* Refactor noun chunk iterators, so that they're simple functions. Install the iterator when the Doc is created, but allow users to write to the noun_chunk_iterator attribute. The iterator functions accept an object and yield (int start, int end, int label) triples.

spacy/syntax/arc_eager.pyx

@@ -383,6 +383,9 @@ cdef class ArcEager(TransitionSystem):
             if st._sent[i].head == 0 and st._sent[i].dep == 0:
                 st._sent[i].dep = self.root_label
 
+    def finalize_doc(self, doc):
+        doc.is_parsed = True
+
     cdef int set_valid(self, int* output, const StateC* st) nogil:
         cdef bint[N_MOVES] is_valid
         is_valid[SHIFT] = Shift.is_valid(st, -1)

spacy/syntax/iterators.pxd

@@ -1,19 +0,0 @@
-
-from spacy.tokens.doc cimport Doc
-
-cdef dict CHUNKERS
-
-cdef class DocIterator:
-    cdef Doc _doc
-
-cdef class EnglishNounChunks(DocIterator):
-    cdef int i
-    cdef int _np_label
-    cdef set _np_deps
-    cdef int _conjunct
-
-cdef class GermanNounChunks(DocIterator):
-    cdef int i
-    cdef int _np_label
-    cdef set _np_deps
-    cdef int _close_app

spacy/syntax/iterators.pyx

@@ -1,55 +1,23 @@
-from spacy.structs cimport TokenC
-from spacy.tokens.span cimport Span
-from spacy.tokens.doc cimport Doc
-from spacy.tokens.token cimport Token
-
 from spacy.parts_of_speech cimport NOUN
 
-CHUNKERS = {'en':EnglishNounChunks, 'de':GermanNounChunks}
 
-# base class for document iterators
+def english_noun_chunks(doc):
-cdef class DocIterator:
+    labels = ['nsubj', 'dobj', 'nsubjpass', 'pcomp', 'pobj',
-    def __init__(self, Doc doc):
+              'attr', 'root']
-        self._doc = doc
+    np_deps = [doc.vocab.strings[label] for label in labels]
-
+    conj = doc.vocab.strings['conj']
-    def __iter__(self):
+    np_label = doc.vocab.strings['NP']
-        return self
+    for i in range(len(doc)):
-
+        word = doc[i]
-    def __next__(self):
+        if word.pos == NOUN and word.dep in np_deps:
-        raise NotImplementedError
+            yield word.left_edge.i, word.i+1, np_label
-
+        elif word.pos == NOUN and word.dep == conj:
-
+            head = word.head
-cdef class EnglishNounChunks(DocIterator):
+            while head.dep == conj and head.head.i < head.i:
-    def __init__(self, Doc doc):
+                head = head.head
-        super(EnglishNounChunks,self).__init__(doc)
-        labels = ['nsubj', 'dobj', 'nsubjpass', 'pcomp', 'pobj', 'attr', 'root']
-        self._np_label = self._doc.vocab.strings['NP']
-        self._np_deps = set( self._doc.vocab.strings[label] for label in labels )
-        self._conjunct = self._doc.vocab.strings['conj']
-        self.i = 0
-
-    def __iter__(self):
-        self.i = 0
-        return super(EnglishNounChunks,self).__iter__()
-
-    def __next__(self):
-        cdef const TokenC* word
-        cdef widx
-        while self.i < self._doc.length:
-            widx = self.i
-            self.i += 1
-            word = &self._doc.c[widx]
-            if word.pos == NOUN:
-                if word.dep in self._np_deps:
-                    return Span(self._doc, word.l_edge, widx+1, label=self._np_label)
-                elif word.dep == self._conjunct:
-                    head = word+word.head
-                    while head.dep == self._conjunct and head.head < 0:
-                        head += head.head
             # If the head is an NP, and we're coordinated to it, we're an NP
-                    if head.dep in self._np_deps:
+            if head.dep in np_deps:
-                        return Span(self._doc, word.l_edge, widx+1, label=self._np_label)
+                yield word.left_edge.i, word.i+1, np_label
-        raise StopIteration
 
 
 # this iterator extracts spans headed by NOUNs starting from the left-most
@@ -58,35 +26,21 @@ cdef class EnglishNounChunks(DocIterator):
 # extended to the right of the NOUN
 # example: "eine Tasse Tee" (a cup (of) tea) returns "eine Tasse Tee" and not
 # just "eine Tasse", same for "das Thema Familie"
-cdef class GermanNounChunks(DocIterator):
+def german_noun_chunks(doc):
-    def __init__(self, Doc doc):
-        super(GermanNounChunks,self).__init__(doc)
     labels = ['sb', 'oa', 'da', 'nk', 'mo', 'ag', 'root', 'cj', 'pd', 'og', 'app']
-        self._np_label = self._doc.vocab.strings['NP']
+    np_label = doc.vocab.strings['NP']
-        self._np_deps = set( self._doc.vocab.strings[label] for label in labels )
+    np_deps = set(doc.vocab.strings[label] for label in labels)
-        self._close_app = self._doc.vocab.strings['nk']
+    close_app = doc.vocab.strings['nk']
-        self.i = 0
 
-    def __iter__(self):
+    for word in doc:
-        self.i = 0
+        if word.pos == NOUN and word.dep in np_deps:
-        return super(GermanNounChunks,self).__iter__()
+            rbracket = word.i+1
-
-    def __next__(self):
-        cdef const TokenC* word
-        cdef int rbracket
-        cdef Token rdep
-        cdef widx
-        while self.i < self._doc.length:
-            widx = self.i
-            self.i += 1
-            word = &self._doc.c[widx]
-            if word.pos == NOUN and word.dep in self._np_deps:
-                rbracket = widx+1
             # try to extend the span to the right
             # to capture close apposition/measurement constructions
-                for rdep in self._doc[widx].rights:
+            for rdep in doc[word.i].rights:
-                    if rdep.pos == NOUN and rdep.dep == self._close_app:
+                if rdep.pos == NOUN and rdep.dep == close_app:
                     rbracket = rdep.i+1
-                return Span(self._doc, word.l_edge, rbracket, label=self._np_label)
+            yield word.l_edge, rbracket, np_label
-        raise StopIteration
 
+
+CHUNKERS = {'en': english_noun_chunks, 'de': german_noun_chunks}

spacy/syntax/parser.pyx

@@ -47,8 +47,6 @@ from ._parse_features cimport fill_context
 from .stateclass cimport StateClass
 from ._state cimport StateC
 
-from spacy.syntax.iterators cimport CHUNKERS, DocIterator, EnglishNounChunks, GermanNounChunks
-
 
 DEBUG = False
 def set_debug(val):
@@ -116,7 +114,7 @@ cdef class Parser:
             self.parseC(tokens.c, tokens.length, nr_feat, nr_class)
         # Check for KeyboardInterrupt etc. Untested
         PyErr_CheckSignals()
-        self._finalize(tokens)
+        self.moves.finalize_doc(tokens)
 
     def pipe(self, stream, int batch_size=1000, int n_threads=2):
         cdef Pool mem = Pool()
@@ -142,7 +140,7 @@ cdef class Parser:
                                 raise ValueError("Error parsing doc: %s" % sent_str)
                 PyErr_CheckSignals()
                 for doc in queue:
-                    self._finalize(doc)
+                    self.moves.finalize_doc(doc)
                     yield doc
                 queue = []
         batch_size = len(queue)
@@ -155,18 +153,9 @@ cdef class Parser:
                         raise ValueError("Error parsing doc: %s" % sent_str)
         PyErr_CheckSignals()
         for doc in queue:
-            self._finalize(doc)
+            self.moves.finalize_doc(doc)
             yield doc
 
-    def _finalize(self, Doc doc):
-        # deprojectivize output
-        if self._projectivize:
-            PseudoProjectivity.deprojectivize(doc)
-        # set annotation-specific iterators
-        doc.noun_chunks = CHUNKERS.get(doc.vocab.lang,DocIterator)
-        # mark doc as parsed
-        doc.is_parsed = True
-
     cdef int parseC(self, TokenC* tokens, int length, int nr_feat, int nr_class) nogil:
         cdef ExampleC eg
         eg.nr_feat = nr_feat
@@ -313,6 +302,7 @@ cdef class StepwiseState:
         if self.stcls.is_final():
             self.parser.moves.finalize_state(self.stcls.c)
         self.doc.set_parse(self.stcls.c._sent)
+        self.parser.moves.finalize_doc(self.doc)
 
 
 cdef int _arg_max_clas(const weight_t* scores, int move, const Transition* actions,

spacy/syntax/transition_system.pyx

@@ -53,6 +53,9 @@ cdef class TransitionSystem:
     cdef int finalize_state(self, StateC* state) nogil:
         pass
 
+    def finalize_doc(self, doc):
+        pass
+
     cdef int preprocess_gold(self, GoldParse gold) except -1:
         raise NotImplementedError
 

spacy/tests/tokens/test_noun_chunks.py

@@ -3,7 +3,7 @@ import numpy as np
 from spacy.attrs import HEAD, DEP
 from spacy.symbols import nsubj, dobj, punct, amod, nmod, conj, cc, root
 from spacy.en import English
-from spacy.syntax.iterators import EnglishNounChunks
+from spacy.syntax.iterators import english_noun_chunks
 
 
 def test_not_nested():
@@ -22,9 +22,7 @@ def test_not_nested():
                 [-2, conj],
                 [-5, dobj]
             ], dtype='int32'))
-    tokens.noun_chunks = EnglishNounChunks
+    tokens.noun_chunks_iterator = english_noun_chunks
-    for chunk in tokens.noun_chunks:
-        print(chunk.text)
     word_occurred = {}
     for chunk in tokens.noun_chunks:
         for word in chunk:

spacy/tokens/doc.pyx

@@ -23,6 +23,7 @@ from .span cimport Span
 from .token cimport Token
 from ..serialize.bits cimport BitArray
 from ..util import normalize_slice
+from ..syntax.iterators import CHUNKERS
 
 
 DEF PADDING = 5
@@ -81,7 +82,7 @@ cdef class Doc:
         self.is_parsed = False
         self._py_tokens = []
         self._vector = None
-        self.noun_chunks_iterator = DocIterator(self)
+        self.noun_chunks_iterator = CHUNKERS.get(self.vocab.lang)
 
     def __getitem__(self, object i):
         """Get a Token or a Span from the Doc.
@@ -233,8 +234,8 @@ cdef class Doc:
                     self.c[start].ent_iob = 3
 
 
-    property noun_chunks:
+    @property
-        def __get__(self):
+    def noun_chunks(self):
         """Yield spans for base noun phrases."""
         if not self.is_parsed:
             raise ValueError(
@@ -242,12 +243,8 @@ cdef class Doc:
                 "requires data to be installed. If you haven't done so, run: "
                 "\npython -m spacy.%s.download all\n"
                 "to install the data" % self.vocab.lang)
-
+        for start, end, label in self.noun_chunks_iterator(self):
-            yield from self.noun_chunks_iterator
+            yield Span(self, start, end, label=label)
-
-        def __set__(self, DocIterator):            
-            self.noun_chunks_iterator = DocIterator(self)
-
 
     @property
     def sents(self):