Matcher ID fixes (#4179)

* allow phrasematcher to link one match to multiple original patterns

* small fix for defining ent_id in the matcher (anti-ghost prevention)

* cleanup

* formatting

spacy/matcher/matcher.pyx

@@ -327,7 +327,7 @@ cdef void transition_states(vector[PatternStateC]& states, vector[MatchC]& match
             states[q].length += 1
             q += 1
         else:
-            ent_id = get_ent_id(&state.pattern[1])
+            ent_id = get_ent_id(state.pattern)
             if action == MATCH:
                 matches.push_back(
                     MatchC(pattern_id=ent_id, start=state.start,

spacy/matcher/phrasematcher.pxd

@@ -0,0 +1,5 @@
+from libcpp.vector cimport vector
+
+from ..typedefs cimport hash_t
+
+ctypedef vector[hash_t] hash_vec

spacy/matcher/phrasematcher.pyx

@@ -2,6 +2,7 @@
 # cython: profile=True
 from __future__ import unicode_literals
 
+from libcpp.vector cimport vector
 from cymem.cymem cimport Pool
 from murmurhash.mrmr cimport hash64
 from preshed.maps cimport PreshMap
@@ -37,6 +38,7 @@ cdef class PhraseMatcher:
     cdef Vocab vocab
     cdef Matcher matcher
     cdef PreshMap phrase_ids
+    cdef vector[hash_vec] ent_id_matrix
     cdef int max_length
     cdef attr_id_t attr
     cdef public object _callbacks
@@ -145,7 +147,23 @@ cdef class PhraseMatcher:
                 lexeme.set_flag(tag, True)
                 phrase_key[i] = lexeme.orth
             phrase_hash = hash64(phrase_key, length * sizeof(attr_t), 0)
-            self.phrase_ids.set(phrase_hash, <void*>ent_id)
+
+            if phrase_hash in self.phrase_ids:
+                phrase_index = self.phrase_ids[phrase_hash]
+                ent_id_list = self.ent_id_matrix[phrase_index]
+                ent_id_list.append(ent_id)
+                self.ent_id_matrix[phrase_index] = ent_id_list
+
+            else:
+                ent_id_list = hash_vec(1)
+                ent_id_list[0] = ent_id
+                new_index = self.ent_id_matrix.size()
+                if new_index == 0:
+                    # PreshMaps can not contain 0 as value, so storing a dummy at 0
+                    self.ent_id_matrix.push_back(hash_vec(0))
+                    new_index = 1
+                self.ent_id_matrix.push_back(ent_id_list)
+                self.phrase_ids.set(phrase_hash,  <void*>new_index)
 
     def __call__(self, Doc doc):
         """Find all sequences matching the supplied patterns on the `Doc`.
@@ -167,9 +185,10 @@ cdef class PhraseMatcher:
             words = [self.get_lex_value(doc, i) for i in range(len(doc))]
             match_doc = Doc(self.vocab, words=words)
         for _, start, end in self.matcher(match_doc):
-            ent_id = self.accept_match(match_doc, start, end)
-            if ent_id is not None:
-                matches.append((ent_id, start, end))
+            ent_ids = self.accept_match(match_doc, start, end)
+            if ent_ids is not None:
+                for ent_id in ent_ids:
+                    matches.append((ent_id, start, end))
         for i, (ent_id, start, end) in enumerate(matches):
             on_match = self._callbacks.get(ent_id)
             if on_match is not None:
@@ -216,11 +235,11 @@ cdef class PhraseMatcher:
         for i, j in enumerate(range(start, end)):
             phrase_key[i] = doc.c[j].lex.orth
         cdef hash_t key = hash64(phrase_key, (end-start) * sizeof(attr_t), 0)
-        ent_id = <hash_t>self.phrase_ids.get(key)
-        if ent_id == 0:
+
+        ent_index = <hash_t>self.phrase_ids.get(key)
+        if ent_index == 0:
             return None
-        else:
-            return ent_id
+        return self.ent_id_matrix[ent_index]
 
     def get_lex_value(self, Doc doc, int i):
         if self.attr == ORTH:

spacy/tests/regression/test_issue3972.py

@@ -6,7 +6,6 @@ from spacy.matcher import PhraseMatcher
 from spacy.tokens import Doc
 
 
-@pytest.mark.xfail
 def test_issue3972(en_vocab):
     """Test that the PhraseMatcher returns duplicates for duplicate match IDs.
     """
@@ -15,4 +14,10 @@ def test_issue3972(en_vocab):
     matcher.add("B", None, Doc(en_vocab, words=["New", "York"]))
     doc = Doc(en_vocab, words=["I", "live", "in", "New", "York"])
     matches = matcher(doc)
+
     assert len(matches) == 2
+
+    # We should have a match for each of the two rules
+    found_ids = [en_vocab.strings[ent_id] for (ent_id, _, _) in matches]
+    assert "A" in found_ids
+    assert "B" in found_ids