opennlp.tools.util.featuregen.BrownBigramFeatureGenerator Maven / Gradle / Ivy
/*
* 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.util.featuregen;
import java.util.List;
/**
* Generates Brown cluster features for token bigrams.
*/
public class BrownBigramFeatureGenerator implements AdaptiveFeatureGenerator {
private BrownCluster brownLexicon;
public BrownBigramFeatureGenerator(BrownCluster dict){
this.brownLexicon = dict;
}
public void createFeatures(List features, String[] tokens, int index,
String[] previousOutcomes) {
List wordClasses = BrownTokenClasses.getWordClasses(tokens[index], brownLexicon);
if (index > 0) {
List prevWordClasses = BrownTokenClasses.getWordClasses(tokens[index - 1], brownLexicon);
for (int i = 0; i < wordClasses.size() && i < prevWordClasses.size(); i++)
features.add("p" + "browncluster" + "," + "browncluster" + "=" + prevWordClasses.get(i) + "," + wordClasses.get(i));
}
if (index + 1 < tokens.length) {
List nextWordClasses = BrownTokenClasses.getWordClasses(tokens[index + 1], brownLexicon);
for (int i = 0; i < wordClasses.size() && i < nextWordClasses.size(); i++) {
features.add("browncluster" + "," + "n" + "browncluster" + "=" + wordClasses.get(i) + "," + nextWordClasses.get(i));
}
}
}
}