diff --git a/opennlp-tools/src/main/java/opennlp/tools/cmdline/namefind/TokenNameFinderTrainerTool.java b/opennlp-tools/src/main/java/opennlp/tools/cmdline/namefind/TokenNameFinderTrainerTool.java
index f3cef4881..095c83e84 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/cmdline/namefind/TokenNameFinderTrainerTool.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/cmdline/namefind/TokenNameFinderTrainerTool.java
@@ -36,7 +36,6 @@
 import opennlp.tools.namefind.TokenNameFinderModel;
 import opennlp.tools.util.InvalidFormatException;
 import opennlp.tools.util.SequenceCodec;
-import opennlp.tools.util.TrainingParameters;
 import opennlp.tools.util.featuregen.GeneratorFactory;
 import opennlp.tools.util.model.ArtifactSerializer;
 import opennlp.tools.util.model.ModelUtil;
@@ -115,7 +114,7 @@ public void run(String format, String[] args) {
 
     mlParams = CmdLineUtil.loadTrainingParameters(params.getParams(), true);
     if (mlParams == null) {
-      mlParams = new TrainingParameters();
+      mlParams = ModelUtil.createDefaultTrainingParameters();
     }
 
     File modelOutFile = params.getModel();
diff --git a/opennlp-tools/src/main/java/opennlp/tools/util/TrainingParameters.java b/opennlp-tools/src/main/java/opennlp/tools/util/TrainingParameters.java
index 6fc351c1f..a1dfd83f3 100644
--- a/opennlp-tools/src/main/java/opennlp/tools/util/TrainingParameters.java
+++ b/opennlp-tools/src/main/java/opennlp/tools/util/TrainingParameters.java
@@ -27,6 +27,7 @@
 import java.util.Properties;
 
 import opennlp.tools.ml.EventTrainer;
+import opennlp.tools.ml.maxent.GISTrainer;
 
 public class TrainingParameters {
 
@@ -443,7 +444,7 @@ public boolean getBooleanParameter(String namespace, String key, boolean default
   
   public static TrainingParameters defaultParams() {
     TrainingParameters mlParams = new TrainingParameters();
-    mlParams.put(TrainingParameters.ALGORITHM_PARAM, "MAXENT");
+    mlParams.put(TrainingParameters.ALGORITHM_PARAM, GISTrainer.MAXENT_VALUE);
     mlParams.put(TrainingParameters.TRAINER_TYPE_PARAM, EventTrainer.EVENT_VALUE);
     mlParams.put(TrainingParameters.ITERATIONS_PARAM, 100);
     mlParams.put(TrainingParameters.CUTOFF_PARAM, 5);