Template-Based Unsupervised Word Sense Disambiguation Method
Daquan Tang · Computer Engineering and Science · 2009
Word sense disambiguation is a key problem in NLP. This essay proposes a template-based unsupervised word sense disambiguation method to improve the precision. We describe polysemous word by the synonymies of different sense and construct the context template considering position,context distance and frequency of the co-occurrence term. Experiment shows this method could improve the performance of word sense disambiguation.