Roberto Bartolini

Automatic Classification and Analysis of Provisions in Italian Legal Texts: A Case Study

In this paper we address the problem of automatically enriching legal texts with semantic annotation, an essential pre–requisite to effective indexing and retrieval of legal documents. This is done through illustration of SALEM (Semantic Annotation for LEgal Management), a computational system developed for automated semantic annotation of (Italian) law texts. SALEM is an incremental system using Natural Language Processing techniques to perform two tasks: i) classify law paragraphs according to their regulatory content, and ii) extract relevant text fragments corresponding to specific semantic roles that are relevant for the different types of regulatory content. The paper sketches the overall architecture of SALEM and reports results of a preliminary case study on a sample of Italian law texts.

Grammar and lexicon in the robust parsing of Italian towards a non-naïve interplay

In the paper we report a qualitative evaluation of the performance of a dependency analyser of Italian that runs in both a non-lexicalised and a lexicalised mode. Results shed light on the contribution of types of lexical information to parsing.

A Standard Lexical-Terminological Resource for the Bio Domain

The present paper describes a large-scale lexical resource for the biology domain designed both for human and for machine use. This lexicon aims at semantic interoperability and extendability, through the adoption of ISO-LMF standard for lexical representation and through a granular and distributed encoding of relevant information. The first part of this contribution focuses on three aspects of the model that are of particular interest to the biology community: the treatment of term variants, the representation on bio events and the alignment with a domain ontology. The second part of the paper describes the physical implementation of the model: a relational database equipped with a set of automatic uploading procedures. Peculiarity of the BioLexicon is that it combines features of both terminologies and lexicons. A set verbs relevant for the domain is also represented with full details on their syntactic and semantic argument structure.