Английский лексический образец

The major goal in ITC-irst's participation at SENSEVAL-2 was to test the role of domain in- formation in word sense disambiguation. The underlying working hypothesis is that domain labels, such …...

The task of word sense disambiguation is to assign a sense label to a word in a passage. We report our algorithms and experiments for the two tasks that we …...

In SENSEVAL-3, CL Research participated in four tasks: English all-words, English lexical sample, disambiguation of WordNet glosses, and automatic labeling of semantic roles. This participation was performed within the development …...

Two systems from the University of Minnesota, Duluth participated in various SENSEVAL-3 lexi- cal sample tasks. The supervised learning system is based on lexical features and bagged decision trees. It …...

The CIAOSENSO WSD system is based on Con- ceptual Density, WordNet Domains and frequences of WordNet senses. This paper describes the upv- unige-CIAOSENSO WSD system, we participated in the english …...

Data sparsity is one of the main factors that make word sense disambiguation (WSD) difficult. To overcome this problem we need to find effective ways to use resources other than …...