  This paper examines efficient predictive broad-coverage parsing without
dynamic programming. In contrast to bottom-up methods, depth-first top-down
parsing produces partial parses that are fully connected trees spanning the
entire left context, from which any kind of non-local dependency or partial
semantic interpretation can in principle be read. We contrast two predictive
parsing approaches, top-down and left-corner parsing, and find both to be
viable. In addition, we find that enhancement with non-local information not
only improves parser accuracy, but also substantially improves the search
efficiency.
