我以编程方式训练了斯坦福NER格式，但没有模型文件

Question

String prop = "austen.prop";
Properties props = StringUtils.propFileToProperties(prop);
String to = props.getProperty("serializeTo");
props.setProperty("serializeTo", "C:\ner-jxy-model.ser.gz");
SeqClassifierFlags flags = new SeqClassifierFlags(props);
CRFClassifier<CoreLabel> crf = new CRFClassifier<CoreLabel>(flags);
crf.train();

这是我的奥斯汀道具

#location of the training file
trainFile = train.tsv
#location where you would like to save (serialize to) your
#classifier; adding .gz at the end automatically gzips the file,
#making it faster and smaller
serializeTo = ner-model.ser.gz
#structure of your training file; this tells the classifier
#that the word is in column 0 and the correct answer is in
#column 1
map = word=0,answer=1
#these are the features we'd like to train with
#some are discussed below, the rest can be
#understood by looking at NERFeatureFactory
useClassFeature=true
useWord=true
useNGrams=true
#no ngrams will be included that do not contain either the
#beginning or end of the word
noMidNGrams=true
useDisjunctive=true
maxNGramLeng=6
usePrev=true
useNext=true
useSequences=true
usePrevSequences=true
maxLeft=1
#the next 4 deal with word shape features
useTypeSeqs=true
useTypeSeqs2=true
useTypeySequences=true
wordShape=chris2useLC

我以编程方式训练了斯坦福NER系统，但没有模型文件ner-model.ser.gz。

但是当我直接使用 crf 进行分类时，它有效。

Answer 1

你需要在 crf.train(( 之后的这行代码

crf.serializeClassifier("path/to/model.ser.gz");