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Open Information Extraction from the Web Michele Banko, Michael J Cafarella, Stephen Soderland, Matt Broadhead and Oren Etzioni
 

Summary: Open Information Extraction from the Web
Michele Banko, Michael J Cafarella, Stephen Soderland, Matt Broadhead and Oren Etzioni
Turing Center
Department of Computer Science and Engineering
University of Washington
Box 352350
Seattle, WA 98195, USA
{banko,mjc,soderlan,hastur,etzioni}@cs.washington.edu
Abstract
Traditionally, Information Extraction (IE) has fo-
cused on satisfying precise, narrow, pre-specified
requests from small homogeneous corpora (e.g.,
extract the location and time of seminars from a
set of announcements). Shifting to a new domain
requires the user to name the target relations and
to manually create new extraction rules or hand-tag
new training examples. This manual labor scales
linearly with the number of target relations.
This paper introduces Open IE (OIE), a new ex-
traction paradigm where the system makes a single

  

Source: Anderson, Richard - Department of Computer Science and Engineering, University of Washington at Seattle
Cafarella, Michael J. - Department of Electrical Engineering and Computer Science, University of Michigan
Etzioni, Oren - Department of Computer Science and Engineering, University of Washington at Seattle

 

Collections: Computer Technologies and Information Sciences