diff --git a/spacy/language.py b/spacy/language.py
index 39d95c689..bfdd00b79 100644
--- a/spacy/language.py
+++ b/spacy/language.py
@@ -618,7 +618,7 @@ class Language(object):
         if component_cfg is None:
             component_cfg = {}
         docs, golds = zip(*docs_golds)
-        docs = list(docs)
+        docs = [self.make_doc(doc) if isinstance(doc, basestring_) else doc for doc in docs]
         golds = list(golds)
         for name, pipe in self.pipeline:
             kwargs = component_cfg.get(name, {})
@@ -628,6 +628,8 @@ class Language(object):
             else:
                 docs = pipe.pipe(docs, **kwargs)
         for doc, gold in zip(docs, golds):
+            if not isinstance(gold, GoldParse):
+                gold = GoldParse(doc, **gold)
             if verbose:
                 print(doc)
             kwargs = component_cfg.get("scorer", {})
diff --git a/spacy/tests/test_language.py b/spacy/tests/test_language.py
new file mode 100644
index 000000000..00175fe9a
--- /dev/null
+++ b/spacy/tests/test_language.py
@@ -0,0 +1,57 @@
+# coding: utf-8
+from __future__ import unicode_literals
+
+import pytest
+from spacy.vocab import Vocab
+from spacy.language import Language
+from spacy.tokens import Doc
+from spacy.gold import GoldParse
+
+
+@pytest.fixture
+def nlp():
+    nlp = Language(Vocab())
+    textcat = nlp.create_pipe("textcat")
+    for label in ("POSITIVE", "NEGATIVE"):
+        textcat.add_label(label)
+    nlp.add_pipe(textcat)
+    nlp.begin_training()
+    return nlp
+
+
+def test_language_update(nlp):
+    text = "hello world"
+    annots = {"cats": {"POSITIVE": 1.0, "NEGATIVE": 0.0}}
+    doc = Doc(nlp.vocab, words=text.split(" "))
+    gold = GoldParse(doc, **annots)
+    # Update with doc and gold objects
+    nlp.update([doc], [gold])
+    # Update with text and dict
+    nlp.update([text], [annots])
+    # Update with doc object and dict
+    nlp.update([doc], [annots])
+    # Update with text and gold object
+    nlp.update([text], [gold])
+    # Update badly
+    with pytest.raises(IndexError):
+        nlp.update([doc], [])
+    with pytest.raises(IndexError):
+        nlp.update([], [gold])
+
+
+def test_language_evaluate(nlp):
+    text = "hello world"
+    annots = {"cats": {"POSITIVE": 1.0, "NEGATIVE": 0.0}}
+    doc = Doc(nlp.vocab, words=text.split(" "))
+    gold = GoldParse(doc, **annots)
+    # Evaluate with doc and gold objects
+    nlp.evaluate([(doc, gold)])
+    # Evaluate with text and dict
+    nlp.evaluate([(text, annots)])
+    # Evaluate with doc object and dict
+    nlp.evaluate([(doc, annots)])
+    # Evaluate with text and gold object
+    nlp.evaluate([(text, gold)])
+    # Evaluate badly
+    with pytest.raises(Exception):
+        nlp.evaluate([text, gold])
diff --git a/website/docs/api/language.md b/website/docs/api/language.md
index 3245a165b..3fcdeb195 100644
--- a/website/docs/api/language.md
+++ b/website/docs/api/language.md
@@ -133,13 +133,13 @@ Evaluate a model's pipeline components.
 > print(scorer.scores)
 > ```
 
-| Name                                         | Type     | Description                                                                           |
-| -------------------------------------------- | -------- | ------------------------------------------------------------------------------------- |
-| `docs_golds`                                 | iterable | Tuples of `Doc` and `GoldParse` objects.                                              |
-| `verbose`                                    | bool     | Print debugging information.                                                          |
-| `batch_size`                                 | int      | The batch size to use.                                                                |
-| `scorer`                                     | `Scorer` | Optional [`Scorer`](/api/scorer) to use. If not passed in, a new one will be created. |
-| `component_cfg` <Tag variant="new">2.1</Tag> | dict     | Config parameters for specific pipeline components, keyed by component name.          |
+| Name                                         | Type     | Description                                                                                                                                                   |
+| -------------------------------------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `docs_golds`                                 | iterable | Tuples of `Doc` and `GoldParse` objects or `(text, annotations)` of raw text and a dict (see [simple training style](/usage/training#training-simple-style)). |
+| `verbose`                                    | bool     | Print debugging information.                                                                                                                                  |
+| `batch_size`                                 | int      | The batch size to use.                                                                                                                                        |
+| `scorer`                                     | `Scorer` | Optional [`Scorer`](/api/scorer) to use. If not passed in, a new one will be created.                                                                         |
+| `component_cfg` <Tag variant="new">2.1</Tag> | dict     | Config parameters for specific pipeline components, keyed by component name.                                                                                  |
 
 ## Language.begin_training {#begin_training tag="method"}