Solon: A Holistic Approach for Modelling, Managing and Mining Legal Sources

Abstract

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 and explore legal resources according to their individual needs. To demonstrate the applicability and usefulness of our approach, Solon has been successfully deployed in a public sector production environment, making Greek tax legislation easily accessible to the public. Opening up legislation in this way will help increase transparency and make governments more accountable to citizens.

Application of an Ecosystem Methodology Based on Legal Language Processing for the Transformation of Court Decisions and Legal Opinions into Open Data

“…In total, more than 140,000 documents were automatically processed and marked up in XML in approximately 15 d (as already discussed, this performance could be much better if the Java instance of ANTLR was used) with a percentage of valid XML files around 90%, while manual markup would require several man-months or even man-years and would result at a much higher cost (we should note that the server used for the processing of the legal texts costs less than 1800 Euros). Moreover, we conducted an evaluation of the approach that treats legal language as a Domain Specific Language, since Koniaris et al [20], who also employed the DSL approach in a similar research, do not provide evaluation results on the quality of the transformation. The quality evaluation of the markup that we performed confirms the conclusion of Sannier et al [12], according to which automatic approaches for the markup are effective and the amount of required manual effort is relatively low.…”

“…In the Related Work section, we referenced two research projects oriented towards Greek legal documents that can be applied in texts written in the Greek language. In [20], neither the source code of the "Solon" platform nor the set of grammar rules used for legal text parsing are published. On the other hand, while the legal parser presented in [19] is available on Github, it is used to parse documents of the Government Gazette and detect their structure and cannot be used to extract structural elements of court decisions or legal opinions.…”

“…Chalkidis et al [19] implemented a rule-based parser that parses PDF documents of the Greek Government Gazette and transforms them into Linked Open Data (RDF triples). In [20] Koniaris et al describe a DSL based approach for parsing legal documents, identifying their structural elements and metadata, and converting plain text to XML following the LegalDocML schema. Regular expressions are used to detect legal citations and interlink the documents.…”

“…In this work, we treat legal language as a Domain Specific Language (DSL), an approach also followed by Koniaris et al for other legal documents types in [20]. DSLs are languages specifically tailored for the needs of a particular problem or application domain [38], in our case that being the legal domain.…”

“…To achieve our goal, we used ANTLR v4 (ANother Tool for Language Recognition) [39], a popular lexer and parser generator. ANTLR is already used for parsing tasks in the legal domain, e.g., by the legal analytics company Lex Machina or by the Solon platform [20] for extracting structural and semantic information from legal texts. When the appropriate lexer and parser grammars are defined, ANTLR is able to generate:…”