diff --git a/spacy/language.py b/spacy/language.py
index e62431bf1..6eb2d150b 100644
--- a/spacy/language.py
+++ b/spacy/language.py
@@ -31,6 +31,8 @@ from .attrs import TAG, DEP, ENT_IOB, ENT_TYPE, HEAD, PROB, LANG, IS_STOP
 from .syntax.parser import get_templates
 from .syntax.nonproj import PseudoProjectivity
 from .pipeline import DependencyParser, EntityRecognizer
+from .syntax.arc_eager import ArcEager
+from .syntax.ner import BiluoPushDown
 
 
 class BaseDefaults(object):
@@ -65,7 +67,7 @@ class BaseDefaults(object):
         prefix_search  = util.compile_prefix_regex(cls.prefixes).search
         suffix_search  = util.compile_suffix_regex(cls.suffixes).search
         infix_finditer = util.compile_infix_regex(cls.infixes).finditer
-        vocab = nlp.vocab if nlp is not None else cls.create_vocab(nlp)
+        vocab = nlp.vocab if nlp is not None else cls.Default.create_vocab(nlp)
         return Tokenizer(nlp.vocab, rules=rules,
                          prefix_search=prefix_search, suffix_search=suffix_search,
                          infix_finditer=infix_finditer)
@@ -82,26 +84,27 @@ class BaseDefaults(object):
             return Tagger.load(nlp.path / 'pos', nlp.vocab)
 
     @classmethod
-    def create_parser(cls, nlp=None):
+    def create_parser(cls, nlp=None, **cfg):
         if nlp is None:
-            return DependencyParser(cls.create_vocab(), features=cls.parser_features)
+            return DependencyParser(cls.create_vocab(), features=cls.parser_features,
+                                    **cfg)
         elif nlp.path is False:
-            return DependencyParser(nlp.vocab, features=cls.parser_features)
+            return DependencyParser(nlp.vocab, features=cls.parser_features, **cfg)
         elif nlp.path is None or not (nlp.path / 'deps').exists():
             return None
         else:
-            return DependencyParser.load(nlp.path / 'deps', nlp.vocab)
+            return DependencyParser.load(nlp.path / 'deps', nlp.vocab, **cfg)
 
     @classmethod
-    def create_entity(cls, nlp=None):
+    def create_entity(cls, nlp=None, **cfg):
         if nlp is None:
-            return EntityRecognizer(cls.create_vocab(), features=cls.entity_features)
+            return EntityRecognizer(cls.create_vocab(), features=cls.entity_features, **cfg)
         elif nlp.path is False:
-            return EntityRecognizer(nlp.vocab, features=cls.entity_features)
+            return EntityRecognizer(nlp.vocab, features=cls.entity_features, **cfg)
         elif nlp.path is None or not (nlp.path / 'ner').exists():
             return None
         else:
-            return EntityRecognizer.load(nlp.path / 'ner', nlp.vocab)
+            return EntityRecognizer.load(nlp.path / 'ner', nlp.vocab, **cfg)
 
     @classmethod
     def create_matcher(cls, nlp=None):
@@ -202,8 +205,8 @@ class Language(object):
             # preprocess training data here before ArcEager.get_labels() is called
             gold_tuples = PseudoProjectivity.preprocess_training_data(gold_tuples)
 
-        parser_cfg['labels'] = ArcEager.get_labels(gold_tuples)
-        entity_cfg['labels'] = BiluoPushDown.get_labels(gold_tuples)
+        parser_cfg['actions'] = ArcEager.get_actions(gold_parses=gold_tuples)
+        entity_cfg['actions'] = BiluoPushDown.get_actions(gold_parses=gold_tuples)
 
         with (dep_model_dir / 'config.json').open('wb') as file_:
             json.dump(parser_cfg, file_)
@@ -224,22 +227,18 @@ class Language(object):
                 vectors=False,
                 pipeline=False)
 
-        self.defaults.parser_labels = parser_cfg['labels']
-        self.defaults.entity_labels = entity_cfg['labels']
-
-        self.vocab = self.defaults.Vocab()
-        self.tokenizer = self.defaults.Tokenizer(self.vocab)
-        self.tagger = self.defaults.Tagger(self.vocab, **tagger_cfg)
-        self.parser = self.defaults.Parser(self.vocab, **parser_cfg)
-        self.entity = self.defaults.Entity(self.vocab, **entity_cfg)
-        self.pipeline = self.defaults.Pipeline(self)
+        self.vocab = self.Defaults.create_vocab(self)
+        self.tokenizer = self.Defaults.create_tokenizer(self)
+        self.tagger = self.Defaults.create_tagger(self)
+        self.parser = self.Defaults.create_parser(self)
+        self.entity = self.Defaults.create_entity(self)
+        self.pipeline = self.Defaults.create_pipeline(self)
         yield Trainer(self, gold_tuples)
         self.end_training()
 
     def __init__(self, path=True, **overrides):
-        if 'data_dir' in overrides and 'path' not in overrides:
+        if 'data_dir' in overrides and 'path' is True:
             raise ValueError("The argument 'data_dir' has been renamed to 'path'")
-        path = overrides.get('path', True)
         if isinstance(path, basestring):
             path = pathlib.Path(path)
         if path is True:
@@ -253,7 +252,7 @@ class Language(object):
         add_vectors    = self.Defaults.add_vectors(self) \
                          if 'add_vectors' not in overrides \
                          else overrides['add_vectors']
-        if add_vectors:
+        if self.vocab and add_vectors:
             add_vectors(self.vocab)
         self.tokenizer = self.Defaults.create_tokenizer(self) \
                          if 'tokenizer' not in overrides \