Contents

trainFile = /u/nlp/data/ner/goodClassifiers/data/all.3class.train
testFile = /u/nlp/data/ner/column_data/conll.testa
serializeTo = all.3class.newdistsim.crf.ser.gz

type = crf

#distSimLexicon = /u/nlp/data/pos_tags_are_useless/englishGigaword.200.pruned
#distSimLexicon = /u/nlp/data/pos_tags_are_useless/egw.bnc.200
distSimLexicon = /u/nlp/data/pos_tags_are_useless/egw4-reut.512.clusters
useDistSim = true

map = word=0,answer=1

saveFeatureIndexToDisk = true

useClassFeature=true
useWord=true
#useWordPairs=true
useNGrams=true
noMidNGrams=true
maxNGramLeng=6
usePrev=true
useNext=true
#useTags=true
#useWordTag=true
useLongSequences=true
useSequences=true
usePrevSequences=true
maxLeft=1
useTypeSeqs=true
useTypeSeqs2=true
useTypeySequences=true
useOccurrencePatterns=true
useLastRealWord=true
useNextRealWord=true
#useReverse=false
normalize=true
# normalizeTimex=true
wordShape=chris2useLC
useDisjunctive=true
disjunctionWidth=5
#useDisjunctiveShapeInteraction=true

readerAndWriter=edu.stanford.nlp.sequences.ColumnDocumentReaderAndWriter

useObservedSequencesOnly=true

useQN = true
QNsize = 25

# makes it go faster
featureDiffThresh=0.05

Version data entries

3 entries across 3 versions & 1 rubygems

Version	Path
stanford-core-nlp-0.1.2	bin/classifiers/all.3class.distsim.prop
stanford-core-nlp-0.1.1	bin/classifiers/all.3class.distsim.prop
stanford-core-nlp-0.1	bin/classifiers/all.3class.distsim.prop