Fix passing of morphological features to lemmatizer

spacy/lemmatizer.py

@@ -47,17 +47,6 @@ class Lemmatizer(object):
         Check whether we're dealing with an uninflected paradigm, so we can
         avoid lemmatization entirely.
         """
-        morphology = {} if morphology is None else morphology
-        morphology = dict(morphology)
-        for key, value in list(morphology.items()):
-            if value is True:
-                feat, value = key.split('_')
-                morphology[feat] = value
-        others = [
-            key
-            for key in morphology
-            if key not in (POS, "Number", "POS", "VerbForm", "Tense")
-        ]
         if univ_pos == "noun" and morphology.get("Number") == "sing":
             return True
         elif univ_pos == "verb" and morphology.get("VerbForm") == "inf":
@@ -68,7 +57,6 @@ class Lemmatizer(object):
             morphology.get("VerbForm") == "fin"
             and morphology.get("Tense") == "pres"
             and morphology.get("Number") is None
-            and not others
         ):
             return True
         elif univ_pos == "adj" and morphology.get("Degree") == "pos":

spacy/morphology.pyx

@@ -141,7 +141,16 @@ cdef class Morphology:
             return self.strings.add(py_string.lower())
         cdef list lemma_strings
         cdef unicode lemma_string
-        lemma_strings = self.lemmatizer(py_string, univ_pos, morphology)
+        # Normalize features into a dict keyed by the field, to make life easier
+        # for the lemmatizer. Handles string-to-int conversion too.
+        string_feats = {}
+        for key, value in morphology.items():
+            if value is True:
+                name, value = self.strings.as_string(key).split('_', 1)
+                string_feats[name] = value
+            else:
+                string_feats[self.strings.as_string(key)] = self.strings.as_string(value)
+        lemma_strings = self.lemmatizer(py_string, univ_pos, string_feats)
         lemma_string = lemma_strings[0]
         lemma = self.strings.add(lemma_string)
         return lemma