Appel: EMNLP 2001

Philippe Blache pb at
Wed Jan 31 17:59:28 UTC 2001

From: Priscilla Rasmussen <rasmusse at>


2001 Conference on Empirical Methods in Natural Language Processing

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 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.


Submissions should take the form of full papers (3200 words or
less, excluding references) describing original work.  Papers being
submitted to other meetings must provide this information on the title


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, llee at
Donna Harman (co-chair), NIST, donna.harman at


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