Explaining Conclusions from Diverse Knowledge Sources

  • J. William Murdock
  • Deborah L. McGuinness
  • Paulo Pinheiro da Silva
  • Chris Welty
  • David Ferrucci
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4273)


The ubiquitous non-semantic web includes a vast array of unstructured information such as HTML documents. The semantic web provides more structured knowledge such as hand-built ontologies and semantically aware databases. To leverage the full power of both the semantic and non-semantic portions of the web, software systems need to be able to reason over both kinds of information. Systems that use both structured and unstructured information face a significant challenge when trying to convince a user to believe their results: the sources and the kinds of reasoning that are applied to the sources are radically different in their nature and their reliability. Our work aims at explaining conclusions derived from a combination of structured and unstructured sources. We present our solution that provides an infrastructure capable of encoding justifications for conclusions in a single format. This integration provides an end-to-end description of the knowledge derivation process including access to text or HTML documents, descriptions of the analytic processes used for extraction, as well as descriptions of the ontologies and many kinds of information manipulation processes, including standard deduction. We produce unified traces of extraction and deduction processes in the Proof Markup Language (PML), an OWL-based formalism for encoding provenance for inferred information. We provide a browser for exploring PML and thus enabling a user to understand how some conclusion was reached.


Entity Annotation Unstructured Information Unstructured Information Management Architecture Information Manipulation Generate Knowledge Base 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • J. William Murdock
    • 1
  • Deborah L. McGuinness
    • 2
  • Paulo Pinheiro da Silva
    • 3
  • Chris Welty
    • 1
  • David Ferrucci
    • 1
  1. 1.IBM Watson Research CenterHawthornUSA
  2. 2.Knowledge Systems, Artificial Intelligence LaboratoryStanford UniversityStanfordUSA
  3. 3.Department of Computer ScienceThe University of Texas at El PasoEl PasoUSA

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