Automatic semantics extraction in law documents

Biagioli, Carlo; Francesconi, Enrico; Passerini, Andrea; Montemagni, Simonetta; Soria, Claudia

doi:10.1145/1165485.1165506

Cited by 119 publications

(84 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…page 14) noted that SVMs were better than patterns at categorisation where word order was less restricted. Biagioli et al [6] classified paragraphs from Italian law using Multiclass Support Vector Machines. However, they were also concerned with classification into types rather than topics, in their case high-level meta-classes such as 'Prohibition Action', 'Obligation Addressee', 'Substitution', and so on.…”

Section: Related Workmentioning

confidence: 99%

Eunomos, a Legal Document and Knowledge Management System to Build Legal Services

Boella

Humphreys

Martín

et al. 2012

Lecture Notes in Computer Science

View full text Add to dashboard Cite

This paper describes the Eunomos software, an advanced legal document and knowledge management system, based on legislative XML and ontologies. We describe the challenges of legal research in an increasingly complex, multi-level and multi-lingual world and how the Eunomos software helps users cut through the information overload to get the legal information they need in an organized and structured way and keep track of the state of the relevant law on any given topic. We describe the core system from workflow and technical perspectives, and discuss applications of the system for various user groups and our long term vision towards an Internet of Social Things, where laws can have an identity and be manipulated adding interpretation and can proactively inform interested users of their changes over time.

show abstract

Section: Related Workmentioning

confidence: 99%

Eunomos, a Legal Document and Knowledge Management System to Build Legal Services

Boella

Humphreys

Martín

et al. 2012

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…A pilot-case is considered of about 100 modificatory provisions from a corpus of 8 Italian laws. 5 A project that has some commonalities with our research is SALEM [8,9,38,14,39]. SALEM automatically annotates the modificatory provisions of NIR documents by using syntactic parsing and uses a rule-based strategy to fill the semantic frames.…”

Section: Related Workmentioning

confidence: 99%

“…Indeed, these idioms can hide the information necessary for the TULSI system to correctly qualify 8 Corpo is the Italian word for body. 9 Rif stands for riferimento, the Italian word for reference. 10 Vir stands for virgolette, the Italian word for quotes.…”

Section: Handling Frequent Annotation Errorsmentioning

confidence: 99%

“…Although highly valuable, a human annotation process is expensive and error-prone. 3 Several tools were developed in the last decade for minimizing manual annotations using parsers to detect normative references and legal text structure [32,9,17]. Such efforts will fully be exploited in conjunction with NLP tools to extract structural and semantic data from legal texts.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

TULSI: an NLP system for extracting legal modificatory provisions

et al. 2012

View full text Add to dashboard Cite

In this work we present the TULSI system (so named after Turin University Legal Semantic Interpreter), a system to produce automatic annotations of normative documents through the extraction of modificatory provisions. TULSI relies on a deep syntactic analysis and a shallow semantic interpreter that are illustrated in detail. We report the results of an experimental evaluation of the system and discuss them, also suggesting future directions for further improvement.

show abstract

“…Machine Learning supports classification, clustering, filtering, extraction, retrieval and data mining services to text processing [18]. Information Retrieval Systems (IRS) employ artificial intelligence mechanisms not only to retrieve information but also helpful in decision support [14]. IRS is strongly supported with Tautology, Boolean Algebra and Fuzzy Logic to affectively extract knowledge from information.…”

Section: Introductionmentioning

confidence: 99%

An Enumerative Framework for extraction of Bag-of-Words from Legal Documents

2015

ajcsit

View full text Add to dashboard Cite

Automatic semantics extraction in law documents

Cited by 119 publications

References 16 publications

Eunomos, a Legal Document and Knowledge Management System to Build Legal Services

Eunomos, a Legal Document and Knowledge Management System to Build Legal Services

TULSI: an NLP system for extracting legal modificatory provisions

An Enumerative Framework for extraction of Bag-of-Words from Legal Documents

Contact Info

Product

Resources

About