The widely-used Brill Tagger attempts to address this bottleneck by automatically acquiring and inferring rules for POS tagging from a running text, and its accuracy has been comparable to that of probabilistic taggers (Brill, 1992).
more pre-annotated data than is typically available for lesser-resourced languages is still required for this approach, and so again it boils down to a decision (costly either way) between crafting enough rules or annotating sufficient training data by hand.