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In the last years important initiatives, like the development of the European Library and Europeana, aim to increase the availability of cultural content from various types of providers and institutions. The accessibility to these resources requires the development of environments which allow both to manage multilingual complexity and to preserve the semantic interoperability. The creation of Natural Language Processing (NLP) applications is finalized to the achievement of Cross-Lingual Information Retrieval (CLIR). This paper presents an ongoing research on language processing based on the Lexicon-Grammar (LG) approach with the goal of improving knowledge management in the Cultural Heritage repositories. The proposed framework aims to guarantee interoperability between multilingual systems in order to overcome crucial issues like crosslanguage and cross-collection retrieval. Indeed, the LG methodology tries to overcome the shortcomings of statistical approaches as in Google Translate or Bing by Microsoft concerning Multi-Word Unit (MWU) processing in queries, where the lack of linguistic context represents a serious obstacle to disambiguation. In particular, translations concerning specific domains, as it is has been widely recognized, is unambiguous since the meanings of terms are mono-referential and the type of relation that links a given term to its equivalent in a foreign language is biunivocal, i.e. a one-to-one coupling which causes this relation to be exclusive and reversible. Ontologies are used in CLIR and are considered by several scholars a promising research area to improve the effectiveness of Information Extraction (IE) techniques particularly for technical-domain queries. Therefore, we present a methodological framework which allows to map both the data and the metadata among the language-specific ontologies. This experiment has been set up for the English/Italian language pair and it can be easily extended to other language pairs. The feasibility of cross-language information extraction and semantic search will be tested by implementing an early prototype system.

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