Added German NER

pom.xml

@@ -85,6 +85,12 @@
 			<version>3.9.1</version>
 			<classifier>models</classifier> <!-- will get the dependent model jars -->
 		</dependency>
+		<dependency>
+			<groupId>edu.stanford.nlp</groupId>
+			<artifactId>stanford-corenlp</artifactId>
+			<version>3.9.1</version>
+			<classifier>models-german</classifier> <!-- will get the dependent model jars -->
+		</dependency>
 		<dependency>
 			<groupId>org.apache.opennlp</groupId>
 			<artifactId>opennlp-tools</artifactId>

src/main/java/org/tmms/classification/resources/NamedEntityRecognitionResource.java

 package org.tmms.classification.resources;
 
+import java.util.ArrayList;
 import java.util.List;
 import java.util.Optional;
+import java.util.Properties;
 import java.util.concurrent.atomic.AtomicLong;
 
 import javax.ws.rs.GET;
@@ -16,6 +18,14 @@ import org.tmms.classification.db.NamedEntityRecognitionDAO;
 
 import com.codahale.metrics.annotation.Timed;
 
+import edu.stanford.nlp.io.IOUtils;
+import edu.stanford.nlp.ling.CoreAnnotations;
+import edu.stanford.nlp.pipeline.*;
+import edu.stanford.nlp.simple.*;
+import edu.stanford.nlp.trees.*;
+import edu.stanford.nlp.util.CoreMap;
+import edu.stanford.nlp.util.PropertiesUtils;
+import edu.stanford.nlp.util.StringUtils;
 import edu.stanford.nlp.simple.Sentence;
 import io.dropwizard.hibernate.UnitOfWork;
 import io.dropwizard.jersey.params.LongParam;
@@ -44,13 +54,47 @@ public class NamedEntityRecognitionResource {
 	public NamedEntityRecognition analyseNER(
 			@ApiParam(value = "input text data", required = true) @QueryParam("data") String data) {
 
-		Sentence sent = new Sentence(data);
-		List<String> nerTags = sent.nerTags();
+        Properties germanProperties = new Properties();
+        germanProperties.setProperty("annotators", "tokenize,ssplit,pos,lemma,ner");
+        germanProperties.setProperty("tokenize.language", "en");
+        germanProperties.setProperty("ner.applyNumericClassifiers", "false");
+        germanProperties.setProperty("ner.useSUTime", "false");
+        
+        StanfordCoreNLP pipeline = new StanfordCoreNLP(germanProperties);
+        CoreDocument document = new CoreDocument(data);
+        pipeline.annotate(document);
+        List<String> ners = new ArrayList<String>();
+        for (CoreSentence sentence : document.sentences()) {
+        	ners.addAll(sentence.nerTags());
+        }
+		return nerDAO.insert(new NamedEntityRecognition(data, ners.toString()));
+	}
 
-		// String result = classifier.classifyString(data);
+	@GET()
+	@Path("/de")
+	@Timed
+	@UnitOfWork
+	@ApiOperation("Returns the Named-Entity-Recognition result of the input text")
+	public NamedEntityRecognition analyseNERde(
+			@ApiParam(value = "input text data", required = true) @QueryParam("data") String data) {
 
-		final String value = nerTags.toString();
-		return nerDAO.insert(new NamedEntityRecognition(data, value));
+        Properties germanProperties = new Properties();
+        germanProperties.setProperty("annotators", "tokenize,ssplit,pos,ner");
+        germanProperties.setProperty("tokenize.language", "de");
+        germanProperties.setProperty("pos.model", "edu/stanford/nlp/models/pos-tagger/german/german-hgc.tagger");
+        germanProperties.setProperty("ner.model", "edu/stanford/nlp/models/ner/german.conll.germeval2014.hgc_175m_600.crf.ser.gz");
+        germanProperties.setProperty("ner.applyNumericClassifiers", "false");
+//        germanProperties.setProperty("ner.applyFineGrained", "false");
+        germanProperties.setProperty("ner.useSUTime", "false");
+        
+        StanfordCoreNLP pipeline = new StanfordCoreNLP(germanProperties);
+        CoreDocument document = new CoreDocument(data);
+        pipeline.annotate(document);
+        List<String> ners = new ArrayList<String>();
+        for (CoreSentence sentence : document.sentences()) {
+        	ners.addAll(sentence.nerTags());
+        }
+		return nerDAO.insert(new NamedEntityRecognition(data, ners.toString()));
 	}
 
 	@GET