guide: Pipe edits

iterative · Aug 26, 2022 · dc16807 · dc16807
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diff --git a/content/docs/command-reference/move.md b/content/docs/command-reference/move.md
@@ -87,9 +87,15 @@ model file:
 $ mv keras.h5 model.h5
 ```
 
-> Note that, often the output of a stage is a dependency in another stage,
-> creating a [dependency graph]. In this case, you may want to also update the
-> `path` in the `deps` field of `dvc.yaml`.
+<admon type="info">
+
+Often the output of a stage is a dependency in another stage, creating a
+[dependency graph]. In this case, you may want to also update the `path` in the
+`deps` field of `dvc.yaml`.
+
+[dependency graph]: /doc/user-guide/data-pipelines/defining-pipelines
+
+</admon>
 
 Finally, we run `dvc commit` with the `-f` option to force save the changes to
 <abbr>cache</abbr>:
@@ -98,8 +104,6 @@ Finally, we run `dvc commit` with the `-f` option to force save the changes to
 $ dvc commit -f
 ```
 
-[dependency graph]: /doc/user-guide/data-pipelines/defining-pipelines
-
 ## Options
 
 - `-h`, `--help` - prints the usage/help message, and exit.

diff --git a/content/docs/user-guide/basic-concepts/dependency.md b/content/docs/user-guide/basic-concepts/dependency.md
@@ -5,5 +5,5 @@ tooltip: >-
   A file or directory (possibly tracked by DVC) recorded in the `deps` section
   of a stage (in `dvc.yaml`) or `.dvc` file file. Stages are invalidated
   (considered outdated) when any of their dependencies change. See `dvc stage
-  add`, `dvc repro`, among others. See also `dvc params`.
+  add`, `dvc params`, `dvc repro`, among others.
 ---
diff --git a/content/docs/user-guide/data-pipelines/defining-pipelines.md b/content/docs/user-guide/data-pipelines/defining-pipelines.md
@@ -26,14 +26,15 @@ We call this file-based definition _codification_ (YAML format in our case). It
 has the added benefit of allowing you to develop pipelines on standard Git
 workflows ([GitOps]).
 
+[gitops]: /doc/use-cases/versioning-data-and-model-files
+
 </admon>
 
 Stages usually take some data and run some code, producing an output (e.g. an ML
 model). The pipeline is formed by making them interdependent, meaning that the
 output of a stage becomes the input of another, and so on. Technically, this is
 called a _dependency graph_ (DAG).
 
-[gitops]: /doc/use-cases/versioning-data-and-model-files
 [data management]: /doc/start/data-management
 [metrics]: /doc/command-reference/metrics
 [plots]: /doc/user-guide/visualizing-plots