diff --git a/spacy/ml/models/parser.py b/spacy/ml/models/parser.py
index 80751a695..97137313d 100644
--- a/spacy/ml/models/parser.py
+++ b/spacy/ml/models/parser.py
@@ -56,7 +56,7 @@ def build_tb_parser_model(
         non-linearity if use_upper=False.
     use_upper (bool): Whether to use an additional hidden layer after the state
         vector in order to predict the action scores. It is recommended to set
-        this to False for large pretrained models such as transformers, and False
+        this to False for large pretrained models such as transformers, and True
         for smaller networks. The upper layer is computed on CPU, which becomes
         a bottleneck on larger GPU-based models, where it's also less necessary.
     nO (int or None): The number of actions the model will predict between.
diff --git a/website/docs/usage/processing-pipelines.md b/website/docs/usage/processing-pipelines.md
index 0109f24c9..0264a2825 100644
--- a/website/docs/usage/processing-pipelines.md
+++ b/website/docs/usage/processing-pipelines.md
@@ -795,7 +795,7 @@ if there's no state to be passed through – spaCy can just take care of this fo
 you. The following two code examples are equivalent:
 
 ```python
-# Statless component with @Language.factory
+# Stateless component with @Language.factory
 @Language.factory("my_component")
 def create_my_component():
     def my_component(doc):
diff --git a/website/meta/universe.json b/website/meta/universe.json
index 04163c61e..6e5696be1 100644
--- a/website/meta/universe.json
+++ b/website/meta/universe.json
@@ -3285,15 +3285,17 @@
             "slogan": "Forte is a toolkit for building Natural Language Processing pipelines, featuring cross-task interaction, adaptable data-model interfaces and composable pipelines.",
             "description": "Forte provides a platform to assemble state-of-the-art NLP and ML technologies in a highly-composable fashion, including a wide spectrum of tasks ranging from Information Retrieval, Natural Language Understanding to Natural Language Generation.",
             "github": "asyml/forte",
-            "pip": "forte.spacy torch",
+            "pip": "forte.spacy stave torch",
             "code_example": [
-                "from forte.spacy import SpacyProcessor",
+                "from fortex.spacy import SpacyProcessor",
+                "from forte.processors.stave import StaveProcessor",
                 "from forte import Pipeline",
                 "from forte.data.readers import StringReader",
                 "",
                 "pipeline = Pipeline()",
                 "pipeline.set_reader(StringReader())",
                 "pipeline.add(SpacyProcessor())",
+                "pipeline.add(StaveProcessor())",
                 "pipeline.run('Running SpaCy with Forte!')"
             ],
             "code_language": "python",