期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2014
卷号：3
期号：12
页码：18230
DOI：10.15680/IJIRSET.2014.0312066
出版社：S&S Publications
摘要：A key ingredient of today’s NLP scenario is annotation and this paper discusses challenges involved inone of the toughest annotation tasks which is sense marking. A large amount of data needs to be sense markedaccurately by human annotators in order to train the machine to understand the spoken languages. The sense markedcorpus for various languages facilitate the task of Word Sense Disambiguation (WSD) which is required for translation.For accurately sense marking voluminous data, a standard and definitive lexicon is required. In the work reported here,the corpus is taken from the newspaper domain and tourism domain. The Princeton WordNet (Version 2.1) is used asthe sense repertoire for English text while the Hindi and Nepali WordNets have been used for Hindi and Nepali textsrespectively. The corpus was independently tagged by different annotators and it was found that the agreement level onword sense disambiguation was about 85% across the three languages, i.e., English, Hindi and Nepali. Different sensesof a particular word in WordNet are quite specific, yet there have been cases when the senses provided had limitationsand posed challenges to the human sense markers.
关键词：Sense-marking; Synset; WordNet; Word sense disambiguation; Expansion approach
