Measuring efficiency in high-accuracy, broad-coverage statistical parsing
<|reference_start|>Measuring efficiency in high-accuracy, broad-coverage statistical parsing: Very little attention has been paid to the comparison of efficiency between high accuracy statistical parsers. This paper proposes one machine-independent metric that is general enough to allow comparisons across very different parsing architectures. This metric, which we call ``events considered'', measures the number of ``events'', however they are defined for a particular parser, for which a probability must be calculated, in order to find the parse. It is applicable to single-pass or multi-stage parsers. We discuss the advantages of the metric, and demonstrate its usefulness by using it to compare two parsers which differ in several fundamental ways.<|reference_end|>
@article{roark2000measuring,
    title={Measuring efficiency in high-accuracy, broad-coverage statistical
  parsing},
    author={Brian Roark and Eugene Charniak},
    journal={Proceedings of the COLING 2000 Workshop on Efficiency in
  Large-Scale Parsing Systems, 2000, pages 29-36},
    year={2000},
    archivePrefix={arXiv},
    eprint={cs/0008027},
    primaryClass={cs.CL}
}