Appel: Natural Language and Knowledge Representation, Special Track at FLAIRS 2006

Tue Aug 30 07:54:20 UTC 2005

Date: Thu, 25 Aug 2005 12:08:44 +0100
From: "Jana Sukkarieh" <jana.sukkarieh at clg.ox.ac.uk>
Message-ID: <001301c5a965$5bc81f00$e25701a3 at cpgljana>
X-url: http://users.ox.ac.uk/~lady0641/Flairs06_NL_KR
X-url: http://www.indiana.edu/~flairs06
X-url: http://www.cogsci.ed.ac.uk/~fracas/
X-url: http://www.pascal-network.org/Challenges/RTE
X-url: http://users.ox.ac.uk/~lady0641/Flairs06_NL_KR/submission_details.html

 [Apologies for x-postings]

NATURAL LANGUAGE AND KNOWLEDGE REPRESENTATION (NL-KR)

Special Track at FLAIRS 2006

ANNOUNCEMENT AND CALL FOR PAPERS

Holiday Inn Melbourne Oceanfront,  Melbourne Beach, FLORIDA, USA

MAIN CONFERENCE: 11-12-13 MAY 2006

Special track web page: http://users.ox.ac.uk/~lady0641/Flairs06_NL_KR
Main conference web page: http://www.indiana.edu/~flairs06

PURPOSE OF THE NL-KR TRACK

We believe the Natural Language Processing (NLP) and the Knowledge
Representation (KR) communities have common goals. They are both
concerned with representing knowledge and with reasoning, since the
best test for the semantic capability of an NLP system is performing
reasoning tasks. Having these two essential common grounds, the two
communities ought to have been collaborating, to provide a well-suited
representation language that covers these grounds. However, the two
communities also have difficult-to-meet concerns. Mainly, the semantic
representation (SR) should be expressive enough and should take the
information in context into account, while the KR should be equipped
with a fast reasoning process.

The main objection against an SR or a KR is that they need experts to
be understood. Non-experts communicate (usually) via a natural
language (NL), and more or less they understand each other while
performing a lot of reasoning. An essential practical value of
representations is their attempt to be transparent.  This will
particularly be useful when/if the system provides a justification for
a user or a knowledge engineer on its line of reasoning using the
underlying KR (i.e. without generating back to NL).

We all seem to believe that, compared to Natural Language, the
existing Knowledge Representation and reasoning systems are
poor. Nevertheless, for a long time, the KR community dismissed the
idea that NL can be a KR. That's because NL can be very ambiguous and
there are syntactic and semantic processing complexities associated
with it. However, researchers in both communities have started looking
at this issue again. Possibly, it has to do with the NLP community
making some progress in terms of processing and handling ambiguity,
the KR community realising that a lot of knowledge is already 'coded'
in NL and that one should reconsider the way they handle expressivity
and ambiguity.

This track is an attempt to provide a forum for discussion on this
front and to bridge a gap between NLP and KR.  A KR in this track has
a well-defined syntax, semantics and a proof theory. It should be
clear what authors mean by NL-like, based on NL or benefiting from NL
(if they are using one). It does not have to be a novel
representation.

NL-KR TRACK TOPICS

 For this track, we will invite submissions including, but not limited
 to:

  a. A novel NL-like KR or building on an existing one
  b. Reasoning systems that benefit from properties of NL to reason
     with NL
  c. Semantic representation used as a KR : compromise between
     expressivity and efficiency?
  d. More Expressive KR for NL understanding (Any compromise?)
  e. Any work exploring how existing representations fall short of
     addressing some problems involved in modelling, manipulating or
     reasoning (whether reasoning as used to get an interpretation for
     a certain utterance, exchange of utterances or what utterances
     follow from other utterances) with NL documents
  f. Representations that show how classical logics are not as
     efficient, transparent, expressive or where a one-step
     application of an inference rule require more (complex) steps in
     a classical environment and vice-versa; i.e.  how classical
     logics are more powerful, etc
  g. Building a reasoning test collection for natural language
     understanding systems: any kind of reasoning (deductive,
     abductive, etc); for a deductive test suite see for
     e.g. deliverable 16 of the FraCas project
     (http://www.cogsci.ed.ac.uk/~fracas/). Also, look at textual
     entailment challenges 1 and 2
     <http://www.pascal-network.org/Challenges/RTE>
  h. Comparative results (on a common test suite or a common task) of
     different representations or systems that reason with NL (again
     any kind of reasoning). The comparison could be either for
     efficiency, transparency or expressivity
  i. Knowledge acquisition systems or techniques that benefit from
     properties of NL to acquire knowledge already 'coded' in NL
  j. Automated Reasoning, Theorem Proving and KR communities views on all
     this

NL_KR TRACK PROGRAM COMMITTEE

James ALLEN, University of Rochester, USA
Patrick BLACKBURN, Institut National de Recherche en Informatique, France
Johan BOS, University of Edinburgh, UK
Richard CROUCH, Palo Alto Research Centre, USA
Maarten DE RIJKE, University of Amsterdam, The Netherlands
Anette FRANK, DFKI, Germany
Fernando GOMEZ, University of Central Florida, USA
Sanda HARABAGIU, University of Texas at Dallas, USA
John HARRISON, Intel, USA
Jerry HOBBS, Information Sciences Institute, USA
Chung Hee HWANG, Raytheon Co., USA
Michael KOHLHASE, International University Bremen, Germany
Shalom LAPPIN, King's College, UK
Carsten LUTZ, Dresden University of Technology, Germany
Dan MOLDOVAN,  University of Texas at Dallas, USA
Jeff PELLETIER, Simon Fraser University, Canada
Stephen PULMAN, University of Oxford, UK
Lenhart SCHUBERT, University of Rochester, USA
John SOWA, VivoMind Intelligence, Inc., USA
Jana SUKKARIEH, University of Oxford, UK (Chair)
Geoff SUTCLIFFE, Miami University, USA
Timothy WILLIAMSON, University of Oxford, UK

NL_KR TRACK INVITED SPEAKER

John SOWA, VivoMind Intelligence, Inc., US

FLAIRS 2006 INVITED SPEAKERS

Alan BUNDY, University of Edinburg, Scotland
Bob MORRIS,  Nasa Ames Research Center, USA
Mehran SAHAMI, Standford University and Google, USA
Barry SMYTH, University College Dublin, Ireland

NL-KR TRACK PROPOSED BY

Jana Sukkarieh, University of Oxford, UK
email: J.Sukkarieh.94 at cantab.net

WEB and TECH SUPPORT

Simon Dobnik, University of Oxford, UK
email: Simon.Dobnik at clg.ox.ac.uk

SUBMISSION DETAILS

Submissions must arrive no later than 21 November 2005. Only
electronic submissions will be considered. Details about submission
can be found on :
http://users.ox.ac.uk/~lady0641/Flairs06_NL_KR/submission_details.html
Selected papers will be considered for publication in a special
journal issue of "The journal of Logic and Computation".

PROCEEDINGS

Printed Proceedings will be published only on demand. Proceedings on CD
will be provided to all.

IMPORTANT DATES

* Submission of papers:  21 November,  2005
* Notification of acceptance: 20 January, 2006
* Final version of the paper is due : 13 February, 2006
* Main Conference: 11-13 May 2006
* Track: max 1 day during the main conference

 Those interested  in running a demo please
contact Jana Sukkarieh <J.Sukkarieh.94 at cantab.net> or Simon Dobnik
<Simon.Dobnik at clg.ox.ac.uk>.

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