/*
* Copyright 2016
* Ubiquitous Knowledge Processing (UKP) Lab
* Technische Universität Darmstadt
*
* Licensed 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 de.tudarmstadt.ukp.dkpro.core.opennlp;
import static org.apache.uima.fit.factory.AnalysisEngineFactory.createEngineDescription;
import static org.apache.uima.fit.factory.CollectionReaderFactory.createReaderDescription;
import static org.apache.uima.fit.pipeline.SimplePipeline.iteratePipeline;
import static org.apache.uima.fit.util.JCasUtil.select;
import static org.junit.Assert.assertEquals;
import java.io.File;
import java.io.IOException;
import java.util.List;
import org.apache.uima.analysis_engine.AnalysisEngineDescription;
import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
import org.apache.uima.collection.CollectionReaderDescription;
import org.apache.uima.fit.component.JCasAnnotator_ImplBase;
import org.apache.uima.fit.pipeline.SimplePipeline;
import org.apache.uima.jcas.JCas;
import org.junit.Before;
import org.junit.Rule;
import org.junit.Test;
import de.tudarmstadt.ukp.dkpro.core.api.datasets.Dataset;
import de.tudarmstadt.ukp.dkpro.core.api.datasets.DatasetFactory;
import de.tudarmstadt.ukp.dkpro.core.api.datasets.Split;
import de.tudarmstadt.ukp.dkpro.core.api.segmentation.type.Sentence;
import de.tudarmstadt.ukp.dkpro.core.eval.EvalUtil;
import de.tudarmstadt.ukp.dkpro.core.eval.model.Span;
import de.tudarmstadt.ukp.dkpro.core.eval.report.Result;
import de.tudarmstadt.ukp.dkpro.core.io.conll.Conll2002Reader;
import de.tudarmstadt.ukp.dkpro.core.testing.DkproTestContext;
public class OpenNlpSentenceTrainerTest
{
private Dataset ds;
@Test
public void test()
throws Exception
{
File targetFolder = testContext.getTestOutputFolder();
Split split = ds.getDefaultSplit();
// Train model
System.out.println("Training model from training data");
CollectionReaderDescription trainReader = createReaderDescription(
Conll2002Reader.class,
Conll2002Reader.PARAM_PATTERNS, split.getTrainingFiles(),
Conll2002Reader.PARAM_LANGUAGE, ds.getLanguage(),
Conll2002Reader.PARAM_COLUMN_SEPARATOR, Conll2002Reader.ColumnSeparators.TAB.getName(),
Conll2002Reader.PARAM_HAS_TOKEN_NUMBER, true,
Conll2002Reader.PARAM_HAS_HEADER, true,
Conll2002Reader.PARAM_HAS_EMBEDDED_NAMED_ENTITY, true);
AnalysisEngineDescription trainer = createEngineDescription(
OpenNlpSentenceTrainer.class,
OpenNlpSentenceTrainer.PARAM_TARGET_LOCATION, new File(targetFolder, "model.bin"),
//OpenNlpSentenceTrainer.PARAM_EOS_CHARACTERS, new char[] { '.', '?' },
OpenNlpSentenceTrainer.PARAM_ABBREVIATION_DICTIONARY_LOCATION,
"src/test/resources/dict/abbreviation_de.txt",
OpenNlpSentenceTrainer.PARAM_LANGUAGE, ds.getLanguage());
SimplePipeline.runPipeline(trainReader, trainer);
// Apply model and collect labels
System.out.println("Applying model to test data");
CollectionReaderDescription testReader = createReaderDescription(
Conll2002Reader.class,
Conll2002Reader.PARAM_PATTERNS, split.getTestFiles(),
Conll2002Reader.PARAM_LANGUAGE, ds.getLanguage(),
Conll2002Reader.PARAM_COLUMN_SEPARATOR, Conll2002Reader.ColumnSeparators.TAB.getName(),
Conll2002Reader.PARAM_HAS_TOKEN_NUMBER, true,
Conll2002Reader.PARAM_HAS_HEADER, true,
Conll2002Reader.PARAM_HAS_EMBEDDED_NAMED_ENTITY, true);
AnalysisEngineDescription stripper = createEngineDescription(
SentenceStripper.class);
AnalysisEngineDescription segmenter = createEngineDescription(
OpenNlpSegmenter.class,
OpenNlpSegmenter.PARAM_WRITE_TOKEN, false,
OpenNlpSegmenter.PARAM_SEGMENTATION_MODEL_LOCATION, new File(targetFolder, "model.bin"));
List<Span<String>> actual = EvalUtil.loadSamples(
iteratePipeline(testReader, stripper, segmenter), Sentence.class, null);
System.out.printf("Actual samples: %d%n", actual.size());
// Read reference data collect labels
List<Span<String>> expected = EvalUtil.loadSamples(testReader, Sentence.class, null);
System.out.printf("Expected samples: %d%n", expected.size());
Result results = EvalUtil.dumpResults(targetFolder, expected, actual);
assertEquals(0.937518, results.getFscore(), 0.0001);
assertEquals(0.932157, results.getPrecision(), 0.0001);
assertEquals(0.942941, results.getRecall(), 0.0001);
}
public static class SentenceStripper
extends JCasAnnotator_ImplBase
{
@Override
public void process(JCas aJCas)
throws AnalysisEngineProcessException
{
for (Sentence s : select(aJCas, Sentence.class)) {
s.removeFromIndexes();
}
}
}
@Before
public void setup() throws IOException
{
DatasetFactory loader = new DatasetFactory(testContext.getCacheFolder());
ds = loader.load("germeval2014-de");
}
@Rule
public DkproTestContext testContext = new DkproTestContext();
}