The paper reports on methodology and preliminary results ofa case study in automatically extracting ontological knowledgefrom Italian legislative texts in the environmental domain. Weuse a fully-implemented ontology learning system (T2K) thatincludes a battery of tools for Natural Language Processing(NLP), statistical text analysis and machine language learn-ing. Tools are dynamically integrated to provide an incremen-tal representation of the content of vast repositories of unstruc-tured documents. Evaluated results, however preliminary, arevery encouraging, showing the great potential of NLP-poweredincremental systems like T2K for accurate large-scale semi-automatic extraction of legal ontologies.
Acquiring Legal Ontologies from Domain-specific Texts
Dell'Orletta F;Montemagni S;Marchi S;Pirrelli V;Venturi G
2008
Abstract
The paper reports on methodology and preliminary results ofa case study in automatically extracting ontological knowledgefrom Italian legislative texts in the environmental domain. Weuse a fully-implemented ontology learning system (T2K) thatincludes a battery of tools for Natural Language Processing(NLP), statistical text analysis and machine language learn-ing. Tools are dynamically integrated to provide an incremen-tal representation of the content of vast repositories of unstruc-tured documents. Evaluated results, however preliminary, arevery encouraging, showing the great potential of NLP-poweredincremental systems like T2K for accurate large-scale semi-automatic extraction of legal ontologies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
