Towards Knowledge Acquisition from Information Extraction

Chris Welty and J. William Murdock

Abstract. In our research to use information extraction to help populate the semantic web, we have encountered significant obstacles to interoperability between the technologies. We believe these obstacles to be endemic to the basic paradigms, and not quirks of the specific implementations we have worked with. In particular, we identify five dimensions of interoperability that must be addressed to successfully populate semantic web knowledge bases from information extraction systems that are suitable for reasoning. We call the task of transforming IE data into knowledge-bases knowledge integration, and briefly present a framework called KITE in which we are exploring these dimensions. Finally, we report on the initial results of an experiment in which the knowledge integration process uses the deeper semantics of OWL ontologies to improve the precision of relation extraction from text.

Keywords: Information Extraction, Applications of OWL DL Reasoning.

LNCS 4273, p. 709 ff.

Full article in PDF | BibTeX

lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2006