/*
* 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.nlp4j;
import java.util.List;
import org.junit.Test;
import edu.emory.mathcs.nlp.component.tokenizer.EnglishTokenizer;
import edu.emory.mathcs.nlp.component.tokenizer.Tokenizer;
import edu.emory.mathcs.nlp.component.tokenizer.token.Token;
public class EnglishTokenizerTest
{
@Test
public void test() {
Tokenizer tokenizer = new EnglishTokenizer();
List<List<Token>> sentences = tokenizer.segmentize("A a a a . B b b b -");
for (List<Token> sentence : sentences) {
for (Token token : sentence) {
System.out.printf("%d %d %s%n", token.getStartOffset(), token.getEndOffset(),
token.getWordForm());
}
}
}
}