diff --git a/bin/parser/train.py b/bin/parser/train.py
index 4c8611f2c..2184ffbe6 100755
--- a/bin/parser/train.py
+++ b/bin/parser/train.py
@@ -187,7 +187,7 @@ def get_labels(sents):
 
 
 def train(Language, train_loc, model_dir, n_iter=15, feat_set=u'basic', seed=0,
-          gold_preproc=False, force_gold=False, n_sents=0):
+          gold_preproc=False, n_sents=0):
     dep_model_dir = path.join(model_dir, 'deps')
     pos_model_dir = path.join(model_dir, 'pos')
     ner_model_dir = path.join(model_dir, 'ner')
@@ -230,8 +230,8 @@ def train(Language, train_loc, model_dir, n_iter=15, feat_set=u'basic', seed=0,
             for tokens in sents:
                 gold = GoldParse(tokens, annot_tuples)
                 nlp.tagger(tokens)
-                nlp.parser.train(tokens, gold, force_gold=force_gold)
-                nlp.entity.train(tokens, gold, force_gold=force_gold)
+                nlp.parser.train(tokens, gold)
+                nlp.entity.train(tokens, gold)
                 nlp.tagger.train(tokens, gold.tags)
 
         print '%d:\t%.3f\t%.3f\t%.3f' % (itn, scorer.uas, scorer.ents_f, scorer.tags_acc)
@@ -280,7 +280,7 @@ def write_parses(Language, dev_loc, model_dir, out_loc):
 def main(train_loc, dev_loc, model_dir, n_sents=0, out_loc="", verbose=False,
          debug=False):
     train(English, train_loc, model_dir, feat_set='basic' if not debug else 'debug',
-          gold_preproc=False, force_gold=False, n_sents=n_sents)
+          gold_preproc=False, n_sents=n_sents)
     if out_loc:
         write_parses(English, dev_loc, model_dir, out_loc)
     scorer = evaluate(English, dev_loc, model_dir, gold_preproc=False, verbose=verbose)
diff --git a/spacy/syntax/parser.pyx b/spacy/syntax/parser.pyx
index cc2c30143..9b71e78ed 100644
--- a/spacy/syntax/parser.pyx
+++ b/spacy/syntax/parser.pyx
@@ -93,7 +93,7 @@ cdef class GreedyParser:
         tokens.set_parse(state.sent)
         return 0
 
-    def train(self, Tokens tokens, GoldParse gold, force_gold=False):
+    def train(self, Tokens tokens, GoldParse gold):
         self.moves.preprocess_gold(gold)
         cdef Pool mem = Pool()
         cdef State* state = new_state(mem, tokens.data, tokens.length)
@@ -109,12 +109,11 @@ cdef class GreedyParser:
         while not is_final(state):
             fill_context(context, state)
             scores = self.model.score(context)
+
             guess = self.moves.best_valid(scores, state)
             best = self.moves.best_gold(scores, state, gold)
+            
             cost = guess.get_cost(&guess, state, gold)
-
             self.model.update(context, guess.clas, best.clas, cost)
-            if force_gold:
-                best.do(&best, state)
-            else:
-                guess.do(&guess, state)
+
+            guess.do(&guess, state)