edu.stanford.nlp.ie
Class EmpiricalNERPriorBIO<IN extends CoreMap>
java.lang.Object
edu.stanford.nlp.ie.EntityCachingAbstractSequencePriorBIO<IN>
edu.stanford.nlp.ie.EmpiricalNERPriorBIO<IN>
- All Implemented Interfaces:
- SequenceListener, SequenceModel
public class EmpiricalNERPriorBIO<IN extends CoreMap>
- extends EntityCachingAbstractSequencePriorBIO<IN>
- Author:
- Mengqiu Wang
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.EntityCachingAbstractSequencePriorBIO |
extractEntity, getConditionalDistribution, getNumClasses, getPossibleValues, leftWindow, length, matches, otherOccurrences, rightWindow, scoreOf, scoresOf, setInitialSequence, toArray, toString, toString, updateSequenceElement |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
p1
protected double p1
p2
protected double p2
ORGIndex
protected int ORGIndex
LOCIndex
protected int LOCIndex
DEBUG
public static boolean DEBUG
EmpiricalNERPriorBIO
public EmpiricalNERPriorBIO(java.lang.String backgroundSymbol,
Index<java.lang.String> classIndex,
Index<java.lang.String> tagIndex,
java.util.List<IN> doc,
Pair<double[][],double[][]> matrices,
SeqClassifierFlags flags)
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