edu.stanford.nlp.ie
Class EmpiricalNERPrior
java.lang.Object
edu.stanford.nlp.ie.EntityCachingAbstractSequencePrior
edu.stanford.nlp.ie.EmpiricalNERPrior
- All Implemented Interfaces:
- SequenceListener, SequenceModel
public class EmpiricalNERPrior
- extends EntityCachingAbstractSequencePrior
- Author:
- Jenny Finkel
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 |
EmpiricalNERPrior
public EmpiricalNERPrior(String backgroundSymbol,
Index classIndex,
List<CoreLabel> doc)
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