Measuring efficiency in high-accuracy, broad-coverage statistical parsing

Simple item page
dc.creatorRoark, Brian
dc.creatorCharniak, Eugene
dc.date2000-08-24
dc.date.accessioned2026-07-07T03:16:30Z
dc.date.available2026-07-07T03:16:30Z
dc.descriptionVery 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.
dc.description8 pages, 4 figures, 2 tables
dc.identifierhttps://arxiv.org/abs/cs/0008027
dc.identifierhttp://arxiv.org/abs/cs/0008027
dc.identifierProceedings of the COLING 2000 Workshop on Efficiency in Large-Scale Parsing Systems, 2000, pages 29-36
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30375
dc.subjectComputation and Language
dc.subjectI.2.7
dc.titleMeasuring efficiency in high-accuracy, broad-coverage statistical parsing
dc.typetext

Files

Collections

arXiv