Knowledge Management in mArachna

Machine-readable semantic annotation of scientific knowledge is becoming increasingly important to manage and access the knowledge contained in an increasing number of scientific publications. At the same time, automated extraction of knowledge from natural language texts is a major technical challenge remaining largely unsolved. Scientific texts in general and mathematical texts in particular, are characterized by the use of complex language constructs with the intent to transfer knowledge. To a large extent, mathematical texts possess a strict internal structuring and can be separated into text elements such as definitions, theorems etc. These text elements are principal carriers of mathematical information. In addition, these elements show a characteristic linguistic structuring well suited for natural language processing techniques. In this paper we present mArachna, a system for extracting mathematical relations from texts and integrating them into a knowledge base. In response to user queries, parts of the knowledge base are visualized using OWL. In particular, mArachna aims to provide an overview of single fields of mathematics, as well as showing intra-field relations between mathematical objects and concepts