Semantic Annotation of Legal Contracts with ContrattoA

Lecture Notes in Computer Science, 2018

This paper describes a task of semantic labeling of document segments. The idea exploits ontology in providing a fine-grained conceptual document annotation. We describe a way of dividing a document into its constituent semantically-coherent blocks. These blocks are then used to perform conceptual tagging for efficient passage information retrieval. The proposed task interfaces other application areas such as intra-mapping of ontologies, text summarization and information extraction. The system has been evaluated on a task of conceptual tagging of documents and achieved a promising result.

Empirical Software Engineering, 2021

Semantic legal metadata provides information that helps with understanding and interpreting legal provisions. Such metadata is therefore important for the systematic analysis of legal requirements. However, manually enhancing a large legal corpus with semantic metadata is prohibitively expensive. Our work is motivated by two observations: (1) the existing requirements engineering (RE) literature does not provide a harmonized view on the semantic metadata types that are useful for legal requirements analysis; (2) automated support for the extraction of semantic legal metadata is scarce, and it does not exploit the full potential of artificial intelligence technologies, notably natural language processing (NLP) and machine learning (ML). Our objective is to take steps toward overcoming these limitations. To do so, we review and reconcile the semantic legal metadata types proposed in the RE literature. Subsequently, we devise an automated extraction approach for the identified metadata types using NLP and ML. We evaluate our approach through two case studies over the Luxembourgish legislation. Our results indicate a high accuracy in the generation of metadata annotations. In particular, in the two case studies, we were able to obtain precision scores of 97.2% and 82.4%, and recall scores of 94.9% and 92.4%.

Language Resources and Evaluation, 2018

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.

Cornell University - arXiv, 2022

A Smart Legal Contract (SLC) is a specialized digital agreement that consists of natural language and computable components. The Accord Project is an open-source SLC framework containing three main modules: Cicero, Concerto, and Ergo. Currently, we need lawyers, programmers, and clients to work together with a great deal of effort to create a useable SLC using the Accord Project. This paper proposes a pipeline to automate the SLC creation process with several NLP models to convert law contracts to the Accord Project's SLC format. We then further describe an interface enabling users to build their SLC with the proposed pipeline.

Frontiers in artificial intelligence and applications, 2023

This paper presents LeDA, a system for Legal Data Annotation. The system offers the functionality of annotating and categorising text spans representing legal concepts that capture the topic of a document, and also supports a metaannotator to adjudicate the ground truth created by different annotators. Notably, our system supports a dynamic update of the ontology by enabling the creation of new legal concepts. Currently employed to annotate key legal concepts, LeDA aims to construct concept-based semantic representations for tasks such as similar case retrieval, and judgment prediction.

2009

This paper illustrates a system designed to automatically extract semantic annotations of the normative modifications present in legal texts. The work relies on a deep parsing approach. The problem of semantically annotating legal texts is cast to the problem of mapping parse trees to semantic frames representing such modifications. We report a preliminary experimentation along with the dataset employed, and discuss the results to point out future improvements.

Semantic Web, 2016

A Semantic Web approach for an advanced access to legislative documents is presented in terms of a model of normative provisions and related axioms. In particular, relations between provisions are identified and modeled by introducing patterns able to describe Hohfeldian legal fundamental relations. Moreover, a query-based approach able to deal with relations between provision specific instances is described. Examples of semantic annotation of legal textual resources using RDF/OWL standards, as well as advanced access and reasoning facilities over provisions using SPARQL, are shown. The main benefit of the approach is represented by the ability to keep the complexity of the problem within a description logic computational tractability.

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.

Legal knowledge and …, 2009

In this work we present STIA a tool for text annotation in the jurisprudence domain. The tool offers an easy interface to experts (lawyers, administrative, researchers,…) for annotating qualified relationships between parts of different laws. Successively, the resulting conceptual annotations feed a complex process to retrieve specific relationships between texts (groups of sentences inside a section) of two laws for new application tasks…

2012

In this work we illustrate a novel approach for solving an information extraction problem on legal texts. It is based on Natural Language Processing techniques and on the adoption of a formalization that allows coupling domain knowledge and syntactic information. The proposed approach is applied to extend an existing system to assist human annotators in handling normative modificatory provisions-that are the changes to other normative texts-. Such laws 'versioning' problem is a hard and relevant one. We provide a linguistic and legal analysis of a particular case of modificatory provision (the efficacy suspension), show how such knowledge can be formalized in a linguistic resource such as FrameNet, and used by the semantic interpreter.