Corpora: Corrected address

From: Svetlana Sheremetyeva (lana@crl.nmsu.edu)
Date: Thu May 04 2000 - 22:16:33 MET DST

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                    PLEASE NOTE A CORRECTED ADDRSS for the main conference home page

    > >
    > > CALL FOR PARTICIPATION
    > >
    > > Analysis for Generation
    > >
    > > a Workshop
    > >
    > > in conjunction with
    > >
    > > The International Conference on Natural
    > > Language Generation INLG'2000 (June 13-14)
    > >
    > >
    > > June 12, 2000, Mitzpe Ramon,
    > > Israel
    > >
    > > 1. The reasons why the workshop is of interest at this time.
    > >
    > > The last decade has seen an explosion in the work done in the field of NLG with the
    > > emphasis on the development of independent NLG applications rather than generation
    > > modules of MT systems. While it seems natural to consider problems of
    > > analysis and generation as two sides of a coin in such NLP applications as MT,
    > > researchers working on "pure" generation systems sometimes treat problems arising
    > > at every stage of generation—content specification, sentence planning, and
    > > surface realization—as independent. Time may be ripe for examining the mutual
    > > utility of analysis and generation in greater detail. The impetus is, as can be
    > > expected, the goal of minimizing system-building efforts in language engineering.
    > >
    > > 2. A brief technical description of the issues the workshop will address.
    > >
    > > The workshop proposes to address:
    > >
    > > • issues connected to the needs of analysis in generation systems as well as
    > >
    > > • issues of interrelation between generation and analysis from the standpoint
    > > of reusability and adaptability of analysis techniques and tools for generation.
    > >
    > > • issues of reusability of analysis knowledge and methodology of its
    > > acquisition for generation.
    > >
    > > Analysis as part of generation. A wide range of complex problems which are
    > > considered to be specific for generation—content specification, planning, and
    > > grammaticalization—may lead one to believe that generation is completely
    > > independent
    > > of analysis. Most generators tacitly assume that an intermediate system module can
    > > use the output of the preceding module as its input without any processing (that
    > > is, analysis) of this output. This is not, however, the case in practice.
    > >
    > > A modicum of analysis is, in fact, an essential part of every generation system.
    > > The input to generation systems such as raw data in tables, lists, diagrams,
    > > elements of various databases or even text snippets that are fed into the system
    > > directly
    > > by a user still must first be somehow processed, that is, analyzed. The analysis is
    > > > needed to provide both the necessary content and, often, format for the content
    > > specification (see, for example, Dale 1995, Robin 1994, Kukich 1988, McKeown
    > > et al. 1994, Bateman and Teich 1995). This problem becomes especially important in
    > > those applications (including multilingual ones) in which at least some input to
    > > generation is in textual form (e.g., Sheremetyeva and Nirenburg 1996).
    > > Many NLG systems often use a variety of analysis techniques. The question arises
    > > whether it is possible to develop criteria to better choose and integrate analysis
    > > techniques which could be efficiently applied at different stages of generation.
    > >
    > > Reusability and adaptability of analysis techniques and tools for generation. While
    > > it is not uncommon to believe that generation and analysis are not reversible, a
    > > number of contributions over the years have discussed reversibility of analysis
    > > and generation resources, especially the grammars. Appelt 1987, Barnett and Mani
    > > 1990 and van Noord 1993, among others, demonstrate how the use of reversible
    > > grammars may lead to efficient and flexible natural language parsing and
    > > generation systems. It is worth discussing constraints on reversibility.
    > >
    > > Reusability of analysis knowledge and methodology of its acquisition for
    > > generation. Generation and analysis are closely related in that both processes use
    > > many similar resources, and often it is less expensive to reorganize an existing
    > > "analysis" resource (e.g., an analysis lexicon) than to acquire one for generation
    > > from scratch. (Allgayer et al. 1989, Viegas and Beale 1996, Sheremetyeva and
    > > Nirenburg 1999a, 1999b). It is worth discussing how to establish whether a resource
    > > built for analysis can be used for generation and at what price.
    > >
    > >
    > > THE PROGRAM:
    > > June,12, 00
    > >
    > > 13.00 - 13.15 S. Sheremetyeva. Introduction
    > >
    > > 13.15-13.50 H. Manuelian. Reusability of Mental Representation Theory in
    > > Automatic Generation: Generating Expressions Referring to
    > > Objects with G-TAG and RMs
    > >
    > > 13.50-14.25 D. Lonsdale. Leveraging Analysis Operators in Incremental
    > > Generation
    > >
    > > 14.25-15.00 S. Busemann. Interfacing Constraint-Based Grammars and
    > > Generation Algorithms
    > >
    > > 15.00-15.20 Break
    > >
    > > 15.20-17.00 Panel : R. Kempson, S. Nirenburg, M.Zock, S.Sheremetyeva.
    > >
    > > PLEASE FIND DETAILS ABOUT REGISTRATION AND ACCOMMODATION at the main conference
    > > homepage at
    > >
    > > http://www.cs.bgu.ac.il/~nlg2000
    > > Organizing Committee
    > >
    > > Svetlana Sheremetyeva, Chair and contact person
    > > Computing Research Laboratory, New Mexico State University, USA
    > > lana@crl.nmsu.edu
    > >
    > > Sergei Nirenburg
    > > Computing Research Laboratory, New Mexico State University, USA
    > >
    > > Richard Kittredge
    > > Department of Linguistics and Translation, University of Montreal
    > > kittredge@IRO.UMontreal.CA
    > >
    > > Anna Sagvall Hein
    > > Department of linguistics, Uppsala University
    > > Anna@ling.uu.se
    > >
    > > Evelyne Viegas
    > > Microsoft Corporation
    > > evelynev@microsoft.com
    > >
    > > Michael Zock
    > > Language & Cognition LIMSI - CNRS
    > > zock@limsi.fr



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