A comprehensive review on resolving ambiguities in natural language processing

Abstract

Natural language processing is a known technology behind the development of some widely known AI assistants such as: SIRI, Natasha, and Watson. However, NLP is a diverse technology used for numerous purposes. NLP based tools are widely used for disambiguation in requirement engineering which will be the primary focus of this paper. A requirement document is a medium for the user to deliver one's expectations from the software. Hence, an ambiguous requirement document may eventually lead to misconceptions in a software. Various tools are available for disambiguation in RE based on different techniques. In this paper, we analyzed different disambiguation tools in order to compare and evaluate them. In our survey, we noticed that even though some disambiguation tools reflect promising results and can supposedly be relied upon, they fail to completely eliminate the ambiguities. In order to avoid ambiguities, the requirement document has to be written using formal language, which is not preferred by users due to its lack of lucidity and readability. Nevertheless, some of the tools we mentioned in this paper are still under development and in future might become capable of eliminating ambiguities. In this paper, we attempt to analyze some existing research work and present an elaborative review of various disambiguation tools.