Hennie van der Vliet
Also published as: Hennie VanderVliet
2008
Integrating Lexical Units, Synsets and Ontology in the Cornetto Database
Piek Vossen
|
Isa Maks
|
Roxane Segers
|
Hennie VanderVliet
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
Cornetto is a two-year Stevin project (project number STE05039) in which a lexical semantic database is built that combines Wordnet with Framenet-like information for Dutch. The combination of the two lexical resources (the Dutch Wordnet and the Referentie Bestand Nederlands) will result in a much richer relational database that may improve natural language processing (NLP) technologies, such as word sense-disambiguation, and language-generation systems. In addition to merging the Dutch lexicons, the database is also mapped to a formal ontology to provide a more solid semantic backbone. Since the database represents different traditions and perspectives of semantic organization, a key issue in the project is the alignment of concepts across the resources. This paper discusses our methodology to first automatically align the word meanings and secondly to manually revise the most critical cases.
Adjectives in the Dutch Semantic Lexical Database CORNETTO
Isa Maks
|
Piek Vossen
|
Roxane Segers
|
Hennie van der Vliet
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
The goal of this paper is to describe how adjectives are encoded in Cornetto, a semantic lexical database for Dutch. Cornetto combines two existing lexical resources with different semantic organisation, i.e. Dutch Wordnet (DWN) with a synset organisation and Referentie Bestand Nederlands (RBN) with an organisation in Lexical Units. Both resources will be aligned and mapped on the formal ontology SUMO. In this paper, we will first present details of the description of adjectives in each of the the two resources. We will then address the problems that are encountered during alignment to the SUMO ontology which are greatly due to the fact that SUMO has never been tested for its adequacy with respect to adjectives. We contrasted SUMO with an existing semantic classification which resulted in a further refined and extended SUMO geared for the description of adjectives.