In sum, by modifying the ILP parameters to select various numbers of triples, we can generate solutions of different sizes whilst the 3 ILP models permit producing solutions with relatively small overlap both within and across models.
our content selection method can be used to automatically create a graduated benchmark for natural language generation in which the inputs are of increasing size and exhibit a good level of semantic variability.