Hi @mattdr,
Thanks for your message and welcome to the Prodigy community 
At a glance, nothing seems wrong with your command's syntax.
First, let's check that your model was trained for the labels you're providing. Can you look for the meta.json file in models/model-last? Does it have:
"ner":[
"MODULE",
"LOGISTICS",
"PRODUCT",
"HR",
"POLICY"
]
How's the performance? You can view in the meta.json.
Just curious, how did you train the model? If you could provide the command that would be great.
Did you do it from scratch (i.e., with a blank model) or fine tuning a pretrained pipeline?
If you did fine tuning, you may be dealing with catastrophic forgetting.
Since you're creating a couple of new entity types, you should likely train your model from scratch. We discuss this in the docs and in the Prodigy NER flowchart.
On the 2nd part: "you're not recognizing the sentences".
How did you get the final_dataset.jsonl file? Did you db-out your annotations? You can run prodigy stats dataset_cw to show basic stats.
Does dataset_cw have any overlap with final_dataset.jsonl? Are they 100% same sentences? Do either or both have annotations? Data duplication/hashing may be coming into play.