This paper proposes a two-step approach to identifying ambiguities in natural language (NL) requirements specifications (RSs

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Abstract. Government regulations are increasingly affecting the security, privacy and governance of information systems in the United States, Europe and elsewhere. Consequently, companies and software developers are required to ensure that their software systems comply with relevant regulations, either through design or re-engineering. We previously proposed a methodology for extracting stakeholder requirements, called rights and obligations, from regulations. In this paper, we examine the challenges to developing tool support for this methodology using the Cerno framework for textual semantic annotation. We present the results from two empirical evaluations of a tool called "Gaius T" that is implemented using the Cerno framework and that extracts a conceptual model from regulatory texts. The evaluation, carried out on the U.S. HIPAA Privacy Rule and the Italian accessibility law, measures the quality of the produced models and the tool's effectiveness in reducing the human effort to derive requirements from regulations.

Abstract. The Web is the greatest information source in human history. Unfortunately, mining knowledge out of this source is a laborious and errorprone task. Many researchers believe that a solution to the problem can be founded on semantic annotations that need to be inserted in web-based documents and guide information extraction and knowledge mining. In this paper, we further elaborate a tool-supported process for semantic annotation of documents based on techniques and technologies traditionally used in software analysis and reverse engineering for large-scale legacy code bases. The outcomes of the paper include an experimental evaluation framework and empirical results based on two case studies adopted from the Tourism sector. The conclusions suggest that our approach can facilitate the semi-automatic annotation of large document bases.