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Category:   E-CFP
Subject:   LREC04 Workshop on "Beyond Named Entity Recognition"
From:   Roberto Basili
Email:   basili_(on)_info.uniroma2.it
Date received:   02 Feb 2004
Start date:   25 May 2004

FINAL CALL FOR PAPERS Workshop Beyond Named Entity Recognition Semantic labelling for NLP tasks URL: http://ai-nlp.info.unir oma2.it/ws_lrec04/ Centro Cultural de Belem LISBON, Portugal 25th may 2004 In Association with 4th INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION LREC2004 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. Submission 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_(on)_info.uniroma2.it Proceedings and Publications Proceedings of the workshop will be printed by the LREC Local Organising Committee. The <http://www.elsevier .com/locate/issn/0885-2308 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_(on)_info.uniroma2.it 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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