* More work on language independent parsing

spacy/language.py

@@ -6,7 +6,6 @@ except ImportError:
     import json
 
 from .tokenizer import Tokenizer
-from .morphology import Morphology
 from .vocab import Vocab
 from .syntax.parser import Parser
 from .tagger import Tagger
@@ -132,16 +131,12 @@ class Language(object):
     def default_data_dir(cls):
         return path.join(path.dirname(__file__), 'data')
 
-    @classmethod
-    def default_morphology(cls, data_dir):
-        return Morphology.from_dir(data_dir)
-
     @classmethod
     def default_vectors(cls, data_dir):
         return None
 
     @classmethod
-    def default_vocab(cls, data_dir=None, get_lex_attr=None, vectors=None, morphology=None):
+    def default_vocab(cls, data_dir=None, get_lex_attr=None, vectors=None):
         if data_dir is None:
             data_dir = cls.default_data_dir()
         if vectors is None:

spacy/morphology.pxd

@@ -22,7 +22,7 @@ cdef struct MorphAnalysisC:
 
 cdef class Morphology:
     cdef readonly Pool mem
-    cdef readonly object strings
+    cdef readonly StringStore strings
     cdef public object lemmatizer
     cdef public object n_tags
     cdef public object reverse_index

spacy/morphology.pyx

@@ -11,20 +11,15 @@ from .parts_of_speech cimport ADJ, VERB, NOUN
 
 
 cdef class Morphology:
-    @classmethod
+    def __init__(self, StringStore string_store, tag_map, lemmatizer):
-    def from_dir(cls, data_dir, lemmatizer=None):
-        tag_map = json.load(open(path.join(data_dir, 'tag_map.json')))
-        if lemmatizer is None:
-            lemmatizer = Lemmatizer.from_dir(data_dir)
-        return cls(tag_map, {}, lemmatizer)
-
-    def __init__(self, string_store, tag_map, lemmatizer):
         self.mem = Pool()
         self.strings = string_store
         self.lemmatizer = lemmatizer
-        self.n_tags = len(tag_map)
+        self.n_tags = len(tag_map) + 1
         self.tag_names = tuple(sorted(tag_map.keys()))
         self.reverse_index = {}
+        
+        self.rich_tags = <RichTagC*>self.mem.alloc(self.n_tags, sizeof(RichTagC))
         for i, (tag_str, props) in enumerate(sorted(tag_map.items())):
             self.rich_tags[i].id = i
             self.rich_tags[i].name = self.strings[tag_str]
@@ -33,12 +28,16 @@ cdef class Morphology:
         self._cache = PreshMapArray(self.n_tags)
 
     cdef int assign_tag(self, TokenC* token, tag) except -1:
-        cdef int tag_id = self.strings[tag] if isinstance(tag, basestring) else tag
+        cdef int tag_id
+        if isinstance(tag, basestring):
+            tag_id = self.reverse_index[self.strings[tag]]
+        else:
+            tag_id = tag
         analysis = <MorphAnalysisC*>self._cache.get(tag_id, token.lex.orth)
         if analysis is NULL:
             analysis = <MorphAnalysisC*>self.mem.alloc(1, sizeof(MorphAnalysisC))
             analysis.tag = self.rich_tags[tag_id]
-            analysis.lemma = self.lemmatize(tag, token.lex.orth)
+            analysis.lemma = self.lemmatize(analysis.tag.pos, token.lex.orth)
         token.lemma = analysis.lemma
         token.pos = analysis.tag.pos
         token.tag = analysis.tag.name

spacy/tagger.pyx

@@ -104,7 +104,7 @@ cdef class Tagger:
 
     @classmethod
     def blank(cls, vocab, templates):
-        model = Model(vocab.n_tags, templates, model_loc=None)
+        model = Model(vocab.morphology.n_tags, templates, model_loc=None)
         return cls(vocab, model)
 
     @classmethod
@@ -113,7 +113,7 @@ cdef class Tagger:
             templates = json.loads(open(path.join(data_dir, 'templates.json')))
         else:
             templates = cls.default_templates()
-        model = Model(vocab.n_tags, templates, data_dir)
+        model = Model(vocab.morphology.n_tags, templates, data_dir)
         return cls(vocab, model)
 
     def __init__(self, Vocab vocab, model):
@@ -128,7 +128,7 @@ cdef class Tagger:
 
     @property
     def tag_names(self):
-        return self.vocab.tag_names
+        return self.vocab.morphology.tag_names
 
     def __call__(self, Doc tokens):
         """Apply the tagger, setting the POS tags onto the Doc object.

spacy/vocab.pyx

@@ -49,13 +49,15 @@ cdef class Vocab:
         self._serializer = None
 
     @classmethod
-    def from_dir(cls, data_dir, get_lex_attr=None, morphology=None, vectors=None):
+    def from_dir(cls, data_dir, get_lex_attr=None, vectors=None):
         if not path.exists(data_dir):
             raise IOError("Directory %s not found -- cannot load Vocab." % data_dir)
         if not path.isdir(data_dir):
             raise IOError("Path %s is a file, not a dir -- cannot load Vocab." % data_dir)
+
         tag_map = json.load(open(path.join(data_dir, 'tag_map.json')))
         cdef Vocab self = cls(get_lex_attr=get_lex_attr, vectors=vectors, tag_map=tag_map)
+
         self.load_lexemes(path.join(data_dir, 'strings.txt'), path.join(data_dir, 'lexemes.bin'))
         if vectors is None and path.exists(path.join(data_dir, 'vec.bin')):
             self.repvec_length = self.load_rep_vectors(path.join(data_dir, 'vec.bin'))