tech,13-3-H01-1041,bq </term> include : ( i ) Robust efficient <term> parsing </term> of <term> Korean </term> ( a <term> verb
other,29-2-P01-1007,bq without increasing their <term> worst-case parsing time complexity </term> . For example , after
tech,7-4-P01-1007,bq </term> . In this paper , we study a <term> parsing technique </term> whose purpose is to improve
other,1-5-P01-1007,bq parsers </term> . The <term> non-deterministic parsing choices </term> of the <term> main parser </term>
other,23-9-J05-1003,bq of the feature space </term> in the <term> parsing data </term> . Experiments show significant
tech,8-12-J05-1003,bq this article are on <term> natural language parsing ( NLP ) </term> , the <term> approach </term>
tech,9-1-C82-1054,bq of modifications to the <term> left corner parsing algorithm </term> for <term> context-free grammars
tech,1-1-P84-1047,bq entity-oriented approach to restricted-domain parsing </term> is proposed . In this approach ,
tech,11-4-P84-1047,bq recognition </term> and the use of <term> multiple parsing strategies </term> , and so is particularly
other,21-6-P84-1047,bq entity-oriented parser </term> , some <term> parsing strategies </term> that use the <term> control
other,8-7-P84-1047,bq <term> control structure </term> and the <term> parsing strategies </term> is currently under <term>
tech,7-2-J86-1002,bq </term> is done by strongly biasing <term> parsing </term> toward expected <term> meanings </term>
tech,0-1-C88-2132,bq analysis of our <term> corpus </term> . <term> Chart parsing </term> is <term> directional </term> in the
tech,28-3-A92-1026,bq technique called <term> terminal substring parsing </term> . For <term> pragmatics processing </term>
tech,6-1-A92-1027,bq algorithm for <term> chart-based phrase structure parsing </term> of <term> natural language </term> that
tech,8-1-C92-2068,bq expensive part of <term> unification-based grammar parsing </term> . We focus on one speed-up element
tech,1-2-C92-3165,bq understanding </term> . The <term> generalized LR parsing </term> is enhanced in this approach . <term>
tech,10-5-H92-1026,bq best existing robust <term> probabilistic parsing models </term> , which we call <term> P-CFG
measure(ment),28-5-H92-1026,bq <term> P-CFG </term> , increasing the <term> parsing accuracy </term> rate from 60 % to 75 % ,
other,1-2-H92-1060,bq analysis </term> fails . This <term> robust parsing capability </term> was achieved through minor
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