NBest                      = 50
MaxSimplifiedSentences     = 0
Verbosity                  = 1

PrunningStrategy           = WordCoverageModelScore
MaxHypothesisStackSize     = 200

//Feature settings
FilterDependencyDistance   = false
//Distance to nearest point
MinimumDependencyDistance  = 15
//Distance to farthest point
MaximumDependencyDistance  = 15
//Span between nearest and farthest point
SpanDependencyDistance  = 15

FilterPPAttachment         = false
FilterSinglePronoun        = false
FilterSentenceLikeBoundary = false
FilterObjectInTheSameVP    = false

//Manually assign start feature weights
//If the number of feature weights doest match with FeatSize, tuner will randomly initalize weights
DecoderWeights        = 0.4112 0.8942 0.8615 0.0586 0.2409 0.3838 0.7823 0.3286 0.2914 0.2251 -0.1682 0.8684 0.0843 0.144 0.2243 0.6461 -0.5125 0.2777 0.4803 0.6582 -0.0741 -0.3119 0.0129 -0.2087 0.1477 0.1548 -0.6986
InitWeightsRandom     = yes
FeatureSize           = 177
TrainingReferenceFile = tune.example.ref
TrainingIterations    = 3
mOracle               = 2
C                     = 0.04
LossFunction          = Ngram

