/*
* 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;
import static org.junit.Assert.assertEquals;
import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.util.ArrayList;
import java.util.List;
import opennlp.model.AbstractModel;
import opennlp.model.Event;
import opennlp.model.EventStream;
import opennlp.model.ListEventStream;
import opennlp.perceptron.PerceptronPrepAttachTest;
public class PrepAttachDataUtil {
private static List<Event> readPpaFile(String filename) throws IOException {
List<Event> events = new ArrayList<Event>();
InputStream in = PerceptronPrepAttachTest.class.getResourceAsStream("/data/ppa/" +
filename);
try {
BufferedReader reader = new BufferedReader(new InputStreamReader(in, "UTF-8"));
String line;
while ((line = reader.readLine()) != null) {
String[] items = line.split("\\s+");
String label = items[5];
String[] context = { "verb=" + items[1], "noun=" + items[2],
"prep=" + items[3], "prep_obj=" + items[4] };
events.add(new Event(label, context));
}
}
finally {
in.close();
}
return events;
}
public static EventStream createTrainingStream() throws IOException {
List<Event> trainingEvents = readPpaFile("training");
EventStream trainingStream = new ListEventStream(trainingEvents);
return trainingStream;
}
public static void testModel(AbstractModel model, double expecedAccuracy) throws IOException {
List<Event> devEvents = readPpaFile("devset");
int total = 0;
int correct = 0;
for (Event ev: devEvents) {
String targetLabel = ev.getOutcome();
double[] ocs = model.eval(ev.getContext());
int best = 0;
for (int i=1; i<ocs.length; i++)
if (ocs[i] > ocs[best])
best = i;
String predictedLabel = model.getOutcome(best);
if (targetLabel.equals(predictedLabel))
correct++;
total++;
}
double accuracy = correct/(double)total;
System.out.println("Accuracy on PPA devset: (" + correct + "/" + total + ") " + accuracy);
assertEquals(expecedAccuracy, accuracy, .00001);
}
}