Emile de Maat

Automated classification of norms in sources of law

The research described here attempts to achieve automated support for modelling sources of law for legal knowledge based systems and services. Many existing systems use models that do not reflect the entire law, and simplify parts of the text. These models are difficult to validate, maintain and re-use. We propose to create an intermediate model that has an isomorphic representation of the structure of the original text. A first step towards automated modelling is the detection and classification of provisions in sources of law. A list of different categories of norms and provisions that are used in Dutch legal texts is presented. These categories can be identified by the use of typical text patterns. Next, the results of experiments in automated classification of provisions using these patterns are presented. 91% of 592 sentences in fifteen different Dutch laws were classified correctly. Some conclusions about the generality of the approach are drawn and future research is outlined.

MetaVex: Regulation Drafting Meets the Semantic Web

Currently almost all legislative bodies throughout Europe use general purpose word-processing software for the drafting of legal documents. These regular word processors do not provide specific support for legislative drafters and parliamentarians to facilitate the legislative process. Furthermore, they do not natively support metadata on regulations. This paper describes how the MetaLex regulation-drafting environment (MetaVex) aims to meet such requirements.

Constructing a semantic network for legal content

The Dutch Tax and Customs Administration (DTCA) is one of many organizations that deal with a multitude of electronic legal data, from various sources and in different formats. In this paper, we describe the results of a study aimed at better access to these sources by having a supplier and format independent knowledge store that describes the sources and their interrelations in a semantic network. Furthermore we developed parsers to automatically detect the identity of sources and typed references within the sources to other legal documents. These parsers can be used to fill and update the semantic network as new documents are added.

Automated Handling of Amending Documents and Resulting Consolidations

This paper describes extensions to our native XML legislative editor MetaVex, dealing with specific requests of legislative drafters: The automatic generation of amending documents based on the editing of an existing law or proposal, and the automatic consolidation of (proposed) legislation based on the original and its amending documents. Moreover, we try to automatically detect (potential) clashes of amendments and amendments of amendments.