Fix attributeruler

spacy/pipeline/attributeruler.py

@@ -80,11 +80,14 @@ class AttributeRuler(Pipe):
         DOCS: https://nightly.spacy.io/api/attributeruler#call
         """
         matches = sorted(self.matcher(doc, allow_missing=True))
+        print("Attrs", self.attrs)
+        print("Matches", matches)
 
         for match_id, start, end in matches:
             span = Span(doc, start, end, label=match_id)
-            attrs = self.attrs[span.label]
-            index = self.indices[span.label]
+            attr_id = _parse_key(span.label_)
+            attrs = self.attrs[attr_id]
+            index = self.indices[attr_id]
             try:
                 token = span[index]
             except IndexError:
@@ -173,9 +176,10 @@ class AttributeRuler(Pipe):
 
         DOCS: https://nightly.spacy.io/api/attributeruler#add
         """
-        # This needs to be a string, because otherwise it's interpreted as a
-        # string key.
-        self.matcher.add(f"attr_rules_{len(self.attrs)}", patterns)
+        # We need to make a string here, because otherwise the ID we pass back
+        # will be interpreted as the hash of a string, rather than an ordinal.
+        key = _make_key(len(self.attrs))
+        self.matcher.add(self.vocab.strings.add(key), patterns)
         self._attrs_unnormed.append(attrs)
         attrs = normalize_token_attrs(self.vocab, attrs)
         self.attrs.append(attrs)
@@ -199,7 +203,7 @@ class AttributeRuler(Pipe):
         all_patterns = []
         for i in range(len(self.attrs)):
             p = {}
-            p["patterns"] = self.matcher.get(i)[1]
+            p["patterns"] = self.matcher.get(_make_key(i))[1]
             p["attrs"] = self._attrs_unnormed[i]
             p["index"] = self.indices[i]
             all_patterns.append(p)
@@ -303,6 +307,12 @@ class AttributeRuler(Pipe):
 
         return self
 
+def _make_key(n_attr):
+    return f"attr_rule_{n_attr}"
+
+def _parse_key(key):
+    return int(key.rsplit("_", 1)[1])
+
 
 def _split_morph_attrs(attrs):
     """Split entries from a tag map or morph rules dict into to two dicts, one