Yes, an interface for dependency and relationship annotation is definitely very high on our list. In the meantime, you can check out my comments on thread, in which I outline some strategies for making it work with the current interfaces, or how to create your own interface.
So even if it turns out that your requirements are very specific, you'll always be able to mix and match the interfaces and create your own custom workflows. Prodigy makes very little assumptions about your task and simply presents the data in the UI, and stores JSON-formatted annotations.
For example, you could create a custom HTML template to display the annotation task however you like. Or you could repurpose the manual NER annotation interface to annotate POS tags instead of entities. This should work pretty well out-of-the-box for creating gold-standard data – you can simply pass in your POS tag scheme as the labels, annotate your corpus and export the JSON-formatted data.
Annotating nested entities can easily get fiddly, so we'd love to come up with a nice and efficient solution for annotating them. In many cases, it's actually easier (and more efficient!) for the human annotator to make more passes over the data, rather than doing too much at once. So even with the existing interfaces, you could do one round of annotating only the parent entities, e.g. the full date spans. For the second round, you can simply export the dataset and do another pass over the already annotated spans, highlighting only the "children".
(The upcoming version of Prodigy will also include an option to flag annotation tasks, so all the annotator would have to do is highlight the "parent" entity and flag the task if it contains a nested entity, to make it even easier to extract and reannotate the relevant examples.)