DeepEL: Deep Learning and Formal Description Logic Reasoning

Light-weight description logics like EL have been successfully used to represent the terminological knowledge of many application domains. Yet, identifying the characteristics of instances often requires sub-symbolic approaches. We introduce a neuro-symbolic extension of EL which allows for (neural) perception and classification of properties, accompanied by formal (symbolic) reasoning based on these perceptions. Through a prototypical implementation, based on a reduction to logic programming, we show that inferences and learning are effectively achievable.