Appel: LREC workshop: Beyond Named Entity Recognition ...

alexis.nasr at LINGUIST.JUSSIEU.FR alexis.nasr at LINGUIST.JUSSIEU.FR
Tue Feb 3 08:53:25 UTC 2004

                 FINAL CALL FOR PAPERS


             Beyond Named Entity Recognition
               Semantic labelling for NLP tasks


                          Centro Cultural de Belem
                               LISBON, Portugal
                                  25th may 2004

In Association with
Main conference 26-27-28 May 2004

Motivation and Aims

Although it is generally assumed that improvements in language
processing will be made through the integration of linguistic
information and statistical techniques, the reality is that language is
very diverse and looking for specific patterns of words that repeat
enough to be statistically significant tends not to be a very fruitful
task: sequences longer than three words are not generally repeated often
enough to be statistically significant. At the same time, the
identification of named entities: Names, dates, places, organizations
etc., has proved to be a very useful preliminary task in many natural
language processing systems are interested in pursuing approaches which
extend this notion by identifying and labeling other semantic
information in a text, in such as way as to allow repeatable semantic
patterns to emerge.  Our interest is in attacking the data sparseness
problem by exploring ways to collapse (semantically) related phrases
which are expressed by different word sequences.

As this seems closely related to previously proposed class-based
language models (see for example Brown et al. 90 in Computational
Linguistics), it is distinguished because the empirical notion of
classes used in the previous work (e.g. classes made up of
collocationally similar words) are replaced by semantically justified sets.

Notice how Name Entity (NE) tagging and Word Sense Disambiguation (WSD)
represent, in terms of granularity and representational complexity, two
extremes of a single general problem: semantic disambiguation. Semantic
disambiguation serves thus the purpose of improving the generalization
power of statistical models. One of the questions here is how to
determine a suitable level of clustering (for NE identification and for
WSD) that would lead to high accuracy and to performance improvement by
obtained statistical models.

Reason of Interest

It is to be noticed that a set of independent research work focused
recently on the statistical treatment of semantic phenomena (e.g.
WordNet navigation as a stochastic process, as studied in Light and
Abney or in Ciaramita & Johnson) highly correlates with the research
program proposed above.

The workshop will represent a forum where experience from lexical
semantics and statistical learning will be presented and fruitful
discussion among researchers in both fields will be promoted. The
workshop is expected to attract researchers and practitioners from a
range of areas as well as developers of large scale semantic resources
who are interested in effective methods of semantic labeling.

Topics (to be addressed in the workshop include, but are not limited to)

* Methods for lexical - semantic annotation of corpora
* Methods and Standards for lexical semantic representation of
dictionary information
* Lexico-semantic taxonomies
* Existing sources of classification: dictionaries, thesauri and
computerized ontologies
* Corpus-driven methods for semantic disambiguation
* Feature selection for semantic disambiguation
* Lexico-semantic tagging of very large corpora
* Algorithms and methods for disambiguation of semantic phenomena
* Statistical learning models and their applications to semantic labeling
* Computational learning frameworks for Natural Language Learning
* Semi-supervised and unsupervised statistical semantic disambiguation
* Evaluation of semantic disambiguation

Workshop format

The workshop will be a half-day event with position statements from
invited speakers (half an hour each) with two hours for 4-6
presentations of scientific papers. Submissions are intended to present
works in progress and more completed works which fall within the scope
defined by the topics listed above.  A final 1 hour open discussion
among all the workshop participants will be moderated by the organizers.
In order to stimulate an interesting general discussion each member of
the program committee will be invited to submit a position statement of
max. 1000 words.


Participants are invited to submit an extended abstract of max. 3500
words concerning one or more of the topics of interest. Each accepted
paper receives a slot of 25 minutes for presentation (15 minutes talk
and 10 minutes for discussion). Each submission should show: title;
author(s); affiliation(s); and contact author's e-mail address, postal
address, telephone and fax numbers. Submissions must be sent
electronically in PDF to the following address:

Roberto Basili
Dept. of Computer Science, Systems and Management
University of Roma Tor Vergata
e-mail: basili at

Proceedings and Publications

Proceedings of the workshop will be printed by the LREC Local Organising
The < Computer, Speech and
Language> journal will dedicate to the workshop topics a Special Issue
on "Semantic tagging/labelling for NLP tasks". Relevant papers submitted
to the workshop will be selected to appear in that special issue.

Important dates

Extended abstract submission (max. 3500 words): 16th of February 2004
Notification of acceptance: 8th of March 2004
Preliminary Program: 29th of March 2004
Submission of the final version of paper: 5th of April 2004
Workshop: 25th May 2004

Organising Committee

Louise Guthrie - University of Sheffield, UK
Roberto Basili - University of Rome, Tor Vergata, Italy
Eva Hajicova - Charles University, Czech Republic
Frederick Jelinek - Johns Hopkins University, Maryland, USA

Further Information
For any information related to the organization, please contact:
Roberto Basili
e-mail: basili at
Dept. of Computer Science, Systems and Management
University of Roma Tor Vergata
Via di Tor Vergata
00133 Roma (ITALY)
tel:     +39 06 72597391
fax:    +39 06 72597460

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