OpenNLP: обучение пользовательской модели NER для нескольких объектов

Я пытаюсь обучить пользовательскую модель NER для нескольких объектов. Вот пример обучающих данных:

count all <START:item_type> operating tables <END> on the <START:location_id> third <END> <START:location_type> floor <END>
count all <START:item_type> items <END> on the <START:location_id> third <END> <START:location_type> floor <END>
how many <START:item_type> beds <END> are in <START:location_type> room <END> <START:location_id> 2 <END>

Метод NameFinderME.train(.) принимает строковый параметр type. Какая польза от этого параметра? И как я могу обучить модель для нескольких объектов (например, item_type, location_type, location_id в моем случае)

public static void main(String[] args) {
    String trainingDataFile = "/home/OpenNLPTest/lib/training_data.txt";
    String outputModelFile = "/tmp/model.bin";
    String sentence = "how many beds are in the hospital";

    train(trainingDataFile, outputModelFile, "location_type");
    predict(sentence, outputModelFile);
}

private static void train(String trainingDataFile, String outputModelFile, String tagToFind) {
    File inFile = new File(trainingDataFile);
    NameSampleDataStream nss = null;
    try {
        nss = new NameSampleDataStream(new PlainTextByLineStream(new java.io.FileReader(inFile)));
    } catch (Exception e) {}

    TokenNameFinderModel model = null;
    int iterations = 100;
    int cutoff = 5;
    try {
        // Does the 'type' parameter mean the entity type that I am trying to train the model for?
        // What if I need to train for multiple entities?
        model = NameFinderME.train("en", tagToFind, nss, (AdaptiveFeatureGenerator) null, Collections.<String,Object>emptyMap(), iterations, cutoff); 
    } catch(Exception e) {}

    try {
        File outFile = new File(outputModelFile);           
        FileOutputStream outFileStream = new FileOutputStream(outFile);
        model.serialize(outFileStream);
    }
    catch (Exception ex) {}
}

private static void predict(String sentence, String modelFile) throws Exception {
    FileInputStream modelInToken = new FileInputStream("/tmp/en-token.bin");
    TokenizerModel modelToken = new TokenizerModel(modelInToken);
    Tokenizer tokenizer = new TokenizerME(modelToken); 
    String tokens[] = tokenizer.tokenize(sentence);

    FileInputStream modelIn = new FileInputStream(modelFile);

    TokenNameFinderModel model = new TokenNameFinderModel(modelIn);
    NameFinderME nameFinder = new NameFinderME(model);
    Span nameSpans[] = nameFinder.find(tokens);

    double[] spanProbs = nameFinder.probs(nameSpans);

    for( int i = 0; i<nameSpans.length; i++) {
        System.out.println(nameSpans[i]);
    }

}