NAME
WordNet::SenseRelate::TargetWord - modules for performing word sense disambiguation.
DESCRIPTION
In this section, we list the modules provided in the package. A short description of each is provided alongside.
- Preprocessing modules
-
Currently, only one preprocessing module is provided in the package:
- Context Selection modules
-
One context selection module is provided in the package:
- Postprocessing modules
-
As of this vesion, there are no postprocessing modules in the package. However, we intend to add some in future releases.
- Sense Selection Algorithm
-
Four sense selection algorithm modules are provided in the pacakge:
- WordNet::SenseRelate::Algorithm::Local
-
This modules selects that sense of the target word which is most related to the senses of the context words. To do this it uses the "Local" disambiguation algorithm as described by Banerjee and Pedersen (2002). In order to determine the relatedness of senses, the algorithm uses one of the WordNet::Similarity measures of relatedness. Using the configuration options for this module, the user can specify which measure the algorithm should use.
- WordNet::SenseRelate::Algorithm::Global
-
This modules selects that sense of the target word which is most related to the senses of the context words. To do this it uses the "Global" disambiguation algorithm as described by Banerjee and Pedersen (2002). This algorithm is somewhat similar to the "Local" algorithm. It differs from the "Local" algorithm, in that it forms all possible combinations of the senses of the context words, and evaluates the semantic relatedness for each combination separately. The combination with the maximum score is is selected, and the sense of the target word in that combination is returned as the answer.
- WordNet::SenseRelate::Algorithm::SenseOne
-
This module provides a baseline for the disambiguation process by always returning the first sense of the target word as the answer.
- WordNet::SenseRelate::Algorithm::Random
-
This module provides another baseline by randomly selecting one of the senses of the target word as the answer.
Apart from all of the modules mentioned above that form the pieces of the bigger structure, the package also contains the WordNet::SenseRelate::TargetWord module which combines the above pieces.
In order to use these modules in a Perl program for Word Sense Disambiguation, we need only create an instance of the WordNet::SenseRelate::TargetWord module in our program, and provide it with options that indicate which of the above modules (along with configuration options) it should use in the disambiguation process.
Additionally, in order to be able to use this package for disambiguating instances from the Senseval2 or the Senseval3 data sets, the WordNet::SenseRelate::Reader::Senseval2 module has also been provided in the package. The reader module reads in an entire Senseval2 formatted XML file and builds a list of instances from the file. A Perl program can then iterate over these instances and pass them to the WordNet::SenseRelate::TargetWord object.
SEE ALSO
http://groups.yahoo.com/group/senserelate
http://search.cpan.org/dist/WordNet-SenseRelate-TargetWord
http://senserelate.sourceforge.net
AUTHORS
Siddharth Patwardhan, University of Utah, Salt Lake City
sidd at cs.utah.edu
Satanjeev Banerjee, Carnegie Mellon University, Pittsburgh
banerjee+ at cs.cmu.edu
Ted Pedersen, University of Minnesota Duluth
tpederse at d.umn.edu
COPYRIGHT AND LICENSE
Copyright (C) 2005 Siddharth Patwardhan, Ted Pedersen, and Satanjeev Banerjee
Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.
Note: a copy of the GNU Free Documentation License is available on the web at http://www.gnu.org/copyleft/fdl.html and is included in this distribution as FDL.txt.