diff --git a/danlp/datasets/ddt.py b/danlp/datasets/ddt.py
index 3f2aff9..33991d7 100644
--- a/danlp/datasets/ddt.py
+++ b/danlp/datasets/ddt.py
@@ -1,5 +1,7 @@
 import os
 
+
+
 from danlp.download import DEFAULT_CACHE_DIR, download_dataset, _unzip_process_func, DATASETS
 
 
@@ -84,3 +86,36 @@ def load_with_flair(self, predefined_splits: bool = False):
                     token.tags['ner'].value = token.tags['ner'].value.split("=")[1].replace("|SpaceAfter", "")
 
         return corpus
+
+    def load_with_spacy(self):
+        """
+        Converts the conllu files to json in the spaCy format.
+
+        Not using jsonl because of:
+        https://github.com/explosion/spaCy/issues/3523
+        :return:
+        """
+        import srsly
+        from spacy.cli.converters import conllu2json
+        from spacy.gold import GoldCorpus
+        from spacy.gold import Path
+
+        for part in ['train', 'dev', 'test']:
+            conll_path = os.path.join(self.dataset_dir, '{}.{}{}'.format(self.dataset_name, part, self.file_extension))
+            json_path = os.path.join(self.dataset_dir, "ddt.{}.json".format(part))
+
+            if not os.path.isfile(json_path):  # Convert the conllu files to json
+                with open(conll_path, 'r') as file:
+                    file_as_string = file.read()
+                    file_as_string = file_as_string.replace("name=", "").replace("|SpaceAfter", "")
+                    file_as_json = conllu2json(file_as_string)
+
+                    srsly.write_json(json_path, file_as_json)
+
+        train_json_path = os.path.join(self.dataset_dir, "ddt.train.json")
+        dev_json_path = os.path.join(self.dataset_dir, "ddt.dev.json")
+
+        assert os.path.isfile(train_json_path)
+        assert os.path.isfile(dev_json_path)
+
+        return GoldCorpus(Path(train_json_path), Path(dev_json_path))
diff --git a/tests/test_datasets.py b/tests/test_datasets.py
index dff2f1c..7948427 100644
--- a/tests/test_datasets.py
+++ b/tests/test_datasets.py
@@ -1,34 +1,41 @@
 import shutil
 import unittest
 
+from flair.datasets import ColumnCorpus
 from pyconll.unit import Conll
+from spacy.gold import GoldCorpus
 
 from danlp.datasets import DDT, WikiAnn, DATASETS
 
 
 class TestNerDatasets(unittest.TestCase):
 
-    def test_ddt_dataset(self):
-        train_len = 4383
-        dev_len = 564
-        test_len = 565
+    def setUp(self):
+        self.train_len = 4383
+        self.dev_len = 564
+        self.test_len = 565
 
-        ddt = DDT()  # Load dataset
+        self.ddt = DDT()  # Load dataset
 
-        train, dev, test = ddt.load_as_conllu(predefined_splits=True)
+    def test_ddt_dataset(self):
+        train, dev, test = self.ddt.load_as_conllu(predefined_splits=True)
 
         self.assertIsInstance(train, Conll)
         self.assertIsInstance(dev, Conll)
         self.assertIsInstance(test, Conll)
 
-        self.assertEqual([len(train), len(dev), len(test)], [train_len, dev_len, test_len])
+        self.assertEqual([len(train), len(dev), len(test)], [self.train_len, self.dev_len, self.test_len])
+
+        full_dataset = self.ddt.load_as_conllu(predefined_splits=False)
+        self.assertEqual(len(full_dataset), self.train_len + self.dev_len + self.test_len)
 
-        full_dataset = ddt.load_as_conllu(predefined_splits=False)
-        self.assertEqual(len(full_dataset), train_len+dev_len+test_len)
+    def test_ddt_dataset_with_flair(self):
+        flair_corpus = self.ddt.load_with_flair()
+
+        self.assertIsInstance(flair_corpus, ColumnCorpus)
 
-        flair_corpus = ddt.load_with_flair()
         flair_lens = [len(flair_corpus.train), len(flair_corpus.dev), len(flair_corpus.test)]
-        self.assertEqual(flair_lens, [train_len, dev_len, test_len])
+        self.assertEqual(flair_lens, [self.train_len, self.dev_len, self.test_len])
 
         ner_tags = flair_corpus.make_tag_dictionary('ner').idx2item
         asserted_ner_tags = [
@@ -38,6 +45,11 @@ def test_ddt_dataset(self):
         ]
         self.assertCountEqual(ner_tags, asserted_ner_tags)
 
+    def test_ddt_dataset_with_spacy(self):
+        ddt = DDT()  # Load dataset
+        corpus = ddt.load_with_spacy()
+        self.assertIsInstance(corpus, GoldCorpus)
+
     def test_wikiann_dataset(self):
         # Change to a sample of the full wikiann to ease test computation
         DATASETS['wikiann']['url'] = "https://danlp.s3.eu-central-1.amazonaws.com/test-datasets/da.tar.gz"
@@ -60,4 +72,3 @@ def test_wikiann_dataset(self):
 
         shutil.rmtree(wikiann.dataset_dir)
 
-