I think what you're interested in should be possible, but it will likely be a combination of a relatively simple regression model for the financials, with some features predicted from the unstructured text. So there's an interplay between two models there: someone will need to be designing the trade-off between what you can get out of the text accurately and easily, and what information is actually useful in the pricing model. I think the project will require a lot of domain expertise combined with some amount of prior NLP experience.
For example, you might find that sellers with certain demographic features often have underpriced listings ("a little old lady who just drove to church on Sundays), but simultaneously, savy sellers try to pose as these groups. Maybe something in the text gives this away, and you can figure out to remove the misleading demographic information for those listings. Maybe. But maybe there are no cases like this where the text features help, or you're unable to predict the feature accurately even if you can think of it.
I really can't say whether the project will be successful, but I think Prodigy would be a good tool for the NLP component, as it's well suited for rapid development.