blob: d1a6305bf153f76819e7d5f6c19844c3b7247bf2 [file] [log] [blame]
/*
* 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.lang.jpn;
import java.util.List;
import opennlp.tools.util.featuregen.AdaptiveFeatureGenerator;
public class BigramNameFeatureGenerator implements AdaptiveFeatureGenerator {
public void createFeatures(List<String> features, String[] tokens, int index,
String[] previousOutcomes) {
String wc = FeatureGeneratorUtil.tokenFeature(tokens[index]);
//bi-gram features
if (index > 0) {
features.add("pw,w=" + tokens[index - 1] + "," + tokens[index]);
String pwc = FeatureGeneratorUtil.tokenFeature(tokens[index - 1]);
features.add("pwc,wc=" + pwc + "," + wc);
}
if (index + 1 < tokens.length) {
features.add("w,nw=" + tokens[index] + "," + tokens[index + 1]);
String nwc = FeatureGeneratorUtil.tokenFeature(tokens[index + 1]);
features.add("wc,nc=" + wc + "," + nwc);
}
}
}