A better N-best list
Jonathan May, Kevin K. Knight · 2006
Ranked lists of output trees from syntactic statistical NLP applications frequently contain multiple repeated entries. This redundancy leads to misrepresentation of tree weight and reduced information for debugging and tuning purposes. It is chiefly due to nondeterminism in the weighted automata that produce the results. We introduce an algorithm that determinizes such automata while preserving proper weights, returning the sum of the weight of all multiply derived trees. We also demonstrate our algorithm's effectiveness on two large-scale tasks.