Emile de Maat

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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(More)
Understanding electronic legislation requires a comprehension of its life-cycle and the events and corresponding transformations that make up this lifecycle. A metadata description attached to the legislative resource represents a time point in this lifecycle. In this paper we advocate an event-based model of version management for legislation. We are(More)
In a lot of existing legal knowledge based applications, the underlying legal model does not retain isomorphism with the original legal text. Parts of the text have not been modelled, and other parts have been simplified to single if-then-else clauses. This makes these models difficult to validate, maintain and re-use. In this article we propose to make an(More)
This paper presents results of an experiment in which we used machine learning (ML) techniques to classify sentences in Dutch legislation. These results are compared to the results of a pattern-based classifier. Overall, the ML classifier performs as accurate (>90%) as the pattern based one, but seems to generalize worse to new laws. Given these results,(More)
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(More)
A main issue in the field of artificial intelligence and law is the translation of source of law that are written in natural language into formal models of law. This article describes a step in that transformation: the creation of models for individual sentences in a source of law. The approach uses a natural language parse to analyse the sentence, and then(More)