Critical annotations are important knowledge sources when researching one’s oeuvre.
They describe literary, historical, cultural, linguistic and other kinds of information
written in natural languages. Acquiring knowledge from these notes is a complex task
due to the limited natural language understanding capability of computerized tools.
The aim of the research was to extract knowledge from existing annotations, and to
develop new authoring methods to facilitate the knowledge acquisition. After structural
and semantic analysis of critical annotations, authors developed a software tool that
transforms existing annotations into a structured form that encodes referral and factual
knowledge. Authors also propose a new method for authoring annotations based on controlled
natural languages. This method ensures that annotations are semantically processable
by computer programs and the authoring process remains simple for non-technical users.
