diff --git a/mallet-addon/LICENSE b/mallet-addon/LICENSE
new file mode 100644
index 0000000..e06d208
--- /dev/null
+++ b/mallet-addon/LICENSE
@@ -0,0 +1,202 @@
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diff --git a/mallet-addon/params/crf-params.txt b/mallet-addon/params/crf-params.txt
new file mode 100644
index 0000000..0a2ace3
--- /dev/null
+++ b/mallet-addon/params/crf-params.txt
@@ -0,0 +1,20 @@
+# 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.
+
+# Sample machine learning properties file
+Algorithm=opennlp.addons.mallet.CRFTrainer
+Cutoff=0
+Iterations=100
+
diff --git a/mallet-addon/params/maxent-params.txt b/mallet-addon/params/maxent-params.txt
new file mode 100644
index 0000000..d8cf288
--- /dev/null
+++ b/mallet-addon/params/maxent-params.txt
@@ -0,0 +1,20 @@
+# 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.
+
+# Sample machine learning properties file
+Algorithm=opennlp.addons.mallet.MaxentTrainer
+Cutoff=0
+Iterations=100
+
diff --git a/mallet-addon/pom.xml b/mallet-addon/pom.xml
new file mode 100644
index 0000000..38f1fc9
--- /dev/null
+++ b/mallet-addon/pom.xml
@@ -0,0 +1,84 @@
+<?xml version="1.0" encoding="UTF-8"?>
+
+<!--
+   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.    
+-->
+
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+	<modelVersion>4.0.0</modelVersion>
+	
+	<groupId>kottmann.opennlp</groupId>
+	<artifactId>mallet-addon</artifactId>
+	<version>1.6.0-SNAPSHOT</version>
+
+	<packaging>jar</packaging>
+	<name>Apache OpenNLP Mallet Addon</name>
+
+	<dependencies>
+		<dependency>
+			<groupId>org.apache.opennlp</groupId>
+			<artifactId>opennlp-tools</artifactId>
+			<version>1.6.0</version>
+		</dependency>
+		
+		<dependency>
+			<groupId>cc.mallet</groupId>
+			<artifactId>mallet</artifactId>
+			<version>2.0.7</version>
+		</dependency>
+	</dependencies>
+
+	<build>
+		<plugins>
+			<plugin>
+				<groupId>org.apache.maven.plugins</groupId>
+				<artifactId>maven-dependency-plugin</artifactId>
+				<version>2.1</version>
+				<executions>
+					<execution>
+						<id>copy-dependencies</id>
+						<phase>package</phase>
+						<goals>
+							<goal>copy-dependencies</goal>
+						</goals>
+						<configuration>
+							<excludeScope>provided</excludeScope>
+							<stripVersion>true</stripVersion>
+						</configuration>
+					</execution>
+				</executions>
+			</plugin>
+			<plugin>
+				<groupId>org.apache.maven.plugins</groupId>
+				<artifactId>maven-compiler-plugin</artifactId>
+				<configuration>
+					<source>1.7</source>
+					<target>1.7</target>
+				</configuration>
+			</plugin>
+			<plugin>
+				<groupId>org.apache.maven.plugins</groupId>
+				<artifactId>maven-surefire-plugin</artifactId>
+				<configuration>
+          				<skipTests>true</skipTests>
+					<argLine>-Xmx512m</argLine>
+				</configuration>
+			</plugin>
+		</plugins>
+	</build>
+</project>
diff --git a/mallet-addon/src/main/java/opennlp/addons/mallet/CRFTrainer.java b/mallet-addon/src/main/java/opennlp/addons/mallet/CRFTrainer.java
new file mode 100644
index 0000000..2980131
--- /dev/null
+++ b/mallet-addon/src/main/java/opennlp/addons/mallet/CRFTrainer.java
@@ -0,0 +1,161 @@
+/*
+ * 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.addons.mallet;
+
+import java.io.IOException;
+import java.util.Map;
+import java.util.regex.Pattern;
+
+import opennlp.tools.ml.AbstractSequenceTrainer;
+import opennlp.tools.ml.model.Event;
+import opennlp.tools.ml.model.Sequence;
+import opennlp.tools.ml.model.SequenceClassificationModel;
+import opennlp.tools.ml.model.SequenceStream;
+import cc.mallet.fst.CRF;
+import cc.mallet.fst.CRFTrainerByLabelLikelihood;
+import cc.mallet.fst.Transducer;
+import cc.mallet.types.Alphabet;
+import cc.mallet.types.FeatureVector;
+import cc.mallet.types.FeatureVectorSequence;
+import cc.mallet.types.Instance;
+import cc.mallet.types.InstanceList;
+import cc.mallet.types.Label;
+import cc.mallet.types.LabelAlphabet;
+import cc.mallet.types.LabelSequence;
+
+// Transducer should be abstract, we have two CRF and HMM.
+// For HMM we don't need to generate any features (how to do that nicely?!)
+// Dummy feature generator ?!
+public class CRFTrainer extends AbstractSequenceTrainer {
+
+  public CRFTrainer(Map<String, String> trainParams,
+      Map<String, String> reportMap) {
+    super(trainParams, reportMap);
+  }
+
+  private int[] getOrders() {
+    String[] ordersString = "0,1".split(",");
+    int[] orders = new int[ordersString.length];
+    for (int i = 0; i < ordersString.length; i++) {
+      orders[i] = Integer.parseInt(ordersString[i]);
+      System.err.println("Orders: " + orders[i]);
+    }
+    return orders;
+  }
+
+  // TODO: Interface has to be changed here,
+  @Override
+  public SequenceClassificationModel<String> doTrain(SequenceStream sequences)
+      throws IOException {
+
+    Alphabet dataAlphabet = new Alphabet();
+    LabelAlphabet targetAlphabet = new LabelAlphabet();
+
+    InstanceList trainingData = new InstanceList(dataAlphabet, targetAlphabet);
+
+    int nameIndex = 0;
+    for (Sequence sequence : sequences) {
+      FeatureVector featureVectors[] = new FeatureVector[sequence.getEvents().length];
+      Label malletOutcomes[] = new Label[sequence.getEvents().length];
+
+      Event events[] = sequence.getEvents();
+
+      for (int eventIndex = 0; eventIndex < events.length; eventIndex++) {
+
+        Event event = events[eventIndex];
+
+        String features[] = event.getContext();
+        int malletFeatures[] = new int[features.length];
+
+        for (int featureIndex = 0; featureIndex < features.length; featureIndex++) {
+          malletFeatures[featureIndex] = dataAlphabet.lookupIndex(
+              features[featureIndex], true);
+        }
+
+        // Note: Might contain a feature more than once ... will that
+        // work ?!
+        featureVectors[eventIndex] = new FeatureVector(dataAlphabet,
+            malletFeatures);
+
+        malletOutcomes[eventIndex] = targetAlphabet.lookupLabel(
+            event.getOutcome(), true);
+      }
+
+      LabelSequence malletOutcomeSequence = new LabelSequence(malletOutcomes);
+
+      FeatureVectorSequence malletSequence = new FeatureVectorSequence(
+          featureVectors);
+
+      trainingData.add(new Instance(malletSequence, malletOutcomeSequence,
+          "name" + nameIndex++, "source"));
+    }
+
+    CRF crf = new CRF(trainingData.getDataAlphabet(),
+        trainingData.getTargetAlphabet());
+
+    String startStateName = crf.addOrderNStates(trainingData, getOrders(),
+        (boolean[]) null,
+        // default label
+        "other", Pattern.compile("other,*-cont"), // forbidden pattern
+        null, // allowed pattern
+        true);
+    crf.getState(startStateName).setInitialWeight(0.0);
+
+    for (int i = 0; i < crf.numStates(); i++) {
+      crf.getState(i).setInitialWeight(Transducer.IMPOSSIBLE_WEIGHT);
+    }
+
+    crf.getState(startStateName).setInitialWeight(0.0);
+    crf.setWeightsDimensionAsIn(trainingData, true);
+
+    // CRFOptimizableBy* objects (terms in the objective function)
+    // objective 1: label likelihood objective
+
+    CRFTrainerByLabelLikelihood crfTrainer = new CRFTrainerByLabelLikelihood(
+        crf);
+    crfTrainer.setGaussianPriorVariance(1.0);
+
+    // CRFOptimizableByLabelLikelihood optLabel = new
+    // CRFOptimizableByLabelLikelihood(
+    // crf, trainingData);
+
+    // CRF trainer
+    // Optimizable.ByGradientValue[] opts = new Optimizable.ByGradientValue[] {
+    // optLabel };
+
+    // by default, use L-BFGS as the optimizer
+    // CRFTrainerByValueGradients crfTrainer = new CRFTrainerByValueGradients(
+    // crf, opts);
+    // crfTrainer.setMaxResets(0);
+
+    // SNIP
+
+    crfTrainer.train(trainingData, Integer.MAX_VALUE);
+
+    // can be very similar to the other model
+    // one important difference is that the feature gen needs to be integrated
+    // ...
+    return new TransducerModel(crf);
+  }
+
+  // TODO: We need to return a sequence model here. How should that be done ?!
+  //
+
+}
diff --git a/mallet-addon/src/main/java/opennlp/addons/mallet/ClassifierModel.java b/mallet-addon/src/main/java/opennlp/addons/mallet/ClassifierModel.java
new file mode 100644
index 0000000..5f6661d
--- /dev/null
+++ b/mallet-addon/src/main/java/opennlp/addons/mallet/ClassifierModel.java
@@ -0,0 +1,129 @@
+/*
+ * 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.addons.mallet;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import opennlp.tools.ml.model.MaxentModel;
+import opennlp.tools.util.model.SerializableArtifact;
+import cc.mallet.classify.Classification;
+import cc.mallet.classify.Classifier;
+import cc.mallet.types.Alphabet;
+import cc.mallet.types.FeatureVector;
+import cc.mallet.types.Instance;
+import cc.mallet.types.Label;
+import cc.mallet.types.LabelAlphabet;
+import cc.mallet.types.LabelVector;
+
+class ClassifierModel implements MaxentModel, SerializableArtifact {
+
+  private Classifier classifer;
+
+  public ClassifierModel(Classifier classifer) {
+    this.classifer = classifer;
+  }
+
+  Classifier getClassifer() {
+    return classifer;
+  }
+  
+  public double[] eval(String[] features) {
+    Alphabet dataAlphabet = classifer.getAlphabet();
+
+    List<Integer> malletFeatureList = new ArrayList<>(features.length);
+
+    for (String feature : features) {
+      int featureId = dataAlphabet.lookupIndex(feature);
+      if (featureId != -1) {
+        malletFeatureList.add(featureId);
+      }
+    }
+
+    int malletFeatures[] = new int[malletFeatureList.size()];
+    for (int i = 0; i < malletFeatureList.size(); i++) {
+      malletFeatures[i] = malletFeatureList.get(i);
+    }
+
+    FeatureVector fv = new FeatureVector(classifer.getAlphabet(),
+        malletFeatures);
+    Instance instance = new Instance(fv, null, null, null);
+
+    Classification result = classifer.classify(instance);
+
+    LabelVector labeling = result.getLabelVector();
+
+    LabelAlphabet targetAlphabet = classifer.getLabelAlphabet();
+
+    double outcomes[] = new double[targetAlphabet.size()];
+    for (int i = 0; i < outcomes.length; i++) {
+
+      Label label = targetAlphabet.lookupLabel(i);
+
+      int rank = labeling.getRank(label);
+      outcomes[i] = labeling.getValueAtRank(rank);
+    }
+
+    return outcomes;
+  }
+
+  public double[] eval(String[] context, double[] probs) {
+    return eval(context);
+  }
+
+  public double[] eval(String[] context, float[] values) {
+    return eval(context);
+  }
+
+  @Override
+  public String getBestOutcome(double[] ocs) {
+    int best = 0;
+    for (int i = 1; i < ocs.length; i++)
+      if (ocs[i] > ocs[best])
+        best = i;
+    
+    return getOutcome(best);
+  }
+
+  @Override
+  public String getAllOutcomes(double[] outcomes) {
+    return null;
+  }
+
+  @Override
+  public String getOutcome(int i) {
+    return classifer.getLabelAlphabet().lookupLabel(i).getEntry().toString();
+  }
+
+  @Override
+  public int getIndex(String outcome) {
+    return classifer.getLabelAlphabet().lookupIndex(outcome);
+  }
+
+  @Override
+  public int getNumOutcomes() {
+    return classifer.getLabelAlphabet().size();
+  }
+
+  @Override
+  public Class<?> getArtifactSerializerClass() {
+    return ClassifierModelSerializer.class;
+  }
+}
diff --git a/mallet-addon/src/main/java/opennlp/addons/mallet/ClassifierModelSerializer.java b/mallet-addon/src/main/java/opennlp/addons/mallet/ClassifierModelSerializer.java
new file mode 100644
index 0000000..9cfb6f2
--- /dev/null
+++ b/mallet-addon/src/main/java/opennlp/addons/mallet/ClassifierModelSerializer.java
@@ -0,0 +1,57 @@
+/*
+ * 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.addons.mallet;
+
+import java.io.IOException;
+import java.io.InputStream;
+import java.io.ObjectInputStream;
+import java.io.ObjectOutputStream;
+import java.io.OutputStream;
+
+import cc.mallet.classify.Classifier;
+import opennlp.tools.util.InvalidFormatException;
+import opennlp.tools.util.model.ArtifactSerializer;
+
+// The standard method for saving classifiers in Mallet is through Java serialization.
+
+public class ClassifierModelSerializer implements
+    ArtifactSerializer<ClassifierModel> {
+
+  @Override
+  public ClassifierModel create(InputStream in) throws IOException,
+      InvalidFormatException {
+
+    ObjectInputStream ois = new ObjectInputStream(in);
+    try {
+      Classifier classifier = (Classifier) ois.readObject();
+      return new ClassifierModel(classifier);
+    } catch (ClassNotFoundException e) {
+      throw new IOException(e);
+    }
+  }
+
+  @Override
+  public void serialize(ClassifierModel artifact, OutputStream out)
+      throws IOException {
+    ObjectOutputStream oos = new ObjectOutputStream(out);
+    oos.writeObject(artifact.getClassifer());
+    oos.flush();
+  }
+}
diff --git a/mallet-addon/src/main/java/opennlp/addons/mallet/MaxentTrainer.java b/mallet-addon/src/main/java/opennlp/addons/mallet/MaxentTrainer.java
new file mode 100644
index 0000000..34f5f7c
--- /dev/null
+++ b/mallet-addon/src/main/java/opennlp/addons/mallet/MaxentTrainer.java
@@ -0,0 +1,95 @@
+/*
+ * 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.addons.mallet;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.Map;
+
+import opennlp.tools.ml.AbstractEventTrainer;
+import opennlp.tools.ml.model.DataIndexer;
+import opennlp.tools.ml.model.MaxentModel;
+import cc.mallet.classify.Classifier;
+import cc.mallet.classify.MaxEntTrainer;
+import cc.mallet.types.Alphabet;
+import cc.mallet.types.FeatureVector;
+import cc.mallet.types.Instance;
+import cc.mallet.types.InstanceList;
+import cc.mallet.types.LabelAlphabet;
+
+public class MaxentTrainer extends AbstractEventTrainer {
+
+  public MaxentTrainer(Map<String, String> trainParams,
+      Map<String, String> reportMap) {
+    super(trainParams, reportMap);
+  }
+
+  @Override
+  public boolean isSortAndMerge() {
+    return true;
+  }
+
+  @Override
+  public MaxentModel doTrain(DataIndexer indexer) throws IOException {
+
+    int numFeatures = indexer.getPredLabels().length;
+
+    Alphabet dataAlphabet = new Alphabet(numFeatures);
+    LabelAlphabet targetAlphabet = new LabelAlphabet();
+
+    Collection<Instance> instances = new ArrayList<>();
+
+    String predLabels[] = indexer.getPredLabels();
+    
+    int outcomes[] = indexer.getOutcomeList();
+    for (int contextIndex = 0; contextIndex < indexer.getContexts().length; contextIndex++) {
+
+      int malletFeatures[] = new int[indexer.getContexts()[contextIndex].length];
+      double weights[] = new double[indexer.getContexts()[contextIndex].length];
+
+      for (int featureIndex = 0; featureIndex < malletFeatures.length; featureIndex++) {
+        malletFeatures[featureIndex] = dataAlphabet.lookupIndex(
+            predLabels[indexer.getContexts()[contextIndex][featureIndex]], true);
+        
+        weights[featureIndex] = indexer.getNumTimesEventsSeen()[contextIndex];
+      }
+
+      FeatureVector fv = new FeatureVector(dataAlphabet, malletFeatures,
+          weights);
+      Instance inst = new Instance(fv, targetAlphabet.lookupLabel(
+          indexer.getOutcomeLabels()[outcomes[contextIndex]], true), "name",
+          "data-indexer");
+      instances.add(inst);
+    }
+
+    InstanceList trainingData = new InstanceList(dataAlphabet, targetAlphabet);
+    Instance inst = instances.iterator().next();
+
+    Alphabet.alphabetsMatch(trainingData, inst);
+    trainingData.addAll(instances);
+
+    MaxEntTrainer trainer = new MaxEntTrainer();
+    
+    Classifier classifier = trainer.train(trainingData);
+
+    return new ClassifierModel(classifier);
+  }
+}
diff --git a/mallet-addon/src/main/java/opennlp/addons/mallet/TransducerModel.java b/mallet-addon/src/main/java/opennlp/addons/mallet/TransducerModel.java
new file mode 100644
index 0000000..52f2ce5
--- /dev/null
+++ b/mallet-addon/src/main/java/opennlp/addons/mallet/TransducerModel.java
@@ -0,0 +1,124 @@
+/*
+ * 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.addons.mallet;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
+
+import opennlp.tools.ml.model.SequenceClassificationModel;
+import opennlp.tools.util.BeamSearchContextGenerator;
+import opennlp.tools.util.SequenceValidator;
+import opennlp.tools.util.model.SerializableArtifact;
+import cc.mallet.fst.CRF;
+import cc.mallet.fst.MaxLatticeDefault;
+import cc.mallet.fst.Transducer;
+import cc.mallet.types.Alphabet;
+import cc.mallet.types.FeatureVector;
+import cc.mallet.types.FeatureVectorSequence;
+import cc.mallet.types.Sequence;
+
+public class TransducerModel<T> implements SequenceClassificationModel<T>, SerializableArtifact {
+
+  private Transducer model;
+
+  public TransducerModel(Transducer model) {
+    this.model = model;
+  }
+  
+  Transducer getModel() {
+    return model;
+  }
+  
+  public opennlp.tools.util.Sequence bestSequence(T[] sequence,
+      Object[] additionalContext, BeamSearchContextGenerator<T> cg,
+      SequenceValidator<T> validator) {
+    return bestSequences(1, sequence, additionalContext, cg, validator)[0];
+  }
+
+  public opennlp.tools.util.Sequence[] bestSequences(int numSequences,
+      T[] sequence, Object[] additionalContext,
+      BeamSearchContextGenerator<T> cg, SequenceValidator<T> validator) {
+
+    // TODO: CRF.getInputAlphabet
+    Alphabet dataAlphabet = model.getInputPipe().getAlphabet();
+    
+    FeatureVector featureVectors[] = new FeatureVector[sequence.length];
+    
+    // TODO:: The feature generator needs to get the detected sequence in the end
+    // to update the adaptive data!
+    String prior[] = new String[sequence.length];
+    Arrays.fill(prior, "s"); // <- HACK, this will degrade performance!
+    
+    // TODO: Put together a feature generator which doesn't fail if outcomes is null!
+    for (int i = 0; i < sequence.length; i++) {
+      String features[] = cg.getContext(i, sequence, null, additionalContext);
+      
+      List<Integer> malletFeatureList = new ArrayList<>(features.length);
+      
+      for (int featureIndex = 0; featureIndex < features.length; featureIndex++) {
+        if (dataAlphabet.contains(features[featureIndex])) {
+          malletFeatureList.add(dataAlphabet.lookupIndex(features[featureIndex]));
+        }
+      }
+
+      int malletFeatures[] = new int[malletFeatureList.size()];
+      for (int k = 0; k < malletFeatureList.size(); k++) {
+        malletFeatures[k] = malletFeatureList.get(k);
+      }
+      
+      // Note: Might contain a feature more than once ... will that work ?!
+      featureVectors[i] = new FeatureVector(dataAlphabet, malletFeatures);
+    }
+    
+    FeatureVectorSequence malletSequence = new FeatureVectorSequence(featureVectors);
+    
+    Sequence[] answers = null;
+    if (numSequences == 1) {
+      answers = new Sequence[1];
+      answers[0] = model.transduce(malletSequence);
+    } else {
+      MaxLatticeDefault lattice = new MaxLatticeDefault(model, malletSequence, null, 3);
+
+      answers = lattice.bestOutputSequences(numSequences).toArray(new Sequence[0]);
+    }
+
+    opennlp.tools.util.Sequence[] outcomeSequences = new opennlp.tools.util.Sequence[answers.length];
+    
+    for (int i = 0; i < answers.length; i++) {
+      Sequence seq = answers[i];
+      
+      List<String> outcomes = new ArrayList<>(seq.size());
+      
+      for (int j = 0; j < seq.size(); j++) {
+        outcomes.add(seq.get(j).toString());
+      }
+      
+      outcomeSequences[i] = new opennlp.tools.util.Sequence(outcomes);
+    }
+    
+    return outcomeSequences;
+  }
+
+  @Override
+  public Class<?> getArtifactSerializerClass() {
+    return TransducerModelSerializer.class;
+  }
+}
diff --git a/mallet-addon/src/main/java/opennlp/addons/mallet/TransducerModelSerializer.java b/mallet-addon/src/main/java/opennlp/addons/mallet/TransducerModelSerializer.java
new file mode 100644
index 0000000..b793ca2
--- /dev/null
+++ b/mallet-addon/src/main/java/opennlp/addons/mallet/TransducerModelSerializer.java
@@ -0,0 +1,53 @@
+/*
+ * 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.addons.mallet;
+
+import java.io.IOException;
+import java.io.InputStream;
+import java.io.ObjectInputStream;
+import java.io.ObjectOutputStream;
+import java.io.OutputStream;
+
+import opennlp.tools.util.InvalidFormatException;
+import opennlp.tools.util.model.ArtifactSerializer;
+import cc.mallet.fst.Transducer;
+
+public class TransducerModelSerializer implements ArtifactSerializer<TransducerModel> {
+
+  @Override
+  public TransducerModel create(InputStream in) throws IOException,
+      InvalidFormatException {
+    ObjectInputStream ois = new ObjectInputStream(in);
+    try {
+      Transducer classifier = (Transducer) ois.readObject();
+      return new TransducerModel(classifier);
+    } catch (ClassNotFoundException e) {
+      throw new IOException(e);
+    }
+  }
+
+  @Override
+  public void serialize(TransducerModel artifact, OutputStream out)
+      throws IOException {
+    ObjectOutputStream oos = new ObjectOutputStream(out);
+    oos.writeObject(artifact.getModel());
+    oos.flush();
+  }
+}