使用.prop文件的NER编程训练

Question

我一直在使用属性文件来训练我的ner模型，如本教程LINK中所示。我使用的是相同的prop文件，但是当我不了解如何以编程方式进行操作时。

props.setProperty("annotators", "tokenize, ssplit, pos, lemma, ner, parse, sentiment, regexner");
props.setProperty("ner.model", "resources/NER.prop");

prop文件如下所示：

# location of the training file
trainFile = nerTEST.tsv
# location where you would like to save (serialize) your
# classifier; adding .gz at the end automatically gzips the file,
# making it smaller, and faster to load
serializeTo = resources/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

# This specifies the order of the CRF: order 1 means that features
# apply at most to a class pair of previous class and current class
# or current class and next class.
maxLeft=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
# word character ngrams will be included up to length 6 as prefixes
# and suffixes only
useNGrams=true
noMidNGrams=true
maxNGramLeng=6
usePrev=true
useNext=true
useDisjunctive=true
useSequences=true
usePrevSequences=true
# the last 4 properties deal with word shape features
useTypeSeqs=true
useTypeSeqs2=true
useTypeySequences=true
wordShape=chris2useLC

错误：

 java.io.StreamCorruptedException: invalid stream header: 23206C6F
....
..
Caused by: java.io.IOException: Couldn't load classifier from resources/NER.prop

[关于SO的另一个问题，我了解您直接提供了模型文件。但是，如何在属性文件的帮助下做到这一点？

Answer 1

您应从命令行运行此命令：

java -cp "*" edu.stanford.nlp.ie.crf.CRFClassifier -prop NER.prop

如果要在Java代码中运行此代码，则可以执行以下操作：

String[] args = new String[]{"-props", "NER.prop"};
CRFClassifier.main(args);

。prop文件是指定用于训练模型的设置的文件。您的代码正试图将.prop文件作为模型本身加载，这会导致错误。

执行任何一项操作都会在resources / ner-model.ser.gz中生成最终模型

Answer 2

public class TrainModel {
private void trainCrf(String serializeFile, String prop) {
    Properties props = StringUtils.propFileToProperties(prop);
    props.setProperty("serializeTo", serializeFile);
    SeqClassifierFlags flags = new SeqClassifierFlags(props);
    CRFClassifier<CoreLabel> crf = new CRFClassifier<>(flags);
    crf.train();
    crf.serializeClassifier(serializeFile);
}

public static void main(String[] args) {

    String serializeFile = "skill/ner-model.ser.gz";
    String prop = "ner.props";
    TrainModel trainModel = new TrainModel();
    trainModel.trainCrf(serializeFile, prop);
}

}