Enriching Knowledge Sources for Natural Language Understanding

This paper presents the complete and consistent ontological annotation of the nominal part of WordNet. The annotation has been carried out using the semantic features defined in the EuroWordNet Top Concept Ontology and made available to the NLP community. Up to now only an initial core set of 1,024 synsets, the so-called Base Concepts, was ontologized in such a way. The work has been achieved by following a methodology based on an iterative and incremental expansion of the initial labeling through the hierarchy while setting inheritance blockage points. Since this labeling has been set on the EuroWordNet’s Interlingual Index (ILI), it can be also used to populate any other wordnet linked to it through a simple porting process. This feature-annotated WordNet is intended to be useful for a large number of semantic NLP tasks and for testing for the first time componential analysis on real environments. Moreover, the quantitative analysis of the work shows that more than 40% of the nominal part of WordNet is involved in structure errors or inadequacies The methodology followed for annotating the ILI with the TCO is based on the common assumption that hyponymy corresponds to feature set inclusion (Cruse, 2002) and in the observation that, since wordnets are taken to be crucially structured by hyponymy it is possible to create a rich consistent semantic lexicon inheriting basic features through the hyponymy relations [10]. This methodology confronts two main drawbacks, the hyponymy hierarchy of wordnet is not consistent (Guarino 1998) and there may be multiple inherintace. In the EuroWordNet project TCO features were asigned to this Basic Concepts. These are genereal concepts that can represent other concepts that are behind them in the hyponymy hierachy, but they do not cover all wordnet. Thus, firs of all, we annotated the gaps of the hierarchy asigning TCO features to the Semantic Files of