Update 101 and add note on pipeline order and tensors
@@ -63,3 +63,16 @@ p
+code(false, "json").
"pipeline": ["tensorizer", "tagger", "parser", "ner"]
+
+p
+ | Although you can mix and match pipeline components, their
+ | #[strong order and combination] is usually important. Some components may
+ | require certain modifications on the #[code Doc] to process it. For
+ | example, the default pipeline first applies the tensorizer, which
+ | pre-processes the doc and encodes its internal
+ | #[strong meaning representations] as an array of floats, also called a
+ | #[strong tensor]. This includes the tokens and their context, which is
+ | required for the next component, the tagger, to make predictions of the
+ | part-of-speech tags. Because spaCy's models are neural network models,
+ | they only "speak" tensors and expect the input #[code Doc] to have
+ | a #[code tensor].
