18.786, Software: Shallow Semantic Parser, New Release

[LINGUIST Network]

LINGUIST List: Vol-18-786. Wed Mar 14 2007. ISSN: 1068 - 4875.

Subject: 18.786, Software: Shallow Semantic Parser, New Release

Moderators: Anthony Aristar, Eastern Michigan U <aristar at linguistlist.org>
            Helen Aristar-Dry, Eastern Michigan U <hdry at linguistlist.org>
 
Reviews: Laura Welcher, Rosetta Project  
       <reviews at linguistlist.org> 

Homepage: http://linguistlist.org/

The LINGUIST List is funded by Eastern Michigan University, 
and donations from subscribers and publishers.

Editor for this issue: Hannah Morales <hannah at linguistlist.org>
================================================================  

To post to LINGUIST, use our convenient web form at
http://linguistlist.org/LL/posttolinguist.html.


===========================Directory==============================  

1)
Date: 13-Mar-2007
From: Sebastian Pado < pado at coli.uni-saarland.de >
Subject: Shallow Semantic Parser, New Release 

	
-------------------------Message 1 ---------------------------------- 
Date: Wed, 14 Mar 2007 13:45:40
From: Sebastian Pado < pado at coli.uni-saarland.de >
Subject: Shallow Semantic Parser, New Release 
 


Dear all,

This is to announce the release 1.1 of Shalmaneser (a SHALlow seMANtic
parSER), a system for automatic sense assignment and semantic role
labeling. Shalmaneser comes with pre-trained FrameNet classifiers for
English and German. (Further details below.)

Improvements over the previous release (1.0) include:

- Pre-trained English classifiers for FrameNet release 1.3 (i.e. improved
coverage and accuracy)
- Support for TreeTagger as POS Tagger for both English and German 
- Removal of numerous bugs

You can download the software from this URL:

http://www.coli.uni-saarland.de/projects/salsa/shal/ 

Again, please let us know if you have any questions, comments, or suggestions!

Best,
Sebastian Pado and Katrin Erk

--
Purpose of Shalmaneser

Shalmaneser has been developed with two uses in mind: research in
applications that use shallow semantic parses, and research on better
shallow semantic parsing. So Shalmaneser can be used either as a 'black
box' to obtain semantic parses for free text, or as a research platform 
that can be extended to new parsers, languages, or classification paradigms.

Features of Shalmaneser

- Shallow semantic parser: word sense disambiguation for predicates, plus
semantic role labeling
- Input: plain text. Syntactic processing integrated
- Classifiers available: trained on FrameNet data for English and German
(System also applicable to other frameworks)
- System output can be viewed graphically in the SALTO viewer: 
http://www.coli.uni-saarland.de/projects/salsa/page.php?id=software
- System realized as a toolchain of independent modules communicating
through a common XML format, hence extensible by further modules
- Interfaces for addition/exchange of parsers, learners, features

More information

K. Erk and S. Pado: Shalmaneser - a flexible toolbox for semantic role
assignment. Proceedings of LREC-06, Genoa.
http://www.coli.uni-saarland.de/~pado/pub/papers/lrec06_erk.pdf 
Linguistic Field(s): Computational Linguistics
                     Semantics
                     Syntax




-----------------------------------------------------------
LINGUIST List: Vol-18-786