Knowledge Systems Laboratory
Abstract: Encoding Extraction as Inferences
The analysis of natural-language text involves many different kinds of
processes that might be described in multiple ways. One way to describe
these processes is in terms of the semantics of their requirements and results.
Such a description makes it possible to view these processes as analogous
to inference rules in a theorem-proving system. This analogy is useful for
metacognition because there is existing theory and infrastructure for
manipulating inference rules. We describe a taxonomy of text extraction tasks
that we have represented as inference rules. We also describe a working
system that encodes the behavior of text analysis components as a graph of
inferences. This representation is currently used to present browsable
explanations of text extraction to a user; in future work, we expect to
perform additional automated reasoning over this encoding of text analysis
J. William Murdock, Paulo Pinheiro da Silva,
David Ferrucci, Christopher Welty and Deborah L. McGuinness.
Encoding Extraction as Inferences. In Proceedings of
Metacognition on Computation, AAAI Press,
stanford University, USA, 2005. Also, KSL Tech Report KSL-04-06.
version is available.
Selected Papers of Deborah L. McGuinness.
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