[Corpora-List] Natural Language and Knowledge Representation (REMINDER)

From: Jana Sukkarieh (jana.sukkarieh@clg.ox.ac.uk)
Date: Wed Nov 09 2005 - 14:14:35 MET

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    NATURAL LANGUAGE AND KNOWLEDGE REPRESENTATION (NL-KR)

    Special Track at FLAIRS 2006

    FINAL CALL FOR PAPERS
    SUBMISSION DEADLINE: 21st of Nov, 2005

    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
    k. where is the NLP or KR community going wrong/right in meeting the above challenge?

    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@cantab.net

    WEB and TECH SUPPORT

    Simon Dobnik, University of Oxford, UK
    email: Simon.Dobnik@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" in the
    2nd half of 2006.

    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@cantab.net> or Simon Dobnik
    <Simon.Dobnik@clg.ox.ac.uk>.



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