abstract
Active learning is a method where a learner attempts to learn some kind of knowledge by posing questions to a teacher. In computational learning theory, classically, the questions made by the learner are called membership queries and are answered with ‘yes’ or ‘no’ (or equivalently, with ‘true’ or ‘false’). Here we consider that the teacher is a language model and we study the case where the knowledge is expressed as an ontology. To evaluate the approach, we present results showing the performance of GPT and other language models when answering whether concept inclusions on existing EL ontologies are ‘true’ or ‘false’.
outcomes
