## tagger training invoked at Fri Feb 14 01:19:49 PST 2014 with arguments:
                   model = chinese-distsim.tagger
                    arch = generic,suffix(4),prefix(4),unicodeshapes(-1,1),unicodeshapeconjunction(-1,1),words(-2,-2),words(2,2),distsim(/u/nlp/data/chinese/distsim/xin_cmn_2000-2010.ldc.seg.utf8.1M.random-c1000,-1,1),distsimconjunction(/u/nlp/data/chinese/distsim/xin_cmn_2000-2010.ldc.seg.utf8.1M.random-c1000,-1,1)
            wordFunction = edu.stanford.nlp.util.UTF8EquivalenceFunction
               trainFile = format=TREES,/u/nlp/data/chinese/ctb7/train.mrg
         closedClassTags = 
 closedClassTagThreshold = 40
 curWordMinFeatureThresh = 1
                   debug = false
             debugPrefix = 
            tagSeparator = #
                encoding = utf-8
              iterations = 100
                    lang = chinese
    learnClosedClassTags = false
        minFeatureThresh = 3
           openClassTags = 
rareWordMinFeatureThresh = 3
          rareWordThresh = 20
                  search = owlqn
                    sgml = false
            sigmaSquared = 0.0
                   regL1 = 0.75
               tagInside = 
                tokenize = false
        tokenizerFactory = 
        tokenizerOptions = 
                 verbose = false
          verboseResults = true
    veryCommonWordThresh = 250
                xmlInput = null
              outputFile = 
            outputFormat = slashTags
     outputFormatOptions = 
                nthreads = 1
