  Grammatical inference is a machine learning area, whose fundamentals are
built around learning sets. At present, real-life data and examples from
manually crafted grammars are used to test their learning performance. This
paper aims to present a method of generating artificial context-free grammars
with their optimal learning sets, which could be successfully applied as a
benchmarking tool for empirical grammar inference methods.
