Word Sense Disambiguation and Semantics techniques

Abstract

Of the many kinds of ambiguity in language is word sense. This problem had received the most attention in computational linguistics, and the reasons for this are clear: their resolution is seemingly essential for any practical application, and they seem to require a wide variety of methods and knowledge-sources with no pattern apparent in what any particular instance requires.Since the beginning of NLP field and the researchers trying to bypass the bottleneck of word sense disambiguation (WSD). The lack of high-performing methods for sense disambiguation may be considered the major obstacle that prevented an extensive use of natural language processing techniques in many areas of information technology, such as information classification and retrieval, query processing, advanced Web search, document warehousing, etc.This obstacle inspired many researchers to come up with new methods, approaches, and to exploit whatever knowledge resources exist to develop a solution. Previously most of the techniques used were based on a huge amount of knowledge sources, which suffers from the problems of incomplete, inadequate, and expensive resources.After that a trained techniques and the statistical approaches dominant over the field for a while were at the beginning good results obtained with limited and small domains. But with the expanding of the domains, the luck of good trained knowledge sources besides the neglecting of the semantic roles did not lay good results at the end.Now a day’s the research had been directed towards a hybrid approach that depends on the available and more reliable knowledge sources besides the semantic techniques, and training methods which consider the role of the words in its context.In this research we will take a case study of WSD. Then we will display the semantic techniques used in it and display the effect of implementing consistence concept evaluation method to produce more reliable results based on semantic similarity, besides that we will show how more conceptualization of the semantic relations can be implemented through semantic information.