LINGUIST List 12.581

Fri Mar 2 2001

Calls: Empirical Method/NLP, Computational NL Learning

Editor for this issue: Jody Huellmantel <>

As a matter of policy, LINGUIST discourages the use of abbreviations or acronyms in conference announcements unless they are explained in the text.


  1. Priscilla Rasmussen, Empirical Methods in NLP: EMNLP-2001 (preceding NAACL-2001)
  2. Priscilla Rasmussen, ACL-2001: Computational Natural Language Learning (CoNLL-2001)

Message 1: Empirical Methods in NLP: EMNLP-2001 (preceding NAACL-2001)

Date: Thu, 1 Mar 2001 13:44:47 EST
From: Priscilla Rasmussen <>
Subject: Empirical Methods in NLP: EMNLP-2001 (preceding NAACL-2001)


(includes submission instructions; note notification deadline)

2001 Conference on Empirical Methods in Natural Language Processing

Sponsored by SIGDAT and the Intelligent Information Systems Institute (IISI).

SIGDAT, the Association for Computational Linguistics' special
interest group on linguistic data and corpus-based approaches to NLP,
invites submissions to EMNLP 2001. The conference will be held at
Carnegie Mellon University, Pittsburgh, PA USA on June 3 and 4,
immediately preceding the meeting of the North American Chapter of the

We are interested in papers from academia, government, and industry on
all areas of traditional interest to the SIGDAT community and aligned
fields, including but not limited to:

* information extraction
* information retrieval
* language and dialog modeling
* lexical acquisition
* machine translation
* multilingual technologies
* question answering
* statistical parsing
* summarization
* tagging
* term and named-entity extraction
* word sense disambiguation
* word, term, and text segmentation

Also, to encourage reflection on the current state of the art in
corpus-based methods, the conference will have the following theme:

 "What Works and What Doesn't: Successes and Challenges"

Successes --- We solicit papers showing the success of empirical
methods in and across application settings. Examples include
improvements in information retrieval performance due to employing
language modeling techniques; effective use of statistical word
segmentation algorithms in machine translation systems; and increased
speech recognition accuracy through the incorporation of statistical

Challenges --- It is clear that empirical and corpus-based methods
have enjoyed many successes over the past years; but in looking to
future accomplishments, the community needs to be aware of the
limitations of various techniques and paradigms. We welcome papers
that carefully expose and study such limitations. Examples include the
identification and exploration of: classes of domains or problems in
which popular techniques perform poorly; significant gaps between
human and machine performance on tasks where statistical approaches
have made great progress; and important practical situations where
common assumptions fail to hold. *** We emphasize that we seek
submissions that thoughtfully document fundamental limitations, rather
than simply report on unsuccessful experiments. *** It is desired that
such papers contain thorough examination, via careful experimentation,
of the critical factors contributing to the "negative" result.


Requirements: Submissions must describe original, completed,
unpublished work, and include concrete evaluation results when
appropriate. Papers being submitted to other meetings must provide
this information (see submission format); in the event of multiple
acceptances, authors are requested to immediately notify the EMNLP
program chair ( and choose which meeting to
present and publish the work at as soon as possible --- EMNLP cannot
accept for publication or presentation work that will be (or has been)
published elsewhere.

Submission Format: Submissions must be hardcopy, and consist of full
papers of not more than 3200 words (exclusive of references). Authors
are strongly encouraged to use the LaTeX style files or MSWord
equivalents available from the EMNLP website -- these formats will
ease the transition to the proceedings version.

Reviewing will be blind. No information identifying the authors should
be in the paper: this includes not only the authors' names and
affilations, but also self-references that reveal authors' identities;
for example, "We have previously shown (Smith 1999)" should be changed
to "Smith (1999) has previously shown". A separate identification
page is required: see below.

Submission procedure: First, an electronic notice of intent to submit
is required. Please email 
(subject line EMNLP 2001 ITS) by March 9 with the following information:

 Paper title
 Authors' names, affiliations, and email addresses
 Contact author
 A short list of keywords 
 A short (no more than 5 lines) summary of the contents
 Whether or not the paper is under consideration for other conferences
 (please specify)							

Then, six hardcopies of the paper together with a single separate
page listing *all* the information from the notice of intent to
submit (i.e., title, authors, contact author, keywords, summary, and
multiple-submission information -- a printout of the notice of intent
to submit suffices) must be received by March 13 at the
following address:

 EMNLP 2001 Submissions
 Lillian Lee
 4130 Upson Hall
 Cornell University
 Ithaca, NY 14853-7501 

The EMNLP committee is not responsible for postal delays or other mail
problems. Papers will not be accepted electronically, and submissions
that do not conform to the guidelines above are subject to rejection
without review.


Notification deadline: March 9, 2001
Submission deadline: March 13, 2001
Acceptance notification: April 13, 2001 
Camera-ready copy due: May 3, 2001
Conference: June 3-4, 2001


Lillian Lee (chair), Cornell University,
Donna Harman (co-chair), NIST,

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Message 2: ACL-2001: Computational Natural Language Learning (CoNLL-2001)

Date: Thu, 1 Mar 2001 13:50:02 EST
From: Priscilla Rasmussen <>
Subject: ACL-2001: Computational Natural Language Learning (CoNLL-2001)



 Fifth Computational Natural Language Learning Workshop 
 Toulouse, France, July 6-7, 2001


CoNLL is the yearly workshop organized by SIGNLL, the Association for
Computational Linguistics Special Interest Group on Natural Language
Learning ( Previous CoNLL meetings were
held in Madrid (1997), Sydney (1998), Bergen (1999) and Lisbon
(2000). The 2001 event will be held as a two-days workshop at the 39th
Annual Meeting of the Association for Computational Linguistics (ACL),
July 6-11, 2001 in Toulouse, France.

This year, a special theme will be the focus of the workshop: 

 Interaction and Automation in Language Learning Resources

Apart from this special theme, the workshop will accept contributions
about language learning topics, including, but not limited to:

 - Computational models of human language acquisition 
 - Computational models of the origins and evolution of language 
 - Machine learning methods applied to natural language processing
 tasks (speech processing, phonology, morphology, syntax, semantics,
 discourse processing, language engineering applications) 
 - Symbolic learning methods (Rule Induction and Decision Tree
 Learning, Lazy Learning, Inductive Logic Programming, Analytical
 Learning, Transformation-based Error-driven Learning) 
 - Biologically-inspired methods (Neural Networks, Evolutionary Computing) 
 - Statistical methods (Bayesian Learning, HMM, maximum entropy, SNoW,
 Support Vector Machines) 
 - Reinforcement Learning 
 - Active learning, ensemble methods, meta-learning 
 - Computational Learning Theory analyses of language learning 
 - Empirical and theoretical comparisons of language learning methods 
 - Models of induction and analogy in Linguistics 

This year's workshop will also accept submissions for a shared task
(segmenting a text into clauses-clausing).


Main Session Theme: Interaction and Automation in Language Learning

The purpose of the special theme is to present and discuss
state-of-the-art learning mechanisms for the automated acquisition of
language resources (dictionaries, ontologies, grammars) or the
automated adaptation of natural language resources/processors to new
domains or languages.

The dimensions of learning that are of interest for this session include:

- The integration of humans/linguists in the learning process 
- The structure of the training data 
- The kind of knowledge that is learned 
- General study of learning methods that are suitable for natural
 language related tasks 

Lately there have been new learning mechanisms that use either large
amounts of raw data or small sets of carefully constructed tagged
training samples. Learning language can be construed as learning
numbers or parameters for some statistical or symbolic system, or
learning rules assigning structures to input data (or a mix of
those). Learning can be done off-line, which introduces the problem of
interpreting (if needed) the derived knowledge before its use in an
NLP engine; or on-line, which raises user interaction
problems. Different approaches are tailored to solve different kinds
of problems subject to a different balance of requirements (large
vs. small training set, tagged vs. untagged training data, results
needs interpretation or can be used as is, etc.). While this session
aims at presenting the largest panorama of learning techniques, we
encourage submission of work on semi-automated learning techniques
that involve interaction with a human during the learning process or
the intervention of a linguist for interpreting results.

Special Session: Shared Task - Segmenting Text Into Clauses 

We invite groups to take part in a shared task: Segmenting a Text Into
Clauses (Clausing). Participating groups will be provided with the
same training and testing material, and will all use the same
evaluation criteria, thus allowing comparison between various learning
technologies. After Chunking, the CoNLL-2000 shared task, Clausing
can be seen as the next step towards a full parsing.

More information on this shared task is available at:

Invited Session: Learning Computational Grammars

There will be a special session devoted to the presentation and
discussion of results of the EU Learning Computational Grammars
project (Coordinator: John Nerbonne). Project participants include:
the University of Groningen (The Netherlands, coordinator), University
of Antwerp (Belgium), the University of Tuebingen (Germany), SRI
Cambridge (UK), the University College Dublin (Ireland), the
University of Geneva (Switzerland), and Xerox Grenoble (France).

Invited Speaker: Eric Brill


Format for Paper Submissions for Main Session 

Submit an abstract of maximum 1500 words (Postscript or ASCII) by
April 6, 2001 electronically to the address below. Authors of accepted
abstracts will be invited to produce a full paper to be published in
the proceedings of the workshop, which will be available at the
workshop for participants, and distributed afterwards by the
ACL. Submit main session abstracts to:

Walter Daelemans, 
Centrum Nederlandse Taal en Spraak. 
Linguistics, Department of Germanic languages and literature 
UIA, University of Antwerp 
Universiteitsplein 1, B-2610 Wilrijk, Belgium 


Rimi Zajac, 
Computing Research Laboratory 
New Mexico State University 
PO Box 30001 Dept. 3CRL 
Las Cruces NM 88003 

Format For Shared Task Submissions

Submit an abstract of maximum 1500 words describing the learning
approach, and your results on the test set by April 6, 2001 to the
address below (preferably by email). A special section of the
proceedings will be devoted to a comparison and analysis of the
results and to a description of the approaches used. Submit shared
task submissions to:

Erik Tjong Kim Sang, 
Centrum Nederlandse Taal en Spraak 
Linguistics, Department of Germanic languages and literature 
UIA, University of Antwerp 
Universiteitsplein 1, B-2610 Wilrijk, Belgium 

Important dates

Deadline for Abstract Submission: April 6, 2001 
Deadline for Shared Task Submission: April 6, 2001 
Notification: April 27, 2001 
Deadline camera-ready full paper: May 16, 2001 
Workshop: July 6/7, 2001 


Walter Daelemans (co-chair) 
Rimi Zajac (co-chair) 
Thorsten Brants (Xerox PARC, USA) 
Michael Brent (Washington University in Saint Louis, USA) 
Claire Cardie (Cornell University, USA) 
James Cussens (University of York, UK) 
Herve Dejean (University of Tuebingen, Germany) 
Gregory Grefenstette (Xerox Grenoble, France) 
Raymond Mooney (University of Texas at Austin, USA) 
John Nerbonne (Groningen University, Netherlands) 
Kemal Oflazer (Sabanci University, Turkey) 
Miles Osborne (University of Edinburgh, UK), 
David Powers (Flinders University, Australia) 
Ronan Reilly (University College Dublin, Ireland) 
Dan Roth (University of Illinois at Urbana-Champaign, USA) 
Erik Tjong Kim Sang (University of Antwerp, Belgium) 
Antal van den Bosch (Tilburg University, Netherlands) 
Yorick Wilks (University of Sheffield, UK) 
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