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/*
* 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.util.ArrayList;
import opennlp.tools.disambiguator.datareader.SensevalReader;
import opennlp.tools.disambiguator.MFS;
import org.junit.Test;
public class MFSEvaluatorTest {
static SensevalReader seReader = new SensevalReader();
@Test
public static void main(String[] args) {
WSDHelper.print("Evaluation Started");
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");
MFS mfs = new MFS();
ArrayList<String> words = seReader.getSensevalWords();
for (String word : words) {
WSDEvaluator evaluator = new WSDEvaluator(mfs);
// don't take verbs because they are not from WordNet
if (!word.split("\\.")[1].equals("v")) {
ArrayList<WSDSample> instances = seReader.getSensevalData(word);
if (instances != null) {
WSDHelper.print("------------------" + word + "------------------");
for (WSDSample instance : instances) {
if (instance.getSenseIDs() != null
&& !instance.getSenseIDs()[0].equals("null")) {
evaluator.evaluateSample(instance);
}
}
WSDHelper.print(evaluator.toString());
} else {
WSDHelper.print("null instances");
}
}
}
}
}