diff --git a/website/usage/_linguistic-features/_rule-based-matching.jade b/website/usage/_linguistic-features/_rule-based-matching.jade
index 7984b100e..f7c800c45 100644
--- a/website/usage/_linguistic-features/_rule-based-matching.jade
+++ b/website/usage/_linguistic-features/_rule-based-matching.jade
@@ -206,7 +206,8 @@ p
     nlp = spacy.load('en_core_web_sm')
     matcher = PhraseMatcher(nlp.vocab)
     terminology_list = ['Barack Obama', 'Angela Merkel', 'Washington, D.C.']
-    patterns = [nlp(text) for text in terminology_list]
+    # Only run nlp.make_doc to speed things up
+    patterns = [nlp.make_doc(text) for text in terminology_list]
     matcher.add('TerminologyList', None, *patterns)
 
     doc = nlp(u"German Chancellor Angela Merkel and US President Barack Obama "
diff --git a/website/usage/_processing-pipelines/_custom-components.jade b/website/usage/_processing-pipelines/_custom-components.jade
index f3f2cc417..674722eba 100644
--- a/website/usage/_processing-pipelines/_custom-components.jade
+++ b/website/usage/_processing-pipelines/_custom-components.jade
@@ -72,7 +72,7 @@ p
         name = 'entity_matcher'
 
         def __init__(self, nlp, terms, label):
-            patterns = [nlp(text) for text in terms]
+            patterns = [nlp.make_doc(text) for text in terms]
             self.matcher = PhraseMatcher(nlp.vocab)
             self.matcher.add(label, None, *patterns)
 
diff --git a/website/usage/_v2/_migrating.jade b/website/usage/_v2/_migrating.jade
index f313d1ce3..f54ceb9cf 100644
--- a/website/usage/_v2/_migrating.jade
+++ b/website/usage/_v2/_migrating.jade
@@ -240,7 +240,7 @@ p
 +code-new.
     from spacy.matcher import PhraseMatcher
     matcher = PhraseMatcher(nlp.vocab)
-    patterns = [nlp(text) for text in large_terminology_list]
+    patterns = [nlp.make_doc(text) for text in large_terminology_list]
     matcher.add('PRODUCT', None, *patterns)
 
 +code-old.