The need to extract relevant meaning from legal texts is an emerging issue in Legal Information handling, as well as within the NLP community, which shows an increasing interest in testing computational linguistic solutions in the field of law. In this scenario, the importance of semantic resources in the development of methodologies and tools for legal knowledge representation has been clearly assessed. The representation of legal concepts in ontological frameworks helps the understanding, sharing, and re-use of knowledge bases, as it makes explicit assumptions about legal knowledge, mediates storage of legal rules and supports reasoning on them. The aim of this article is to set out methodological routes for constructing legal ontologies in applications that, due to the tasks they intend to achieve, should maintain a clear reference to the source texts. Considering the complexity of the legal domain, methodologies based on ontology learning techniques seem to be the most promising way to fill the gap between dogmatic conceptual models and lexical patterns extracted from texts by combining lexical information and formal semantics, by codifying relations between concepts, their linguistic realisations and the contexts that contain them.
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