Contextual Knowledge Representation for Requirements Documents in Natural Language

Beum-Seuk Lee and Barrett R. Bryant

In software requirements engineering there have been very few attempts to automate the translation from a requirements document written in a natural language (NL) to one of the formal specification languages. One of the major reasons for this challenge comes from the ambiguity of the NL requirements documentation because NL depends heavily on context. To make a smooth transition from NL requirements to one of the formal specification languages we need a precise yet expressive knowledge representation that captures not only syntactic but also contextual information of the requirements. We propose the Contextual Natural Language Processing to overcome the ambiguity in NL using this contextual knowledge representation and Two-Level Grammar (TLG) to construct a bridge between a NL requirements specification and a formal specification to promote rapid prototyping and reusability of requirements documents.


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