Specifying and Verbalising Answer Set Programs in Controlled Natural Language
This work addresses the challenge of improving readability and usability of answer set programs for users in computational logic, though it appears incremental as it builds on existing controlled natural language processing methods.
The authors tackled the problem of specifying and verbalizing answer set programs by developing a bi-directional grammar that translates controlled natural language into executable programs and back, ensuring semantic equivalence without modifications.
We show how a bi-directional grammar can be used to specify and verbalise answer set programs in controlled natural language. We start from a program specification in controlled natural language and translate this specification automatically into an executable answer set program. The resulting answer set program can be modified following certain naming conventions and the revised version of the program can then be verbalised in the same subset of natural language that was used as specification language. The bi-directional grammar is parametrised for processing and generation, deals with referring expressions, and exploits symmetries in the data structure of the grammar rules whenever these grammar rules need to be duplicated. We demonstrate that verbalisation requires sentence planning in order to aggregate similar structures with the aim to improve the readability of the generated specification. Without modifications, the generated specification is always semantically equivalent to the original one; our bi-directional grammar is the first one that allows for semantic round-tripping in the context of controlled natural language processing. This paper is under consideration for acceptance in TPLP.