This page describes how to annotate English sentences with AMR graphs to create more training data (perhaps in a new domain) or check the output of your parser.
Step 1: Read the guidelines to learn how AMR works: AMR Guidelines
First, decide the “main” event/verb in the sentence and put that at the top. If sentence is a conjunction of main verbs or is actually a multi-sentence then a conjunction or multi-sentence concept goes at the top.
You'll want to proceed top-down in the AMR. For each content word in the AMR, decide if it's an event, thing or property. Add the lemma to the AMR graph using the editor. If it is an event concept, then click on it and a pop-up will open with the PropBank frame file. Click on the definition you want to use. You'll need to look at the definitions of the arguments of the event to correctly annotate them.
There are many linguistic phenomena you may encounter that are not covered in the annotation guidelines. If you're not sure about how to handle a certain linguistic phenomena, there are two approaches you can employ:
Search in an AMR corpus for words or phrases that exhibit the phenomenon to see how the other annotators have handled it (sometimes annotations may be inconsistent, and this should be resolved through discussion)
If you find a reoccurring phenomena in your domain that isn't handled well in AMR or PropBank, you may need to add more predicates. To do this, you can expand the PropBank lexicon to include predicates in your domain or add more core AMR predicates. Examples: Spatial AMR, Dialogue-AMR, Bio AMR Corpus
To annotate non-English sentences, you'll need a PropBank-style resource of event predicates in that language upon which to build the AMRs. Examples: Xue 2014, Li 2016