Semantic parsing using content and context: A case study from requirements elicitation

We present a model for the automatic semantic analysis of requirements elicitation documents. Our target semantic representation employs live sequence charts, a multi-modal visual language for scenariobased programming, which can be directly translated into executable code. The architecture we propose integrates sentencelevel and discourse-level processing in a generative probabilistic framework for the analysis and disambiguation of individual sentences in context. We show empirically that the discourse-based model consistently outperforms the sentence-based model when constructing a system that reflects all the static (entities, properties) and dynamic (behavioral scenarios) requirements in the document.