/* * 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()); } } } }