HIT-CIR: An Unsupervised WSD System Based on Domain Most Frequent Sense Estimation
Yuhang Guo, Wanxiang Che, Wei Ping He, Ting Liu, Sheng Li · 2010
This paper presents an unsupervised system for all-word domain specific word sense disambiguation task. This system tags target word with the most frequent sense which is estimated using a thesaurus and the word distribution information in the domain. The thesaurus is automatically constructed from bilingual parallel corpus using paraphrase technique. The recall of this system is 43.5 % on SemEval-2 task 17 English data set. 1