Corpora: Linguistic Knowledge Acquisition and Representation: NEW DEADLINE

[Alessandro Lenci]

********************** NEW DEADLINE: 25th of February 2002 **************


                              LREC 2002 Workshop on

                 LINGUISTIC KNOWLEDGE ACQUISITION AND REPRESENTATION:
                        BOOTSTRAPPING ANNOTATED LANGUAGE DATA

                        Las Palmas, Canary Islands, Spain

                                  2nd June 2002


********************** NEW DEADLINE: 25th of February 2002 **************

                          _____________________________

MOTIVATION AND AIMS

Provision of large-scale labelled language resources, such as tagged 
corpora or repositories of pre-classified text documents, is a crucial key 
to steady progress in an extremely wide spectrum of research, technological 
and business areas in the HLT sector. The continuously changing demands for 
language-specific and application-dependent annotated data (e.g. at the 
syntactic or at the semantic level), indispensable for design validation 
and efficient software prototyping, however, are daily confronted by the 
labelled-data bottleneck. Hand-crafted resources are often too costly and 
time-consuming to be produced at a sustainable pace, and, in some cases, 
they even exceed the limits of human conscious awareness and descriptive 
capability.

Possible ways to circumvent, or at least minimise, this problem come from 
the literature on automatic knowledge acquisition and, more generally, from 
the machine-learning community. Annotated data are bootstrapped by training 
a machine-learning classifier with a small sample of pre-annotated data and 
by using the induced classifier to annotate more data. Co-learning provides 
an alternative methodology, which essentially consists in iterative 
cooperation of two or more independent learning systems. Another promising 
route consists in automatically tracking down recurrent knowledge patterns 
in unstructured or implicit information sources (such as free texts or 
machine readable dictionaries) for this information to be moulded into 
explicit representation structures (e.g. subcategorisation frames, 
syntactic-semantic templates, ontology hierarchies etc.).

We believe that all these attempts at bootstrapping labelled data are not 
only of practical interest (for continuous updating, management and 
validation of dynamic resources), but also point to a bunch of germane 
theoretical issues. In particular, the workshop intends to focus on the 
issue of interaction between techniques for inducing structured knowledge 
from raw data and formal methods of linguistic knowledge representation. 
Gaining insights into this issue is an essential requirement for explaining 
the effective use of linguistic knowledge by cognitive agents. Although the 
cognitive and engineering views of the form and acquisition of linguistic 
knowledge need not be related, data from neuroscience and psychology are 
indeed relevant when evaluating different ways of representing information 
in artificial systems, and different models for linguistic knowledge 
acquisition.

We encourage in-depth analysis of underlying assumptions of the proposed 
bootstrapping methods and discussion of possible relevant connections with 
existing annotation and representation schemes. This investigation is 
likely to have significant repercussions on the way linguistic resources 
will be designed, developed and used for applications in the years to come. 
As the two aspects of knowledge representation and acquisition are 
profoundly interrelated, progress on both fronts can only be achieved, in 
our view of things, through a full appreciation of this deep interdependency.


TOPICS OF INTEREST

Possible themes for contributions are:
* development of  'data-driven' annotation/representation schemes
* dynamic update, customisation and tuning of labelled resources through 
acquired data
* 'hybrid models' of linguistic knowledge extraction, whereby machine 
learning methods are integrated with formal structures of knowledge 
representation
* incremental linguistic knowledge-bases
* formal representation and structuring of information flow automatically 
acquired from texts
* knowledge acquisition and linguistic resources lifecycle
* linguistic knowledge acquisition and representation in cognitive tasks


NEW!!!  IMPORTANT DATES  NEW!!!

Deadline for workshop abstract submission:
25th of February 2002

Notification of acceptance:
20th of March 2002

Final version of paper for workshop proceedings:
20th of April 2002

Workshop:
2nd June 2002 (afternoon session)


SUBMISSIONS

The organizers welcome contributions describing existing research related 
to the topics of the workshop. Each presentation will be 25 minutes long 
(20 minutes for presentation and 5 minutes for questions and discussion). 
Submissions should include: title; author(s); affiliation(s); and contact 
author's e-mail address, postal address, telephone and fax numbers. 
Abstracts (maximum 500 words, plain-text format) must be sent to: 
simo at ilc.pi.cnr.it

The final version of the accepted papers should not be longer than 4,000 
words or 10 A4 pages. Instructions for formatting and presentation of the 
final version will be sent to authors upon notification of acceptance.


ORGANISING COMMITEE

Alessandro Lenci (Università di Pisa, Italy)
Simonetta Montemagni (Istituto di Linguistica Computazionale - CNR, Italy)
Vito Pirrelli (Istituto di Linguistica Computazionale - CNR, Italy)


PROGRAM COMMITTEE

Harald Baayen (Max Planck Institute for Psycholinguistics - Nijmegen, The 
Netherlands)
Rens Bod (University of Amsterdam, Holland)
Michael R. Brent (Washington University, USA)
Nicoletta Calzolari (Istituto di Linguistica Computazionale - CNR, Italy)
Jean-Pierre Chanod (Xerox Research Centre Europe, Grenoble, France)
Walter Daelemans (University of Antwerp, Belgium)
Dekang Lin (University of Alberta, Edmonton, Canada)
Horacio Rodriguez (Universidad Politecnica de Catalunya)
Fabrizio Sebastiani (Istituto per l'Elaborazione dell'Informazione - CNR, 
Italy)
Lucy Vanderwende (Microsoft Research, Redmond, USA)
François Yvon (Ecole Nationale Superieure des Telecommunications, Paris 
Frances)
Menno van Zaanen (University of Amsterdam, The Netherlands)


CONTACT PERSON

Simonetta Montemagni
Istituto di Linguistica Computazionale (ILC) - CNR
Area della Ricerca di Pisa
Via Moruzzi 1, 56124 Pisa, ITALY
e-mail: simo at ilc.pi.cnr.it


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://listserv.linguistlist.org/pipermail/corpora/attachments/20020214/a595a31a/attachment.htm>