diff --git a/.gitignore b/.gitignore
index 77ee74c7e6..78232efd98 100644
--- a/.gitignore
+++ b/.gitignore
@@ -7,3 +7,4 @@ torchtext.egg-info/
 */**/*.pyc
 */**/*~
 *~
+.cache
diff --git a/build_tools/travis/install.sh b/build_tools/travis/install.sh
index 359917658e..c0c92a5284 100644
--- a/build_tools/travis/install.sh
+++ b/build_tools/travis/install.sh
@@ -54,6 +54,10 @@ pip install -r requirements.txt
 if [[ "$SKIP_TESTS" != "true" ]]; then
     # SpaCy English models
     python -m spacy download en
+
+    # NLTK data needed for Moses tokenizer
+    python -m nltk.downloader perluniprops nonbreaking_prefixes
+
     # PyTorch
     conda install --yes pytorch torchvision -c soumith
 fi
diff --git a/test/data/test_field.py b/test/data/test_field.py
index f8bd82785d..8a8d9f1b78 100644
--- a/test/data/test_field.py
+++ b/test/data/test_field.py
@@ -1,6 +1,5 @@
 from unittest import TestCase
 
-import six
 import torchtext.data as data
 
 
@@ -88,20 +87,3 @@ def test_pad(self):
         field = data.Field(init_token="<bos>", eos_token="<eos>",
                            sequential=False, include_lengths=True)
         assert field.pad(minibatch) == minibatch
-
-    def test_get_tokenizer(self):
-        # Test the default case with str.split
-        assert data.get_tokenizer(str.split) == str.split
-        test_str = "A string, particularly one with slightly complex punctuation."
-        assert data.get_tokenizer(str.split)(test_str) == str.split(test_str)
-
-        # Test SpaCy option, and verify it properly handles punctuation.
-        assert data.get_tokenizer("spacy")(six.text_type(test_str)) == [
-            "A", "string", ",", "particularly", "one", "with", "slightly",
-            "complex", "punctuation", "."]
-
-        # Test that errors are raised for invalid input arguments.
-        with self.assertRaises(ValueError):
-            data.get_tokenizer(1)
-        with self.assertRaises(ValueError):
-            data.get_tokenizer("some other string")
diff --git a/test/data/test_utils.py b/test/data/test_utils.py
new file mode 100644
index 0000000000..508b1361df
--- /dev/null
+++ b/test/data/test_utils.py
@@ -0,0 +1,33 @@
+from unittest import TestCase
+
+import six
+import torchtext.data as data
+
+
+class TestUtils(TestCase):
+    def test_get_tokenizer(self):
+        # Test the default case with str.split
+        assert data.get_tokenizer(str.split) == str.split
+        test_str = "A string, particularly one with slightly complex punctuation."
+        assert data.get_tokenizer(str.split)(test_str) == str.split(test_str)
+
+        # Test SpaCy option, and verify it properly handles punctuation.
+        assert data.get_tokenizer("spacy")(six.text_type(test_str)) == [
+            "A", "string", ",", "particularly", "one", "with", "slightly",
+            "complex", "punctuation", "."]
+
+        # Test Moses option. Test strings taken from NLTK doctests.
+        # Note that internally, MosesTokenizer converts to unicode if applicable
+        moses_tokenizer = data.get_tokenizer("moses")
+        assert moses_tokenizer(test_str) == [
+            "A", "string", ",", "particularly", "one", "with", "slightly",
+            "complex", "punctuation", "."]
+
+        # Nonbreaking prefixes should tokenize the final period.
+        assert moses_tokenizer(six.text_type("abc def.")) == ["abc", "def", "."]
+
+        # Test that errors are raised for invalid input arguments.
+        with self.assertRaises(ValueError):
+            data.get_tokenizer(1)
+        with self.assertRaises(ValueError):
+            data.get_tokenizer("some other string")
diff --git a/torchtext/data/example.py b/torchtext/data/example.py
index c5faf73638..4aa9e10e34 100644
--- a/torchtext/data/example.py
+++ b/torchtext/data/example.py
@@ -49,8 +49,8 @@ def fromtree(cls, data, fields, subtrees=False):
         try:
             from nltk.tree import Tree
         except ImportError:
-            print('''Please install NLTK:
-    $ pip install nltk''')
+            print("Please install NLTK. "
+                  "See the docs at http://nltk.org for more information.")
             raise
         tree = Tree.fromstring(data)
         if subtrees:
diff --git a/torchtext/data/utils.py b/torchtext/data/utils.py
index 6703c57421..9aa36a3078 100644
--- a/torchtext/data/utils.py
+++ b/torchtext/data/utils.py
@@ -1,7 +1,7 @@
 def get_tokenizer(tokenizer):
     if callable(tokenizer):
         return tokenizer
-    if tokenizer == 'spacy':
+    if tokenizer == "spacy":
         try:
             import spacy
             spacy_en = spacy.load('en')
@@ -14,10 +14,24 @@ def get_tokenizer(tokenizer):
             print("Please install SpaCy and the SpaCy English tokenizer. "
                   "See the docs at https://spacy.io for more information.")
             raise
+    elif tokenizer == "moses":
+        try:
+            from nltk.tokenize.moses import MosesTokenizer
+            moses_tokenizer = MosesTokenizer()
+            return moses_tokenizer.tokenize
+        except ImportError:
+            print("Please install NLTK. "
+                  "See the docs at http://nltk.org for more information.")
+            raise
+        except LookupError:
+            print("Please install the necessary NLTK corpora. "
+                  "See the docs at http://nltk.org for more information.")
+            raise
     raise ValueError("Requested tokenizer {}, valid choices are a "
-                     "callable that takes a single string as input "
-                     "and \"spacy\" for the SpaCy English "
-                     "tokenizer.".format(tokenizer))
+                     "callable that takes a single string as input, "
+                     "\"spacy\" for the SpaCy English tokenizer, or "
+                     "\"moses\" for the NLTK port of the Moses tokenization "
+                     "script.".format(tokenizer))
 
 
 def interleave_keys(a, b):