opennlp.tools.cmdline.parser.CheckModelUpdaterTool Maven / Gradle / Ivy
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* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
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* http://www.apache.org/licenses/LICENSE-2.0
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package opennlp.tools.cmdline.parser;
import java.io.IOException;
import opennlp.tools.dictionary.Dictionary;
import opennlp.tools.ml.EventTrainer;
import opennlp.tools.ml.TrainerFactory;
import opennlp.tools.ml.model.Event;
import opennlp.tools.ml.model.MaxentModel;
import opennlp.tools.parser.Parse;
import opennlp.tools.parser.ParserEventTypeEnum;
import opennlp.tools.parser.ParserModel;
import opennlp.tools.parser.chunking.ParserEventStream;
import opennlp.tools.util.ObjectStream;
import opennlp.tools.util.model.ModelUtil;
// trains a new check model ...
public final class CheckModelUpdaterTool extends ModelUpdaterTool {
public String getShortDescription() {
return "trains and updates the check model in a parser model";
}
@Override
protected ParserModel trainAndUpdate(ParserModel originalModel,
ObjectStream parseSamples, ModelUpdaterParams parameters)
throws IOException {
Dictionary mdict = ParserTrainerTool.buildDictionary(parseSamples, originalModel.getHeadRules(), 5);
parseSamples.reset();
// TODO: Maybe that should be part of the ChunkingParser ...
// Training build
System.out.println("Training check model");
ObjectStream bes = new ParserEventStream(parseSamples,
originalModel.getHeadRules(), ParserEventTypeEnum.CHECK, mdict);
EventTrainer trainer = TrainerFactory.getEventTrainer(
ModelUtil.createDefaultTrainingParameters(), null);
MaxentModel checkModel = trainer.train(bes);
parseSamples.close();
return originalModel.updateCheckModel(checkModel);
}
}