Newsgroups: comp.ai.jair.announce
Path: cantaloupe.srv.cs.cmu.edu!fs7.ece.cmu.edu!europa.eng.gtefsd.com!howland.reston.ans.net!vixen.cso.uiuc.edu!uwm.edu!lll-winken.llnl.gov!ames!kronos.arc.nasa.gov!jair-ed
From: jair-ed@ptolemy.arc.nasa.gov
Subject: New Article, Wrap-Up: A Trainable Discourse Module...
Message-ID: <1994Dec13.210412.22252@ptolemy-ethernet.arc.nasa.gov>
Originator: jair-ed@polya.arc.nasa.gov
Lines: 54
Sender: usenet@ptolemy-ethernet.arc.nasa.gov (usenet@ptolemy.arc.nasa.gov)
Nntp-Posting-Host: polya.arc.nasa.gov
Organization: NASA/ARC Computational Sciences Division
Date: Tue, 13 Dec 1994 21:04:12 GMT
Approved: jair-ed@ptolemy.arc.nasa.gov

JAIR is pleased to announce publication of the following article:

Soderland, S. and Lehnert. W. (1994)
  "Wrap-Up: a Trainable Discourse Module for Information Extraction", 
   Volume 2, pages 131-158.
   Postscript: volume2/soderland4a.ps (442K)

   Abstract: The vast amounts of on-line text now available have led to
   renewed interest in information extraction (IE) systems that analyze
   unrestricted text, producing a structured representation of selected
   information from the text. This paper presents a novel approach that
   uses machine learning to acquire knowledge for some of the higher
   level IE processing.  Wrap-Up is a trainable IE discourse component
   that makes intersentential inferences and identifies logical relations
   among information extracted from the text.  Previous corpus-based
   approaches were limited to lower level processing such as
   part-of-speech tagging, lexical disambiguation, and dictionary
   construction.  Wrap-Up is fully trainable, and not only automatically
   decides what classifiers are needed, but even derives the feature set
   for each classifier automatically. Performance equals that of a
   partially trainable discourse module requiring manual customization
   for each domain.


The PostScript file is available via:
   
 -- comp.ai.jair.papers

 -- World Wide Web: The URL for our World Wide Web server is
       http://www.cs.washington.edu/research/jair/home.html

 -- Anonymous FTP from either of the two sites below:
      CMU:   p.gp.cs.cmu.edu        directory: /usr/jair/pub/volume2
      Genoa: ftp.mrg.dist.unige.it  directory:  pub/jair/pub/volume2

 -- automated email. Send mail to jair@cs.cmu.edu or jair@ftp.mrg.dist.unige.it
    with the subject AUTORESPOND, and the body GET VOLUME2/SODERLAND94A.PS
    (either upper or lowercase is fine). 
    Note: Your mailer might find this file too large to handle.

 -- JAIR Gopher server: At p.gp.cs.cmu.edu, port 70. 

For more information about JAIR, check out our WWW or FTP sites, or
send electronic mail to jair@cs.cmu.edu with the subject AUTORESPOND
and the message body HELP, or contact jair-ed@ptolemy.arc.nasa.gov.


