[Corpora-List] CFP: Special CL issue on Semantic Role Labeling

[Ken Litkowski]

Call for papers:

	Special issue of Computational Linguistics on
		Semantic Role Labeling

Special issue website: http://www.lsi.upc.edu/~carreras/srlcl.html

BACKGROUND
----------
The general problem of interpreting text involves the determination of 
the semantic relations among the entities and the events they 
participate in. Given a sentence, one formulation of the task consists 
of detecting basic event structures such as "who" did "what" to "whom", 
"when" and "where". From a linguistic point of view, a key component of 
the task corresponds to identifying the semantic arguments filling the 
roles of the sentence predicates. These predicates are mainly 
lexicalized by verbs but also by some verb nominalizations and 
adjectives. Typical predicate semantic arguments include Agent, Patient, 
and Instrument; semantic roles may also be found as adjuncts (e.g., 
Locative, Temporal, Manner, and Cause). The related tasks of determining 
the semantic relations among nouns and their modifiers, as well as 
prepositions and their arguments, are clearly important for text 
interpretation as well, and indeed often draw on similar role labels.

As with many areas in computational linguistcs (CL) and Natural Language 
Processing (NLP), work has proceeded for decades on manually created 
semantic grammars and other resources for supporting text interpretation 
(e.g., [Hirst 1987], [Pustejovsky 1995], [Copestake and Flickinger 
2000]). This body of research has supported deep semantic analysis of 
language input, but has the drawbacks typical of such approaches in 
requiring intensive manual labor, often restricted to narrow domains. 
The growth of statistical machine learning methods, addressing these 
issues of the knowledge acquisition bottleneck, were for many years 
limited in this area to related problems of learning subcategorization 
frames [Briscoe and Carroll 1997] or classifying verbs according to 
argument structure properties [Merlo and Stevenson 2001] [Schulte im 
Walde 2000], due to the lack of appropriate resources to support such 
methods in labeling semantic roles of arguments.

Recently, however, the compilation and manual annotation with semantic 
roles of medium-large corpora - the PropBank, NomBank, and FrameNet 
initiatives - has enabled the development of statistical approaches 
specifically for the task of semantic role labeling (SRL). SRL, 
especially focused on the labeling of verbal arguments and adjuncts, has 
become a well-defined task with a substantial body of work and 
comparative evaluation (e.g., see [Gildea and Jurafsky 2002], [Surdeanu 
et al. 2003], [Xue and Palmer 2004], [Pradhan et al. 2005], CoNLL Shared 
Task in 2004 and 2005, Senseval-3). The identification of such event 
frames holds potential for significant impact in many NLP applications, 
as suggested by the following works on Information Extraction [Surdeanu 
et al. 2003], Question Answering [Narayanan and Harabagiu 2004], 
Summarization [Melli et al. 2005], and Machine Translation [Boas 2002]; 
as well, work on noun modifier relations has been encouraging for 
related NLP tasks (e.g., [Moldovan and Badulescu 2005], [Rosario and 
Hearst 2004]). Although the use of SRL systems in real-world 
applications has so far been limited, the outlook is promising over the 
next several years for a spread of this type of analysis to a range of 
applications requiring some level of semantic interpretation. Moreover, 
the problem represents an excellent framework to perform research on CL 
and NLP techniques for acquiring and exploiting semantic relations among 
the different components of the structured output to be constructed.

TOPICS
------
The call for papers of this special issue invites submissions of 
articles describing novel and challenging work and results in Semantic 
Role Labeling (SRL) and its applications, with emphasis on the 
evaluation of qualitative and quantitative aspects that give a deep 
insight on the SRL task and, in general, on the syntactico-semantic 
processing of natural language. The range of topics to be covered 
includes, but is not limited to:

     * Novel statistical and machine learning approaches and 
architectures for SRL
     * Study of the relevant information/knowledge for the task
     * Learning from small training sets
     * Unsupervised models for SRL
     * Scalability of the state-of-the-art systems
     * How to make systems robust against annotation errors
     * Inclusion of deep semantic information and relations
     * Generalization to new corpora and to new unseen frames
     * Knowledge-based approaches to SRL and comparison to the 
statistical approach
     * Combination of systems and approaches, specially addressing the 
integration of knowledge-based and statistical views
     * Study of the relation between the syntactic and semantic layers 
for SRL characterization and system development
     * Applications of SRL (e.g., in domains such as Q&A, MT, 
Summarization, etc.)
     * Evaluation: new metrics for direct evaluation and indirect 
evaluations through applications
     * Development of copora and resources for the task
     * SRL for languages other than English

IMPORTANT DATES
---------------
Call for papers: 15 March 2006
Submission of articles: 15 July 2006
Preliminary decisions to authors: 15 November 2006
Submission of revised articles: 31 January 2007
Final decisions to authors: 15 March 2007
Final versions due from authors: 15 April 2007
Publication: Fall 2007

SUBMISSION INSTRUCTIONS
-----------------------
Articles submitted to this special issue must adhere to the 
Computational Linguistics Style Guidelines. Please follow the link on 
the website to find the CL Style Guide and LaTeX style files.

Articles are to be sent electronically by email in Adobe's PDF format. 
Instructions will be provided at the web site.


GUEST EDITORS
-------------
Guest Editors

Lluís Màrquez, Technical University of Catalonia
Kenneth C. Litkowski,  CL Research
Suzanne Stevenson,  University of Toronto
Xavier Carreras, Technical University of Catalonia

GUEST EDITORIAL BOARD
---------------------
See the web site for the members of the guest editorial board (still in 
the process of being finalized).
-- 
Ken Litkowski                     TEL.: 301-482-0237
CL Research                       EMAIL: ken at clres.com
9208 Gue Road
Damascus, MD 20872-1025 USA       Home Page: http://www.clres.com