We propose a supervised word sense disambiguation (WSD) method using tree-structured conditional random fields (TCRFs). By applying TCRFs to a sentence described as a dependency t...
In this paper we investigate whether the task of disambiguating pseudowords (artificial ambiguous words) is comparable to the disambiguation of real ambiguous words. Since the two...
When a word sense disambiguation (WSD) system is trained on one domain but applied to a different domain, a drop in accuracy is frequently observed. This highlights the importance...
We propose a supervised word sense disambiguation (WSD) system that uses features obtained from clustering results of word instances. Our approach is novel in that we employ semi-s...
Choosing the right parameters for a word sense disambiguation task is critical to the success of the experiments. We explore this idea for prepositions, an often overlooked word c...