edu.ucla.sspace.mains

Class LexSubWordsiMain.LexSubWordsi

java.lang.Object

edu.ucla.sspace.mains.LexSubWordsiMain.LexSubWordsi

All Implemented Interfaces:

Wordsi

Enclosing class:

LexSubWordsiMain

public static class LexSubWordsiMain.LexSubWordsi
extends Object
implements Wordsi

Constructor Summary

Constructors

Constructor and Description
LexSubWordsiMain.LexSubWordsi(String outFile, String sspaceFile)

Method Summary

Methods

Modifier and Type	Method and Description
boolean	acceptWord(String focus) Returns true if this Wordsi implementation should generate a semantic vector for word.
String	getBaseSense(String focus, SparseDoubleVector vector)
void	handleContextVector(String focus, String secondary, SparseDoubleVector vector) Performs some operation with contextVector, which can be indexed by either primaryKey, secondaryKey, or both.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

LexSubWordsiMain.LexSubWordsi

public LexSubWordsiMain.LexSubWordsi(String outFile,
                             String sspaceFile)

Method Detail

acceptWord

public boolean acceptWord(String focus)

Description copied from interface: Wordsi

Returns true if this Wordsi implementation should generate a semantic vector for word.

Specified by:

acceptWord in interface Wordsi

handleContextVector

public void handleContextVector(String focus,
                       String secondary,
                       SparseDoubleVector vector)

Description copied from interface: Wordsi

Performs some operation with contextVector, which can be indexed by either primaryKey, secondaryKey, or both. This operation will likely assign the contextVector to some cluster immediately or store the contextVector so that it may be clustered with all other other context vecetors generated for primaryKey.

The secondaryKey does not need to be used, but some experiments may require it, such as the SenseEval/SemEval evaluation or pseudo-word disambiguation. For SenseEval/SemEval evaluations, a SenseEvalContextExtractor should be used, which will provide the context id as the secondaryKey; reporting should be done with a SenseEvalReporter. For pseudo-word disambiguation/discrimination, a PseudoWordContextExtractor should be used, which will create pseudo-words for some set of tokens. This extractor will use the pseudo-word for the primaryKey and the original token as the secondaryKey.

Specified by:

handleContextVector in interface Wordsi

Parameters:

focus - The primary key for contextVector

vector - a SparseDoubleVector that represents a single context for a word

getBaseSense

public String getBaseSense(String focus,
                  SparseDoubleVector vector)