Testing the Adequacy of Automated Explanations of EL Subsumptions

Ontology verbalization techniques have been introduced to automatically translate description logic (DL) axioms and derivations to natural-language texts. This way, non-expert users can be offered explanations for subsumptions derived by systems using ontologies for knowledge-representation. We address the question of the readability and understandability of explanations generated from longer chains of inference steps, as they occur with non-trivial ontologies. An experimental design is presented to assess readers’ understanding, the readability and the quality of the generated texts. The experiment tests verbalizations of derivations of different lengths, and assesses the effect of a strategy proposed to shorten explanations while retaining an adequate level of informativeness.