Corpora: Call for participation

[Svetlana Sheremetyeva]

>
>                                                   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.il/~nlg2000
> Organizing Committee
>
>   Svetlana Sheremetyeva, Chair and contact person
>   Computing Research Laboratory, New Mexico State University, USA
>   lana at crl.nmsu.edu
>
>   Sergei Nirenburg
>  Computing Research Laboratory, New Mexico State University, USA
>
>   Richard Kittredge
>   Department of Linguistics and Translation, University of Montreal
>   kittredge at IRO.UMontreal.CA
>
>   Anna Sagvall Hein
>   Department of linguistics, Uppsala University
>   Anna at ling.uu.se
>
>   Evelyne Viegas
>   Microsoft Corporation
>   evelynev at microsoft.com
>
>   Michael Zock
>   Language & Cognition LIMSI - CNRS
>   zock at limsi.fr