, to evaluate the results obtained through CRIKE, we discuss experimental results on a real dataset of 180,000 court decisions of the State of Illinois taken from the Caselaw Access Project (CAP).



中文翻译:

一个以知识为中心的法律文件探索和检索框架

强烈需要自动化的法律知识提取系统,以支持法律文件的注释以及从中提取知识,为法律行为者(例如法官、律师)提供有用和相关的建议,以管理新案件。

在本文中,我们提出了CRIKE (CRIme Knowledge Extraction),一种基于知识的框架,旨在支持从法律文件集合中提取法律知识,基于称为 LATO(法律抽象术语本体)的参考法律本体。我们首先介绍 LATO-KM,这是 LATO 的知识模型,其中以集合中的文件为特征的法律知识被适当地形式化为概念知识,以法律概念和关系的形式,以及术语知识,以与法律概念相关的术语集的形式。然后,我们提出了 CRIKE 的引导循环,旨在通过从法律文件中提取新术语来逐步丰富 LATO 的术语知识层,用于丰富与相应法律概念相关的术语集。最后,为了评估通过 CRIKE 获得的结果,

更新日期:2021-07-07
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