Answer Set Programming via Controlled Natural Language Processing

Controlled natural languages are subsets of natural languages that can be used to describe a problem in a very precise way, furthermore they can often be translated automatically into a formal notation. We investigate in this paper how a controlled natural language can be used as a specification language for Answer Set Programming (ASP). ASP is a declarative approach to problem solving and has its roots in knowledge representation, logic programming, and constraint satisfaction. Solutions of ASP programs are stable models (= answer sets) that build the starting point for question answering. As a proof of concept, we translate a problem specification written in controlled natural language into an ASP program and compute a stable model that contains the answers to a number of questions.

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