Updated the basic samples README (#129)

* Updated the basic samples README

Fixed a link. Clarified YAML vs TAR format for workflow specification. Made other textual improvements.

* Changed values for sample parameters

samples/basic/README.md

@@ -1,16 +1,30 @@
-## Compile
-Follow [README.md](https://github.com/kubeflow/pipelines/blob/master/samples/README.md) to install the compiler and 
-compile the sample python into workflow yaml. 
 
-"sequential.yaml" is pre-generated for referencing purpose.
+
+This page tells you how to use the _basic_ sample pipelines contained in the repo.
+
+## Compile the pipeline specification
+
+Follow the guide to [building a pipeline](https://github.com/kubeflow/pipelines/wiki/Build-a-Pipeline) to install the Kubeflow Pipelines SDK and compile the sample Python into a workflow specification. The specification takes the form of a YAML file compressed into a `.tar.gz` file. 
+
+For convenience, you can download a pre-compiled, compressed YAML file containing the
+specification of the `sequential.py` pipeline. This saves you the steps required
+to compile and compress the pipeline specification:
+[sequential.tar.gz](https://storage.googleapis.com/sample-package/sequential.tar.gz)
 
 ## Deploy
-Open Pipelines UI, Follow the wizard to create a new pipeline and upload the generated workflow yaml.
+
+Open the Kubeflow pipelines UI, and follow the prompts to create a new pipeline and upload the generated workflow
+specification, `my-pipeline.tar.gz` (example: `sequential.tar.gz`).
 
 ## Run
-Follow the pipeline UI to create pipeline runs. The parameter value for "exit_handler" and "sequential" samples can 
-be "gs://ml-pipeline/shakespeare1.txt". The parameter values for "parallel_join" can be "gs://ml-pipeline/shakespeare1.txt"
-and "gs://ml-pipeline/shakespeare2.txt".
 
-## Components Source
+Follow the pipeline UI to create pipeline runs. 
+
+Useful parameter values:
+
+* For the "exit_handler" and "sequential" samples: `gs://ml-pipeline-playground/shakespeare1.txt`
+* For the "parallel_join" sample: `gs://ml-pipeline-playground/shakespeare1.txt` and `gs://ml-pipeline-playground/shakespeare2.txt`
+
+## Components source
+
 All samples use pre-built components. The command to run for each container is built into the pipeline file.