Incremental compilation of knowledge documents for markup-based closed-world authoring

Abstract

Text-based authoring using knowledge markups is an increasingly popular editing paradigm in manual knowledge acquisition. Closed world authoring environments support the user to form a coherent knowledge base by checking the referenced objects against a set of declared domain objects. In this scenario, the task of efficient translation (compilation) of the text sources is non-trivial. Additionally, in realworld applications frequent small changes are performed on the source documents and instant feedback to the author is crucial. Therefore, a scalable compilation into the target knowledge representations is necessary. In this paper, we introduce a general algorithm for the incremental compilation of knowledge documents, that analyzes the current document modifications and performs minimal updates on the knowledge base. We provide a formal proof of the correctness of the algorithm and show the effectiveness of the approach in several case studies, using various kinds of knowledge representations and markups.