edu.stanford.nlp.ie
Class EmpiricalNERPrior

java.lang.Object
  extended by edu.stanford.nlp.ie.EntityCachingAbstractSequencePrior
      extended by edu.stanford.nlp.ie.EmpiricalNERPrior
All Implemented Interfaces:
SequenceListener, SequenceModel

public class EmpiricalNERPrior
extends EntityCachingAbstractSequencePrior

Author:
Jenny Finkel

Field Summary
 
Fields inherited from class edu.stanford.nlp.ie.EntityCachingAbstractSequencePrior
backgroundSymbol, classIndex, doc, numClasses, possibleValues, sequence
 
Constructor Summary
EmpiricalNERPrior(String backgroundSymbol, Index classIndex, List<CoreLabel> doc)
           
 
Method Summary
 double scoreOf(int[] sequence)
          Computes the score assigned by this model to the whole sequence.
 
Methods inherited from class edu.stanford.nlp.ie.EntityCachingAbstractSequencePrior
addingSingletonEntity, appendingEntity, extractEntity, getConditionalDistribution, getNumClasses, getPossibleValues, joiningTwoEntities, leftWindow, length, matches, noChange, otherOccurrences, prependingEntity, removingBeginningOfEntity, removingEndOfEntity, rightWindow, scoreOf, scoresOf, setInitialSequence, splittingTwoEntities, toArray, toString, toString, updateSequenceElement
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

EmpiricalNERPrior

public EmpiricalNERPrior(String backgroundSymbol,
                         Index classIndex,
                         List<CoreLabel> doc)
Method Detail

scoreOf

public double scoreOf(int[] sequence)
Description copied from interface: SequenceModel
Computes the score assigned by this model to the whole sequence. Typically this will be an unnormalized probability in log space (since the probabilities are small).

Parameters:
sequence - the sequence to compute a score for
Returns:
the score for the sequence


Stanford NLP Group