Check whether doc is instantiated in Example.get_gold_parses() (#5167)

* Check whether doc is instantiated

When creating docs to pair with gold parses, modify test to check
whether a doc is unset rather than whether it contains tokens.

* Restore test of evaluate on an empty doc

* Set a minimal gold.orig for the scorer

Without a minimal gold.orig the scorer can't evaluate empty docs. This
is the v3 equivalent of #4925.

spacy/gold.pyx

@@ -834,7 +834,7 @@ cdef class Example:
         if merge:
             t = self.token_annotation
             doc = self.doc
-            if not self.doc:
+            if self.doc is None:
                 if not vocab:
                     raise ValueError(Errors.E998)
                 doc = Doc(vocab, words=t.words)
@@ -993,7 +993,10 @@ cdef class GoldParse:
         self.links = {} if links is None else dict(links)
 
         # avoid allocating memory if the doc does not contain any tokens
-        if self.length > 0:
+        if self.length == 0:
+            # set a minimal orig so that the scorer can score an empty doc
+            self.orig = TokenAnnotation(ids=[])
+        else:
             if not words:
                 words = [token.text for token in doc]
             if not tags:

spacy/tests/regression/test_issue4924.py

@@ -5,5 +5,4 @@ from spacy.language import Language
 def test_issue4924():
     nlp = Language()
     docs_golds = [("", {})]
-    with pytest.raises(ValueError):
-        nlp.evaluate(docs_golds)
+    nlp.evaluate(docs_golds)

spacy/tests/test_gold.py

@@ -480,3 +480,10 @@ def test_tuples_to_example(merged_dict):
     assert ex_dict["token_annotation"]["tags"] == merged_dict["tags"]
     assert ex_dict["token_annotation"]["sent_starts"] == merged_dict["sent_starts"]
     assert ex_dict["doc_annotation"]["cats"] == cats
+
+
+def test_empty_example_goldparse():
+    nlp = English()
+    doc = nlp("")
+    example = Example(doc=doc)
+    assert len(example.get_gold_parses()) == 1