Automated Detection of Reference Structures in Law (original) (raw)
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Reference Extraction and Resolution for Legal Texts
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An application to the legal domain of information extraction is presented. Its goal is to automate the extraction of references from legal documents, their resolution, and the storage of their information in order to facilitate an automatic treatment of these information items by services offered in digital libraries. References are extracted matching the texts in the collection against sets of patterns, using grammars.
Dealing with automatic reference extraction in the legal domain digital libraries
Palabras clave : Referencias, extracción de información, textos jurídicos Résumé Nous présentons une application de l'extraction d'information au domaine juridique. Le but est d'automatiser l'extraction de références des documents juridiques (par un analyse du contenu). Les informations concernant les références extraites sont stockées, et utilisées par des services offerts dans les bibliothèques électroniques. Le traitement couvre l'analyse du domaine juridique à l'implantation des logiciels, et quelques expérimentations. Ce travail est fait en collaboration avec des juristes.
Solon: A Holistic Approach for Modelling, Managing and Mining Legal Sources
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Recently there has been an exponential growth of the number of publicly available legal resources. Portals allowing users to search legal documents, through keyword queries, are now widespread. However, legal documents are mainly stored and offered in different sources and formats that do not facilitate semantic machine-readable techniques, thus making difficult for legal stakeholders to acquire, modify or interlink legal knowledge. In this paper, we describe Solon, a legal document management platform. It offers advanced modelling, managing and mining functions over legal sources, so as to facilitate access to legal knowledge. It utilizes a novel method for extracting semantic representations of legal sources from unstructured formats, such as PDF and HTML text files, interlinking and enhancing them with classification features. At the same time, utilizing the structure and specific features of legal sources, it provides refined search results. Finally, it allows users to connect a...
International Conference on Legal Knowledge and Information Systems, 2017
In this paper we present the BO-ECLI Parser, an open framework for the extraction of legal references from case-law issued by judicial authorities of European member States. The problem of automatic legal links extraction from texts is tackled for multiple languages and jurisdictions by providing a common stack which is customizable through pluggable extensions in order to cover the linguistic diversity and specific peculiarities of national legal citation practices. The aim is to increase the availability in the public domain of machine readable references metadata for case-law by sharing common services, a guided methodology and efficient solutions to recurrent problems in legal references extraction, that reduce the effort needed by national data providers to develop their own extraction solution. Keywords. natural language processing, legal references, case law databases, linked open data 1 Council conclusions inviting the introduction of the European Case Law Identifier (ECLI) and a minimum set of uniform metadata for case law (CELEX:52011XG0429(01)).
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Texts referencing court decisions, statutes, and EU directives can be difficult to understand without context. It can be time consuming and expensive to find related statutes or to learn about context specific terminology. As a solution, we utilized an automatic annotation tool, Nelli, for extracting information and tailored it to a service that can automatically annotate legal documents to provide context to the readers. The service can identify and link named entities and references to legal texts to corresponding vocabularies and data sources by combining statisticsand rule-based named entity recognition with named entity linking. The results provide users with enhanced reading experience with contextual information and possibility to access related materials such as statutes and court decisions.
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While formalizing legal sources is an important challenge, the generation of a formal representation from legal texts has been far less considered and requires considerable expertise. In order to improve the uniformity, richness, and efficiency of legal annotation, it is necessary to experiment with annotations and the annotation process. This paper reports on a first experiment, which was a campaign to annotate legal instruments provided by the Scottish Government's Parliamentary Counsel Office and bearing on Scottish smoking legislation and regulation. A small set of elements related to LegalRuleML was used. An initial guideline manual was produced to annotate the text using annotations related to these elements. The resulting annotated corpus is converted into a LegalRuleML XML compliant document, then made available via an online visualisation and query tool. In the course of annotating the documents, a range of important interpretive and practical issues arose, highlighting the value of a focused study on legal text annotation.
LegalVis: Exploring and Inferring Precedent Citations in Legal Documents
IEEE Transactions on Visualization and Computer Graphics, 2022
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Annotating legal documents with GaiusT 2.0
International Journal of Metadata, Semantics and Ontologies , 2017
We present the GaiusT 2.0 framework for annotating legal documents. The framework was designed and implemented as a web-based system to semi-automate the extraction of legal concepts from text. In requirements analysis these concepts can be used to identify requirements a software system has to fulfil to comply with a law or regulation. The analysis and annotation of legal documents in prescriptive natural language is still an open problem for research in the field. In GaiusT 2.0, a multistep process exploits a number of linguistic and technological resources to offer a comprehensive annotation environment. The modules of the system are presented as evolutions from corresponding modules of the original GaiusT framework, which in turn was based on a general-purpose annotation tool, Cerno. The application of GaiusT 2.0 is illustrated with two use cases, to demonstrate the extraction process and its adaptability to different law models.