diff --git a/spacy/_align.pyx b/spacy/_align.pyx
index 718c0ff90..07b6efbd4 100644
--- a/spacy/_align.pyx
+++ b/spacy/_align.pyx
@@ -90,7 +90,7 @@ from .compat import unicode_
 from murmurhash.mrmr cimport hash32
 
 
-def align(S, T, many_to_one=False, one_to_many=False):
+def align(S, T):
     cdef int m = len(S)
     cdef int n = len(T)
     cdef np.ndarray matrix = numpy.zeros((m+1, n+1), dtype='int32')
@@ -126,39 +126,58 @@ def multi_align(np.ndarray i2j, np.ndarray j2i, i_lengths, j_lengths):
     i2j_multi: {1: 1, 2: 1}
     j2i_multi: {}
     '''
-    i_starts = numpy.cumsum([0] + i_lengths[:-1])
-    j_starts = numpy.cumsum([0] + j_lengths[:-1])
-    i2j_miss = _get_regions(i2j, i_starts)
-    j2i_miss = _get_regions(j2i, j_starts)
+    i2j_miss = _get_regions(i2j, i_lengths)
+    j2i_miss = _get_regions(j2i, j_lengths)
 
-    i2j_multi = _get_mapping(i2j_miss, j2i_miss, i_lengths, j_lengths)
-    j2i_multi = _get_mapping(j2i_miss, i2j_miss, j_lengths, i_lengths)
+    i2j_multi, j2i_multi = _get_mapping(i2j_miss, j2i_miss, i_lengths, j_lengths)
     return i2j_multi, j2i_multi
 
 
-def _get_regions(alignment, starts):
+def _get_regions(alignment, lengths):
     regions = {}
     start = None
+    offset = 0
     for i in range(len(alignment)):
         if alignment[i] < 0:
             if start is None:
-                start = starts[i]
+                start = offset
                 regions.setdefault(start, [])
             regions[start].append(i)
         else:
             start = None
+        offset += lengths[i]
     return regions
 
 
 def _get_mapping(miss1, miss2, lengths1, lengths2):
-    output = {}
+    i2j = {}
+    j2i = {}
     for start, region1 in miss1.items():
-        region2 = miss2.get(start, [])
-        if len(region2) == 1:
-            if sum(lengths1[i] for i in region1):
-                for i in region1:
-                    output[i] = region2[0]
-    return output
+        if not region1 or start not in miss2:
+            continue
+        region2 = miss2[start]
+        if sum(lengths1[i] for i in region1) == sum(lengths2[i] for i in region2):
+            j = region2.pop(0)
+            buff = []
+            # Consume tokens from region 1, until we meet the length of the
+            # first token in region2. If we do, align the tokens. If
+            # we exceed the length, break.
+            while region1:
+                buff.append(region1.pop(0))
+                if sum(lengths1[i] for i in buff) == lengths2[j]:
+                    for i in buff:
+                        i2j[i] = j
+                    j2i[j] = buff[-1]
+                    j += 1
+                    buff = []
+                elif sum(lengths1[i] for i in buff) > lengths2[j]:
+                    break
+            else:
+                if buff and sum(lengths1[i] for i in buff) == lengths2[j]:
+                    for i in buff:
+                        i2j[i] = j
+                    j2i[j] = buff[-1]
+    return i2j, j2i
 
 
 def _convert_sequence(seq):
diff --git a/spacy/gold.pyx b/spacy/gold.pyx
index 56a4f971b..f6bf38700 100644
--- a/spacy/gold.pyx
+++ b/spacy/gold.pyx
@@ -63,8 +63,6 @@ def merge_sents(sents):
 
 punct_re = re.compile(r'\W')
 def align(cand_words, gold_words):
-    cand_words = [punct_re.sub('', w).lower() for w in cand_words]
-    gold_words = [punct_re.sub('', w).lower() for w in gold_words]
     if cand_words == gold_words:
         alignment = numpy.arange(len(cand_words))
         return 0, alignment, alignment, {}, {}
@@ -389,7 +387,7 @@ cdef class GoldParse:
         for i, gold_i in enumerate(self.cand_to_gold):
             if doc[i].text.isspace():
                 self.words[i] = doc[i].text
-                self.tags[i] = 'SP'
+                self.tags[i] = '_SP'
                 self.heads[i] = None
                 self.labels[i] = None
                 self.ner[i] = 'O'