opennlp.tools.cmdline.parser.BuildModelUpdaterTool 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 org.slf4j.Logger;
import org.slf4j.LoggerFactory;
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;
public final class BuildModelUpdaterTool extends ModelUpdaterTool {
private static final Logger logger = LoggerFactory.getLogger(BuildModelUpdaterTool.class);
public String getShortDescription() {
return "Trains and updates the build 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: training individual models should be in the chunking parser, not here
// Training build
logger.info("Training builder");
ObjectStream bes = new ParserEventStream(parseSamples,
originalModel.getHeadRules(), ParserEventTypeEnum.BUILD, mdict);
EventTrainer trainer = TrainerFactory.getEventTrainer(
ModelUtil.createDefaultTrainingParameters(), null);
MaxentModel buildModel = trainer.train(bes);
parseSamples.close();
return originalModel.updateBuildModel(buildModel);
}
}