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In this paper we introduce an approach to exploit knowledge represented in an ontology in answers to queries to an information base. We assume that the ontology is embedded in a knowledge base covering the domain of the information base. The ontology is first of all to influence ranking of objects in answers to queries as measured by similarity to the query. We consider a generative framework where an ontology in combination with a concept language defines a set of well-formed concepts. Wellformed concepts is assumed to be the basis for an indexing of the information base in the sense that these concepts appear as descriptors attached to objects in the base. Concepts are thus applied to obtain a means for descriptions that generalizes simple word-based information base indexing. In effect query evaluation is generalized to be a matter of comparison at the level of concepts rather than words.

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This paper outlines a system, OntoScape, serving to accomplish complex inference tasks on knowledge bases and bio-models derived from life-science text corpora. The system applies so-called natural logic, a form of logic which is readable for humans. This logic affords ontological representations of complex terms appearing in the text sources. Along with logical propositions, the system applies a semantic graph representation facilitating calculation of bio-pathways. More generally, the system affords means of query answering appealing to general and domain specific inference rules.

Abstract. We describe principles and design of a system for knowledge bases applying a natural logic. Natural logics are forms of logic which appear as stylized fragments of natural language sentences. Accordingly, such knowledge base sentences can be read and understood directly by a domain expert. The system applies a graph form computed from the input natural logic sentences. The graph form generalizes the usual partialorder ontological sub-class structures by accommodation of affirmative sentences comprising recursive phrase structures. In this paper we focus on the logical inference rules for extending the concept graph form enabling deductive querying as well as computation of pathways between the concepts mentioned in the sentences. Keywords. Deductive querying of natural-logic knowledge bases, Path finding in knowledge bases, Logical knowledge bases in bio-informatics and medicine

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