content: package zemberek.examples.ner;
  
  import java.io.IOException;
  import java.nio.file.Files;
  import java.nio.file.Path;
  import java.nio.file.Paths;
  import zemberek.core.logging.Log;
  import zemberek.morphology.TurkishMorphology;
  import zemberek.ner.NerDataSet;
  import zemberek.ner.NerDataSet.AnnotationStyle;
  import zemberek.ner.PerceptronNer;
  import zemberek.ner.PerceptronNerTrainer;
  
  /**
   * This example shows how programmatically train NER model.
   * Alternatively, {@link zemberek.apps.ner.TrainNerModel} console application can be used.
   */
  public class GenerateNerModel {
  
    public static void main(String[] args) throws IOException {
  
      // you will need ner-train and ner-test files to run this example.
  
      Path trainPath = Paths.get("ner-train");
      Path testPath = Paths.get("ner-test");
      Path modelRoot = Paths.get("my-model");
  
      NerDataSet trainingSet = NerDataSet.load(trainPath, AnnotationStyle.BRACKET);
      Log.info(trainingSet.info()); // prints information
  
      NerDataSet testSet = NerDataSet.load(testPath, AnnotationStyle.BRACKET);
      Log.info(testSet.info());
  
      TurkishMorphology morphology = TurkishMorphology.createWithDefaults();
  
      // Training occurs here. Result is a PerceptronNer instance.
      // There will be 7 iterations with 0.1 learning rate.
      PerceptronNer ner = new PerceptronNerTrainer(morphology)
          .train(trainingSet, testSet, 13, 0.1f);
  
      Files.createDirectories(modelRoot);
      ner.saveModelAsText(modelRoot);
    }
  
  }
  