This paper presents a new method for Word Sense Disambiguation based on the WordNet Domains lexical resource [4]. The underlaying working hypothesis is that domain labels, such as ARCHITECTURE, SPORT and MEDICINE provide a natural way to establish semantic relations between word senses, that can be used during the disambiguation process. This resource has already been used on Word Sense Disambi...

The essential characteristic of a signed language corpus is that it has been annotated, and not, contrary to the practice of many signed language researchers, that it has been transcribed. Annotations are necessary for corpus-based investigations of signed or spoken languages. Multi-media annotation software can now be used to transform a recording into a machine-readable text without it first ...

OntoLearn is a system for automatic acquisition of specialized ontologies from domain corpora, based on a syntactic pattern matching technique for word sense disambiguation, called structural semantic interconnection (SSI). We use SSI to extract from corpora complex domain concepts and create a specialized version of WordNet. In order to facilitate the task of domain specialists who inspects an...

We review in detail here a polished version of the systems with which we participated in the Senseval2 competition English tasks (all words and lexical sample). It is based on a combination of selectional preference measured over a large corpus and hierarchical information taken from WordNet, as well as some additional heuristics. We use that information to expand sense glosses of the senses in...