NERSSEAL 2008

NERSSEAL 2008
IJCNLP Workshop on NER for South and South East Asian Languages
Dates	Jan 12, 2008 (iCal) - Jan 12, 2008
Homepage:	ltrc.iiit.ac.in/ner-ssea-07
Location
Location:	Hyderabad, India
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Important dates
Submissions:	Sep 21, 2007
Table of Contents

Call for Papers

Papers are invited on substantial, original, and unpublished research on all aspects of Named Entity Recognition (NER) for South and South East Asian (SSEA) languages. At least one of the languages considered should be an SSEA language. We also invite researchers to be contestants in a shared task (the second track of the workshop) on NER for SSEA languages.
Background and Motivation

Most of the SSEA languages are scarce in resources as well as tools and NER systems are no exception. It is very important that good systems for NER be available, because many problems in information extraction and machine translation (among others) are dependent on accurate NER. However, the issues involved are significantly different for these languages from those for European languages or even East Asian languages. For example, these languages do not have capitalization, which is a major feature for NER systems for European languages.

Another similarity among these languages is that most of them use scripts of Brahmi origin. For some languages, there are additional issues like word segmentation (e.g. for Thai). Large gazetteers are not available for most of these languages. There is also the problem of lack of standardization and spelling variation. The number of frequently used words which can also be used as names is very large for many languages, unlike European languages where a larger proportion of the first names are not used as common words. And most importantly, there is a serious lack of labeled data for machine learning.
Scope

This workshop will be the second stage of an annual event called NLPAI Machine Learning Contest which focuses on application of machine learning techniques for one major NLP problem every year. This year the problem was NER. However, unlike that event, this workshop will have one track for regular research papers on NER for SSEA languages and the second track will be on the lines of a shared task.
Shared Task

In the shared task, the contestants having their own NER systems will be given some annotated test data. The participating systems will be ranked according to their performance on the test data. There may or may not be training data for a particular language. In either case, the contestants will have the freedom to use any technique for NER, e.g. a purely rule based technique or a purely statistical technique.

At present some data is available for Hindi, Bengali and Telugu for the shared task. Other languages can be included in the contest provided data for them becomes available. The data released for the shared task will be made accessible to all researchers, not just the participants.

If the language you are interested in has not been included in the shared task, you can also prepare the annotated test data and submit it to us. We will then include that language in the shared task.

The task in this contest will be different in one important way. The NER systems also have to identify nested named entities. For example, in the sentence The Lal Bahadur Shastri National Academy of Administration is located in Mussoorie, 'Lal Bahadur Shastri' is a Person, but 'Lal Bahadur Shastri National Academy of Administration' is an Organization. In this case, the NER systems will have to identify both 'Person' and 'Organization' in the given sentence.
Submission

Paper submission is through the centralized workshop submission page. Papers have to be written in English. Note that shared task contestants also have to submit a paper describing their method and the results etc. Long or short papers can be submitted to either of the tracks. Long papers can be up to 8 pages long, while the maximum length for short papers is 5 pages (including references, figures, tables etc.). All selected papers will be published in the workshop proceedings.

The papers should be formatted using the LaTeX styles or MS Word templates recommended for the main IJCNLP conference. These documents are available here. Reviewing will be blind. The draft papers should not contain any information that can identify the authors, as far as possible.
Important Dates

    * Release of Training and Development Data: Aug 2 to Aug 25, 2007 (for different languages)
    * Release of Test Data: Sept 13, 2007
    * Annotated Test Data Submission Deadline: Sept 15, 2007
    * Paper Submission Deadline: Sept 21, 2007
    * Notification of Paper Acceptance: Oct 26, 2007
    * Camera Ready Submission Deadline: Nov 16, 2007

Note: There is no separate registration for the shared task(the contest). You will be a contestant if you submit the annotated test data by the deadline mentioned above.
Program Committee
Rajeev Sangal, IIIT, Hyderabad, India

Dekai Wu, The Hong Kong University of Science & Technology, Hong Kong

Ted Pedersen, University of Minnesota, USA

Dipti Misra Sharma, IIIT, Hyderabad, India

Virach Sornlertlamvanich, TCL, NICT, Thailand

M. Sasikumar, CDAC, Mumbai, India

Sudeshna Sarkar, Indian Institute of Technology, Kharagpur, India

Thierry Poibeau, CNRS, France

Sobha L., AU-KBC, Chennai, India

Tzong-Han Tsai, National Taiwan University, Taiwan

Prasad Pingali, IIIT, India

Canasai Kreungkrai, NICT, Japan

Manabu Sassano, Yahoo Japan Corporation, Japan

Anil Kumar Singh, IIIT, Hyderabad, India

Doaa Samy, Universidad Aut�noma de Madrid, Spain

Ratna Sanyal, Indian Inst. of Inf. Tech., Allahabad, India

V. Sriram, IIIT, Hyderabad, India

Anagha Kulkarni, Carnegie Mellon University, USA

Soma Paul, IIIT, Hyderabad, India

Contact Persons
Dipti Misra Sharma, Rajeev Sangal, Anil Kumar Singh
Language Technologies Research Centre
International Institute of Information Technology
Gachibowli, Hyderabad, India

Phone: 91-40-23001412, 91-40-23001967/9 Extension 144
Fax: 91-40-23001413
Email: dipti@iiit.ac.in, sangal@iiit.ac.in, anil@research.iiit.ac.in
	

This CfP was obtained from WikiCFP