/* * 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 static org.apache.uima.fit.factory.AnalysisEngineFactory.createEngineDescription; import static org.apache.uima.fit.util.JCasUtil.select; import org.apache.uima.analysis_engine.AnalysisEngineDescription; import org.apache.uima.jcas.JCas; import org.junit.Assume; import org.junit.Rule; import org.junit.Test; import de.tudarmstadt.ukp.dkpro.core.api.ner.type.NamedEntity; import de.tudarmstadt.ukp.dkpro.core.testing.AssertAnnotations; import de.tudarmstadt.ukp.dkpro.core.testing.DkproTestContext; import de.tudarmstadt.ukp.dkpro.core.testing.TestRunner; public class Nlp4JNamedEntityRecognizerTest { @Test public void testEnglish() throws Exception { long maxMemory = Runtime.getRuntime().maxMemory(); Assume.assumeTrue("Insufficient max memory: " + maxMemory, maxMemory > 3700000000l); // Run the test pipeline. Note the full stop at the end of a sentence is preceded by a // whitespace. This is necessary for it to be detected as a separate token! JCas jcas = runTest("en", null, "SAP where John Doe works is in Germany ."); // Define the reference data that we expect to get back from the test String[] namedEntity = { "[ 10, 18]NamedEntity(PERSON) (John Doe)", "[ 31, 38]NamedEntity(GPE) (Germany)" }; // Compare the annotations created in the pipeline to the reference data AssertAnnotations.assertNamedEntity(namedEntity, select(jcas, NamedEntity.class)); } // Auxiliary method that sets up the analysis engine or pipeline used in the test. // Typically, we have multiple tests per unit test file that each invoke this method. private JCas runTest(String language, String variant, String testDocument) throws Exception { AnalysisEngineDescription postagger = createEngineDescription(Nlp4JPosTagger.class); AnalysisEngineDescription lemmatizer = createEngineDescription(Nlp4JLemmatizer.class); AnalysisEngineDescription ner = createEngineDescription(Nlp4JNamedEntityRecognizer.class, Nlp4JNamedEntityRecognizer.PARAM_VARIANT, variant, Nlp4JNamedEntityRecognizer.PARAM_PRINT_TAGSET, true); AnalysisEngineDescription engine = createEngineDescription(postagger, lemmatizer, ner); // Here we invoke the TestRunner which performs basic whitespace tokenization and // sentence splitting, creates a CAS, runs the pipeline, etc. TestRunner explicitly // disables automatic model loading. Thus, models used in unit tests must be explicitly // made dependencies in the pom.xml file. return TestRunner.runTest(engine, language, testDocument); } @Rule public DkproTestContext testContext = new DkproTestContext();}