Word-Sense Disambiguation: an Aid to true translation between Natural Languages

Abstract

Word-sense disambiguation (WSD) is a long-standing research area of Natural Language Processing (NLP) applications. This is the core of many NLP Systems and has become an important and very successful technique for the last 03 decades. By definition, WSD is a technic for seeking the right sense (meaning) of a word appearing in a sentence with a certain context. A single word may be Polysemy (i.e. multiple meanings) and even multiple words may represent Synonymy (i.e. similar meaning) by its nature. The “Corpus/lexicon” is a special kind of dictionary or knowledge base which is very helpful in Natural Language Translations.  It is also called the heart of NLP. WordNet is the most important example of it. A WordNet is a lexical English database, available online and designed to use with the support of a control program. In this paper, a framework for WSD and its approaches has been provided through which the Natural Language Translation can be done. Further, the detailed knowledge of the artifacts of WSD and also the brief of various applications of WSD has been discussed.