Requirements documentsare always written in natural language. At the point when a sentence can be understood diversely among various readersambiguity is happened [1]. In this paper, we illustrate an automated tool for detectingand resolvingambiguities thatcause a high risk of misunderstanding byseveralreaders and lead to confusion, waste of both effort and time and rework. Sentences in a natural language requirements specification document thathaveambiguity are initialdetected automatically from the text andambiguity type is determined. Sentences thatincludeambiguity are thenresolved automatically also by resolving algorithm based on a set of rules that we collected from training data. We implemented a tool for Detecting and Resolving Ambiguity (DARA), in order to clarifyand estimate our approach. The tool focuses on Lexical, Referential, Coordination, Scope and Vague ambiguity.We determine on the results of a collection of requirement specification documents to evaluatethe performance and utility of the approach.