CIDOC-CRM is a new standard for encoding a wide range of information for Cultural Heritage (CH). At present, existing CH collections are stored using all sorts of formats, sometimes proprietary, often defined roughly, which \ud makes it difficult to share or access heterogeneous information among the CH community. There is a need for a tool to map diverse formats into CIDOC-CRM, assisted by another tool using intelligent language technology to help the mapping whenever fields are underspecified or loosely described, both tools being complementary. In some cases, it may even be better to build fragments of a CIDOC database directly from informal descriptions in natural \ud language only, as the CH community may be reluctant to switch to new formats of data entry. Therefore, this paper focus primarily on the mapping of CH data described in natural language into CIDOC-CRM triples, the building blocks of the full CIDOC-CRM ontology. The methods exploits the propositional nature of CIDOC-CRM triples. Using WordNet as a lexical database and the WEB as corpus, we first extract triples from examples provided in the CIDOC-CRM literature, and then from text describing the medieval city of Wolfenbüttel. We show the strong points of the system and suggest where and how it could be improved. Although the triples extracted automatically from texts do not provide a full picture of the CIDOC-CRM structure buried in the textual description, our results indicate that it provides a sound initial working basis for the mapping/translation process, saving time on what would otherwise have to be done by hand
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