T.C.: Using answer set programming and lambda calculus to characterize natural language sentences with normatives and exceptions

One way to solve the knowledge acquisition bottle-neck is to have ways to translate natural language sen-tences and discourses to a formal knowledge represen-tation language, especially ones that are appropriate to express domain knowledge in sciences, such as Biol-ogy. While there have been several proposals, includ-ing by Montague (1970), to give model theoretic se-mantics for natural language and to translate natural language sentences and discourses to classical logic, none of these approaches use knowledge representation languages that can express domain knowledge involv-ing normative statements and exceptions. In this pa-per we take a first step to illustrate how one can au-tomatically translate natural language sentences about normative statements and exceptions to representations in the knowledge representation language Answer Set Programming (ASP). To do this, we use λ-calculus rep-resentation of words and their composition as dictated by a CCG grammar