de.tudarmstadt.ukp.csniper.ml.TKSVMlightFeatureExtractor.java Source code

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Here is the source code for de.tudarmstadt.ukp.csniper.ml.TKSVMlightFeatureExtractor.java

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/*******************************************************************************
 * Copyright 2013
 * Ubiquitous Knowledge Processing (UKP) Lab
 * Technische Universitt 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.csniper.ml;

import java.util.Collection;

import org.apache.commons.lang.StringUtils;
import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
import org.apache.uima.jcas.JCas;
import org.cleartk.classifier.CleartkAnnotator;
import org.cleartk.classifier.CleartkProcessingException;
import org.cleartk.classifier.Feature;
import org.cleartk.classifier.Instance;
import org.apache.uima.fit.util.JCasUtil;

import de.tudarmstadt.ukp.csniper.ml.type.BooleanClassification;
import de.tudarmstadt.ukp.dkpro.core.api.syntax.type.PennTree;

public class TKSVMlightFeatureExtractor extends CleartkAnnotator<Boolean> {
    @Override
    public void process(JCas aJCas) throws AnalysisEngineProcessException {
        // create a new instance for each PennTree
        Collection<PennTree> trees = JCasUtil.select(aJCas, PennTree.class);
        for (PennTree t : trees) {
            Instance<Boolean> instance = new Instance<Boolean>();
            instance.add(new Feature("TK_tree", StringUtils.normalizeSpace(t.getPennTree())));

            BooleanClassification bc = JCasUtil.selectSingle(aJCas, BooleanClassification.class);
            instance.setOutcome(bc.getExpectedLabel());

            train(instance);
        }
        if (trees.size() == 0) {
            getLogger().warn("No PennTree found: " + aJCas.getDocumentText());
        }
        if (trees.size() > 1) {
            getLogger().warn("Too many [" + trees.size() + "] PennTrees found: " + aJCas.getDocumentText());
        }
    }

    private void train(Instance<Boolean> instance) throws CleartkProcessingException {
        dataWriter.write(instance);
    }
}