22.1002, Calls: Computational Linguistics, Semantics/USA

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LINGUIST List: Vol-22-1002. Tue Mar 01 2011. ISSN: 1068 - 4875.

Subject: 22.1002, Calls: Computational Linguistics, Semantics/USA

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1)
Date: 01-Mar-2011
From: Preslav Nakov [nakov at comp.nus.edu.sg]
Subject: Workshop on Relational Models of Semantics
 

	
-------------------------Message 1 ---------------------------------- 
Date: Tue, 01 Mar 2011 12:31:13
From: Preslav Nakov [nakov at comp.nus.edu.sg]
Subject: Workshop on Relational Models of Semantics

E-mail this message to a friend:
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Full Title: Workshop on Relational Models of Semantics 
Short Title: RELMS-11 

Date: 23-Jun-2011 - 23-Jun-2011
Location: Portland, Oregon, USA 
Contact Person: Preslav Nakov
Meeting Email: nakov at comp.nus.edu.sg
Web Site: http://sites.google.com/site/relms2011/ 

Linguistic Field(s): Computational Linguistics; Semantics 

Call Deadline: 25-Mar-2011 

Meeting Description:

Workshop on Relational Models of Semantics (RELMS-11)
Collocated with ACL 2011 (www.acl2011.org)
June 23, 2011
Portland, Oregon

http://sites.google.com/site/relms2011/
Contact: relms.workshop.2011 at gmail.com

This workshop will bring together NLP researchers whose work deals with relational aspects of language understanding. The ability to reason about semantic relations is a fundamental linguistic competence: it is through recognising explicit and implicit relations between entities and events that humans (and machines) can form a coherent representation of a text's meaning. Numerous recent workshops have focused on lexical semantics; RELMS-11 will highlight relational semantics.

The modeling of semantic relations has been considered from many angles, across a variety of tasks and sub-disciplines. In ontology learning and information extraction, the focus is on learning 'encyclopaedic' relations between entities in the domain of discourse. In structured prediction tasks such as semantic role labeling or biomedical event extraction, systems must reason about the relational content of a text, about which entities and events enter into which mutual relations. The interpretation of compound nouns requires reasoning about probable and plausible relations between two entities, with limited knowledge of context. Some sources of textual information are inherently relational - for example, content in on-line social networks - so computational models can benefit from reasoning explicitly about relational structures. There is also much to gain from understanding the connections between NLP tasks in which semantic relations play a key role. Methods which work for one task tend to generalize to others, and semantic relations tend to interact in interesting ways.

Researchers primarily working on specific modeling contexts stand to gain from understanding the connections between the various NLP tasks in which semantic relations play a key role. As well as considering whether methods used for one task may generalize to others, a key question is how different kinds of semantic relations interact. For example, encyclopedic world knowledge may be of use for 'guiding' structured prediction; this might be particularly useful in impoverished contexts such as compound noun interpretation and 'implicit' semantic role labeling. Conversely, encyclopedic relation learning can be viewed as generalising over instance-level relational analyses. Exploring these connections will be an important theme of the workshop. 

Call for Papers:

Topics of interest include but are not restricted to the following:

- Classification of semantic relations in text, for example in the framework of SemEval-2 Tasks 8 and 9 or TempEval
- Semantic structured prediction: semantic role labeling, event extraction
- Semantic applications of statistical relational learning (Markov Logic, Inductive Logic Programming, and so on)
- Joint modeling of heterogeneous semantic relations, connections between traditionally distinct relational modeling tasks
- Relational information extraction and ontology learning
- Compound noun interpretation and retrieval of implicit semantic relations
- Annotation and evaluation issues relating to semantic relations
- Domain-specific aspects of relation learning

Important Dates:

March 25: Paper submissions due (23:59 Samoa Time/UTC-11)
April 25: Notification of acceptance
May 6: Camera-ready papers due
June 23: RELMS-11 Workshop

Submission Information:

Papers may have up to eight pages of content with an additional page of references. As reviewing will be blind, papers must not include authors' names or affiliations, nor any references that would indicate the authors' identities.

We require the use of the ACL-HLT 2011 LaTeX style files or Microsoft Word Style files tailored for this year's conference.  Papers must conform to the official ACL-HLT 2011 style guidelines.  Authors who are unable to use these style files or submit a PDF file electronically should contact the workshop organizers. Please refer to the Format and ACL-HLT 2011 Style Files sections only at the following URL:

http://www.acl2011.org/call.shtml#submission

Papers should be submitted electronically via:

https://www.softconf.com/acl2011/relms/

Workshop Organizers:

Su Nam Kim, University of Melbourne, Australia
Zornitsa Kozareva, University of Southern California, USA
Preslav Nakov, National University of Singapore, Singapore
Diarmuid Ó Séaghdha, University of Cambridge, UK
Sebastian Padó, Universität Heidelberg, Germany
Stan Szpakowicz, University of Ottawa, Canada

Program Committee:

Eneko Agirre, University of the Basque Country, Spain
Timothy Baldwin, University of Melbourne, Australia
Ken Barker, University of Texas at Austin, USA
Paul Buitelaar, National University of Ireland, Galway, Ireland
Nathanael Chambers, Stanford University, USA
Yee Seng Chan, University of Illinois at Urbana-Champaign, USA
Mark Craven, University of Wisconsin-Madison, USA
Matthew Gerber, Michigan State University, USA
Roxana Girju, University of Illinois at Urbana-Champaign, USA
Sanda Harabagiu, University of Texas at Dallas, USA
Iris Hendrickx, University of Lisboa, Portugal
Raphael Hoffmann, University of Washington, USA
Sophia Katrenko, University of Amsterdam, The Netherlands
Roman Klinger, Fraunhofer Institute for Algorithms and Scientific Computing, Germany
Milen Kouylekov, Celi SRL Torino, Italy
Kenneth Litkowski, CL Research, USA
Dan Moldovan, University of Texas at Dallas, USA
Vivi Nastase, HITS gGmbH, Germany
Roberto Navigli, University of Rome 'La Sapienza', Italy
Patrick Pantel, Microsoft Research, USA
Marco Pennacchiotti, Yahoo! Inc., USA
Simone Paolo Ponzetto, University of Heidelberg, Germany
Sampo Pyysalo, University of Tokyo, Japan
Sebastian Riedel, University of Massachusetts-Amherst, USA
Alan Ritter, University of Washington, USA
Lorenza Romano, FBK-irst, Italy
Dan Roth, University of Illinois at Urbana Champaign, USA
Barbara Rosario, Intel Lab, USA
Caroline Sporleder, Saarland University, Germany
Carlo Strapparava, FBK-irst, Italy
György Szarvas, Technical University of Darmstadt, Germany
Peter Turney, National Research Council of Canada, Canada
Benjamin Van Durme, Johns Hopkins University, USA
Tony Veale, University College Dublin, Ireland
Andreas Vlachos, University of Wisconsin-Madison, USA
Rui Wang, Saarland University, Germany
Limin Yao, University of Massachusetts-Amherst, USA
Deniz Yuret, Koç University, Turkey


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