P09-1022 gives a short introduction to the LFG annotation . Section 4 describes in more
P00-1009 validity of the DOP hypothesis to LFG annotations . We do not yet know whether
P09-1022 dependency-based method using LFG annotation has been successfully employed
P02-1035 absolute F-score . Both the DR and LFG annotations broadly agree in their measure
P10-1111 therefore crucial to the German LFG annotation algorithm , in particular when
P02-1035 LFG fstructures ( henceforth the LFG annotation scheme ) to a gold standard of
P09-1022 dependencies . The treebank-based LFG annotation used in this paper and developed
P06-2018 Spanish . 3 Previous Work 3.1 LFG Annotation A methodology for automatically
J12-2005 one gold-standard and one with LFG annotation . We extend the gold-standard
W04-3223 dependency bank3 , which is an LFG annotation of 700 examples randomly extracted
P09-1022 Charniak-Johnson parser and the LFG annotation , with BE , which uses Minipar
P06-2018 Spanish Treebank As input to our LFG annotation algorithm we use the output of
P06-1063 information ( daughter categories plus LFG annotations ) in the tree in Figure 10 (
P85-1018 a slash category in GPSG or an LFG annotation concerning a matching constituent
P10-1111 and where the coverage of the LFG annotation algorithm drops to 93.62 % with
P06-2018 for MBL vs MaxEnt . 6 Task-Based LFG Annotation Evaluation Finally , we also
W10-1753 collaborators2 first apply the LFG annotation algorithm to the Penn Treebank
P09-1022 the LFG parser which applies the LFG annotation algorithm to the earlier Charniak
P09-1022 extraction is accomplished through an LFG annotation of Cahill et al. ( 2004 ) applied
W10-1753 two respects : 1 ) the inhouse LFG annotation algorithm is not publicly available
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