Skip to Main content Skip to Navigation
Conference papers

Combining NLP Approaches for Rule Extraction from Legal Documents

Mauro Dragoni 1 Serena Villata 2 Williams Rizzi 1 Guido Governatori 3
2 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : Legal texts express conditions in natural language describing what is permitted, forbidden or mandatory in the context they regulate. Despite the numerous approaches tackling the problem of moving from a natural language legal text to the respective set of machine-readable conditions, results are still unsatisfiable and it remains a major open challenge. In this paper, we propose a preliminary approach which combines different Natural Language Processing techniques towards the extraction of rules from legal documents. More precisely, we combine the linguistic information provided by WordNet together with a syntax-based extraction of rules from legal texts, and a logic-based extraction of dependencies between chunks of such texts. Such a combined approach leads to a powerful solution towards the extraction of machine-readable rules from legal documents. We evaluate the proposed approach over the Australian " Telecommunications consumer protections code " .
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-01572443
Contributor : Serena Villata <>
Submitted on : Monday, August 7, 2017 - 1:49:06 PM
Last modification on : Tuesday, May 26, 2020 - 6:50:41 PM

File

MIREL2016.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01572443, version 1

Collections

Citation

Mauro Dragoni, Serena Villata, Williams Rizzi, Guido Governatori. Combining NLP Approaches for Rule Extraction from Legal Documents. 1st Workshop on MIning and REasoning with Legal texts (MIREL 2016), Dec 2016, Sophia Antipolis, France. ⟨hal-01572443⟩

Share

Metrics

Record views

1099

Files downloads

5265