opennlp-wsd/src/test/java/opennlp/tools/disambiguator/OSCCTester.java

/*
 * 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.tools.disambiguator;

import java.io.File;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

import opennlp.tools.disambiguator.datareader.SemcorReaderExtended;
import opennlp.tools.disambiguator.oscc.OSCCFactory;
import opennlp.tools.disambiguator.oscc.OSCCME;
import opennlp.tools.disambiguator.oscc.OSCCModel;
import opennlp.tools.disambiguator.oscc.OSCCParameters;
import opennlp.tools.util.ObjectStream;
import opennlp.tools.util.Span;
import opennlp.tools.util.TrainingParameters;

public class OSCCTester {

  public static void main(String[] args) {

    SemcorReaderExtended sr = new SemcorReaderExtended();

    String modelsDir = "src\\test\\resources\\models\\";
    WSDHelper.loadTokenizer(modelsDir + "en-token.bin");
    WSDHelper.loadLemmatizer(modelsDir + "en-lemmatizer.dict");
    WSDHelper.loadTagger(modelsDir + "en-pos-maxent.bin");

    String test = "write.v";
    TrainingParameters trainingParams = new TrainingParameters();
    OSCCParameters OSCCParams = new OSCCParameters("");
    OSCCFactory OSCCFactory = new OSCCFactory();

    ObjectStream<WSDSample> sampleStream = sr.getSemcorDataStream(test);

    OSCCModel model = null;
    OSCCModel readModel = null;
    try {
      model = OSCCME.train("en", sampleStream, trainingParams, OSCCParams,
          OSCCFactory);
      model.writeModel(test);
      File outFile = new File(test + ".OSCC.model");
      readModel = new OSCCModel(outFile);

    } catch (IOException e1) {
      // TODO Auto-generated catch block
      e1.printStackTrace();
    }
    OSCCME OSCC = new OSCCME(readModel, OSCCParams);

    /**
     * This is how to make the context for one-word-disambiguation using OSCC
     */
    String test1 = "We need to discuss important topic, please write to me soon.";
    String[] sentence1 = WSDHelper.getTokenizer().tokenize(test1);
    String[] tags1 = WSDHelper.getTagger().tag(sentence1);
    List<String> tempLemmas1 = new ArrayList<String>();
    for (int i = 0; i < sentence1.length; i++) {
      String lemma = WSDHelper.getLemmatizer()
          .lemmatize(sentence1[i], tags1[i]);
      tempLemmas1.add(lemma);
    }
    String[] lemmas1 = tempLemmas1.toArray(new String[tempLemmas1.size()]);

    // output
    String[] senses1 = OSCC.disambiguate(sentence1, tags1, lemmas1, 8);
    System.out.print(lemmas1[8] + " :\t");
    WSDHelper.print(senses1);
    WSDHelper.print("*****************************");

    /**
     * This is how to make the context for disambiguation of span of words
     */
    String test2 = "The component was highly radioactive to the point that"
        + " it has been activated the second it touched water";
    String[] sentence2 = WSDHelper.getTokenizer().tokenize(test2);
    String[] tags2 = WSDHelper.getTagger().tag(sentence2);
    List<String> tempLemmas2 = new ArrayList<String>();
    for (int i = 0; i < sentence2.length; i++) {
      String lemma = WSDHelper.getLemmatizer()
          .lemmatize(sentence2[i], tags2[i]);
      tempLemmas2.add(lemma);
    }
    String[] lemmas2 = tempLemmas2.toArray(new String[tempLemmas2.size()]);
    Span span = new Span(3, 7);

    // output
    List<String[]> senses2 = OSCC.disambiguate(sentence2, tags2, lemmas2, span);
    for (int i = span.getStart(); i < span.getEnd() + 1; i++) {
      String[] senses = senses2.get(i - span.getStart());
      System.out.print(lemmas2[i] + " :\t");
      WSDHelper.print(senses);
      WSDHelper.print("----------");
    }

    WSDHelper.print("*****************************");
  }
}