Package opennlp.uima.postag

Source Code of opennlp.uima.postag.POSTaggerTrainer

/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements.  See the NOTICE file distributed with
* 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
* the License. You may obtain a copy of the License at
*
*     http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

package opennlp.uima.postag;

import java.io.BufferedReader;
import java.io.File;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;

import opennlp.maxent.GIS;
import opennlp.tools.postag.POSDictionary;
import opennlp.tools.postag.POSModel;
import opennlp.tools.postag.POSSample;
import opennlp.tools.postag.POSTaggerME;
import opennlp.tools.util.ObjectStreamUtils;
import opennlp.tools.util.model.ModelType;
import opennlp.uima.util.AnnotatorUtil;
import opennlp.uima.util.CasConsumerUtil;
import opennlp.uima.util.ContainingConstraint;
import opennlp.uima.util.OpennlpUtil;
import opennlp.uima.util.UimaUtil;

import org.apache.uima.UimaContext;
import org.apache.uima.cas.CAS;
import org.apache.uima.cas.FSIndex;
import org.apache.uima.cas.Feature;
import org.apache.uima.cas.Type;
import org.apache.uima.cas.TypeSystem;
import org.apache.uima.cas.text.AnnotationFS;
import org.apache.uima.collection.CasConsumer_ImplBase;
import org.apache.uima.resource.ResourceInitializationException;
import org.apache.uima.resource.ResourceProcessException;
import org.apache.uima.util.Level;
import org.apache.uima.util.Logger;
import org.apache.uima.util.ProcessTrace;

/**
* OpenNLP POSTagger trainer.
* <p>
* Mandatory parameters
* <table border=1>
*   <tr><th>Type</th> <th>Name</th> <th>Description</th></tr>
*   <tr><td>String</td> <td>opennlp.uima.ModelName</td> <td>The name of the model file</td></tr>
*   <tr><td>String</td> <td>opennlp.uima.SentenceType</td> <td>The full name of the sentence type</td></tr>
*   <tr><td>String</td> <td>opennlp.uima.TokenType</td> <td>The full name of the token type</td></tr>
*   <tr><td>String</td> <td>pennlp.uima.POSFeature</td> <td>The name of the token pos feature,
*       the feature must be of type String</td></tr>
*   <tr><td>String</td> <td>opennlp.uima.TagDictionaryName</td></tr>
* </table>
*/
public class POSTaggerTrainer extends CasConsumer_ImplBase {

  public static final String TAG_DICTIONARY_NAME = "opennlp.uima.TagDictionaryName";
 
  private UimaContext mContext;

  private Type mSentenceType;

  private Type mTokenType;

  private String mModelName;

  private Feature mPOSFeature;
 
  private Logger mLogger;
 
  private List<POSSample> mPOSSamples = new ArrayList<POSSample>();
 
  private String language;
 
  private POSDictionary tagDictionary;
 
  /**
   * Initializes the current instance.
   */
  public void initialize() throws ResourceInitializationException {
   
    super.initialize();
   
    mContext = getUimaContext();
   
    mLogger = mContext.getLogger();
   
    if (mLogger.isLoggable(Level.INFO)) {
      mLogger.log(Level.INFO, "Initializing the OpenNLP " +
          "POSTagger trainer.");
    }
   
    mModelName = CasConsumerUtil.getRequiredStringParameter(mContext,
        UimaUtil.MODEL_PARAMETER);
   
    language = CasConsumerUtil.getRequiredStringParameter(mContext,
        UimaUtil.LANGUAGE_PARAMETER);
   
    String tagDictionaryName = CasConsumerUtil.getOptionalStringParameter(mContext,
        TAG_DICTIONARY_NAME);

    if (tagDictionaryName != null) {
      try {
        InputStream dictIn = AnnotatorUtil.getResourceAsStream(mContext, tagDictionaryName);

        // TODO: ask Tom if case sensitivity must be configureable
        tagDictionary = new POSDictionary(new BufferedReader(new InputStreamReader(dictIn)), false);

      } catch (final IOException e) {
        // if this fails just print error message and continue
        final String message = "IOException during tag dictionary reading, "
            + "running without tag dictionary: " + e.getMessage();

        if (this.mLogger.isLoggable(Level.WARNING)) {
          this.mLogger.log(Level.WARNING, message);
        }
      }
    }
  } 
 
  /**
   * Initialize the current instance with the given type system.
   */
  public void typeSystemInit(TypeSystem typeSystem)
      throws ResourceInitializationException {
    String sentenceTypeName = CasConsumerUtil.getRequiredStringParameter(mContext,
        UimaUtil.SENTENCE_TYPE_PARAMETER);
   
    if (mLogger.isLoggable(Level.INFO)) {
      mLogger.log(Level.INFO, UimaUtil.SENTENCE_TYPE_PARAMETER + ": " +
          sentenceTypeName);
    }

    mSentenceType = CasConsumerUtil.getType(typeSystem, sentenceTypeName);

    String tokenTypeName = CasConsumerUtil.getRequiredStringParameter(mContext,
        UimaUtil.TOKEN_TYPE_PARAMETER);
   
    mTokenType = CasConsumerUtil.getType(typeSystem, tokenTypeName);
   
    String posFeatureName = CasConsumerUtil.getRequiredStringParameter(mContext,
        UimaUtil.POS_FEATURE_PARAMETER);
   
    mPOSFeature = mTokenType.getFeatureByBaseName(posFeatureName);
  }
 
  /**
   * Process the given CAS object.
   */
  public void processCas(CAS cas) {

    FSIndex<AnnotationFS> sentenceAnnotations = cas.getAnnotationIndex(mSentenceType);

    for (AnnotationFS sentence : sentenceAnnotations) {
      process(cas, sentence);
    }
  }
 
  private void process(CAS tcas, AnnotationFS sentence) {
   
    FSIndex<AnnotationFS> allTokens = tcas.getAnnotationIndex(mTokenType);

    ContainingConstraint containingConstraint =
        new ContainingConstraint(sentence);
   
    List<String> tokens = new ArrayList<String>();
    List<String> tags = new ArrayList<String>();
   
    Iterator<AnnotationFS> containingTokens = tcas.createFilteredIterator(
        allTokens.iterator(), containingConstraint);
   
    while (containingTokens.hasNext()) {
     
      AnnotationFS tokenAnnotation = (AnnotationFS) containingTokens.next();
     
      String tag = tokenAnnotation.getFeatureValueAsString(mPOSFeature);
     
      tokens.add(tokenAnnotation.getCoveredText().trim());
      tags.add(tag);
    }
   
    mPOSSamples.add(new POSSample(tokens, tags));
  }
 
  /**
   * Called if the processing is finished, this method
   * does the training.
   */
  public void collectionProcessComplete(ProcessTrace trace)
      throws ResourceProcessException, IOException {
   
    GIS.PRINT_MESSAGES = false;

    POSModel posTaggerModel = POSTaggerME.train(language,
        ObjectStreamUtils.createObjectStream(mPOSSamples),
        ModelType.MAXENT, tagDictionary, null, 100, 5);
   
    // dereference to allow garbage collection
    mPOSSamples = null;
   
    File modelFile = new File(getUimaContextAdmin().getResourceManager()
        .getDataPath() + File.separatorChar + mModelName);

    OpennlpUtil.serialize(posTaggerModel, modelFile);
  }
 
  /**
   * The trainer is not stateless.
   */
  public boolean isStateless() {
    return false;
  }
 
  /**
   * Releases allocated resources.
   */
  public void destroy() {
   // dereference to allow garbage collection
    mPOSSamples = null;
  }
}
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