如何从Stanford NLP工具中获得增强的依赖解析？

Answer 1

这里有关于如何训练模型的信息：

https://stanfordnlp.github.io/corenlp/depparse.html

示例命令：

java -Xmx12g edu.stanford.nlp.parser.nndep.DependencyParser -trainFile fr-ud-train.conllu -devFile fr-ud-dev.conllu -model new-french-UD-model.txt.gz -embedFile wiki.fr.vec -embeddingSize 300 -tlp edu.stanford.nlp.trees.international.french.FrenchTreebankLanguagePack -cPOS

java -mx1g edu.stanford.nlp.tagger.maxent.MaxentTagger -props myPropertiesFile.props 

示例文件：

## tagger training invoked at Sun Sep 23 19:24:37 PST 2018 with arguments:
                   model = english-left3words-distsim.tagger
                    arch = left3words,naacl2003unknowns,wordshapes(-1,1),distsim(/u/nlp/data/pos_tags_are_useless/egw4-reut.512.clusters,-1,1),distsimconjunction(/u/nlp/data/pos_tags_are_useless/egw4-reut.512.clusters,-1,1)
            wordFunction = edu.stanford.nlp.process.AmericanizeFunction
               trainFile = /path/to/training-data
         closedClassTags = 
 closedClassTagThreshold = 40
 curWordMinFeatureThresh = 2
                   debug = false
             debugPrefix = 
            tagSeparator = _
                encoding = UTF-8
              iterations = 100
                    lang = english
    learnClosedClassTags = false
        minFeatureThresh = 2
           openClassTags = 
rareWordMinFeatureThresh = 10
          rareWordThresh = 5
                  search = owlqn
                    sgml = false
            sigmaSquared = 0.0
                   regL1 = 0.75
               tagInside = 
                tokenize = true
        tokenizerFactory = 
        tokenizerOptions = 
                 verbose = false
          verboseResults = true
    veryCommonWordThresh = 250
                xmlInput = 
              outputFile = 
            outputFormat = slashTags
     outputFormatOptions = 
                nthreads = 1

这里有一个详尽的示例训练属性文件列表：

https://github.com/stanfordnlp/corenlp/tree/master/scripts/pos-tagger