The available approaches for automatically generating class models from natural language (NL) software requirements specifications (SRS) exhibit less accuracy due to informal nature of NL such as English. In the automated class model generation, a higher accuracy can be achieved by overcoming the inherent syntactic ambiguities and semantic inconsistencies in English. In this paper, we propose a SBVR based approach to generate an unambiguous representation of NL software requirements. The presented approach works as the user inputs the English specification of software requirements and the approach processes input English to extract SBVR vocabulary and generate a SBVR representation in the form of SBVR rules. Then, SBVR rules are semantically analyzed to extract OO information and finally OO information is mapped to a class model. The presented approach is also presented in a prototype tool NL2SBVRviaSBVR that is an Eclipse plugin and a proof of concept. A case study has also been solved to show that the use of SBVR in automated generation of class models from NL software requirements improves accuracy and consistency.