P04-1080 1 gives out our feature subset evaluation algorithm . If some features in feature
A83-1027 problem arose in designing the evaluation algorithm . By higher order property we
N07-1059 designed our interlingua-based evaluation algorithm following these two principles
J01-2003 system . The first step of the evaluation algorithm , alignment , determines which
J00-2001 though , the second phase of the evaluation algorithm modifies the ratings based on
N04-4012 Our formalism and the associated evaluation algorithm work closely with a dialogue
H05-1117 assessing the quality of an automatic evaluation algorithm . Correlation between official
A00-2043 special path finding and path evaluation algorithm specified in Markert and Hahn
J92-2002 grammars for which terminating evaluation algorithms are known , we can implement
C02-1079 advantage of a fast and efficient evaluation algorithm . For instance , ( Caraballo
W06-0401 each combination of input and evaluation algorithm . 4.3 Input sentences To test
J00-2001 sequence . The linguistic option evaluation algorithm . anything in the plan , so the
W06-0401 Gapping sen - tences . 4 Testing the evaluation algorithms To test the predictions of the
W06-0401 psycholinguistic study , the four evaluation algorithms yielded identical results . These
J00-2001 annotations lead the first phase of the evaluation algorithm to rate the option as HIGH ;
W06-0401 By applying one of these four evaluation algorithms , the computational model yields
J02-1002 gold standard " and to develop an evaluation algorithm that suits all applications reasonably
J00-2001 also runs the first phase of the evaluation algorithm ( described in Figure 4 ) to
W01-1612 affected either , because common evaluation algorithms for anaphor annotations ( Vilain
W06-0401 different predictions Because the four evaluation algorithms behaved identically on all sentences
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