  Answer Set Programming (ASP) is a popular declarative programming language
for solving hard combinatorial problems. Although ASP has gained widespread
acceptance in academic and industrial contexts, there are certain user groups
who may find it more advantageous to employ a higher-level language that
closely resembles natural language when specifying ASP programs. In this paper,
we propose a novel tool, called CNL2ASP, for translating English sentences
expressed in a controlled natural language (CNL) form into ASP. In particular,
we first provide a definition of the type of sentences allowed by our CNL and
their translation as ASP rules, and then exemplify the usage of the CNL for the
specification of both synthetic and real-world combinatorial problems. Finally,
we report the results of an experimental analysis conducted on the real-world
problems to compare the performance of automatically generated encodings with
the ones written by ASP practitioners, showing that our tool can obtain
satisfactory performance on these benchmarks. Under consideration in Theory and
Practice of Logic Programming (TPLP).

Artificial Intelligence;Computation and Language;Logic in Computer Science