摘要: Many different metrics exist for evaluating parsing results, including Viterbi, Crossing Brackets Rate, Zero and several others. However, most algorithms, the Viterbi algorithm, attempt to optimize same metric, namely probability of getting correct labelled tree. By choosing a algorithm appropriate evaluation better performance can be achieved. We present two new algorithms: "Labelled Recall Algorithm," which maximizes expected Labelled "Bracketed Bracketed Rate. Experimental results are given, showing that algorithms have improved over on many criteria, especially ones they optimize.
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