An Empirical Comparison of Parsing Methods for Stanford Dependencies
Table 2: CCprocessed SD parsing performance. Since converting to CCprocessed SD requires labeled dependencies, EasyFirst and Huang do not join in the comparison here. †Charniak-Johnson uses semi-supervised training; Stanford englishPCFG and RNN models use external resources; see text.
['[EMPTY]', 'Type', 'Parser', 'PTB §22 U.\xa0 [ITALIC] F1', 'PTB §22 L.\xa0 [ITALIC] F1', 'PTB §23 U.\xa0 [ITALIC] F1', 'PTB §23 L.\xa0 [ITALIC] F1']
Because the number of attachments in a parser’s CCprocessed output may not equal the number in the gold-standard tree, we follow the convention of reporting F1 scores (unlabeled and labeled). The additional runtime for this transformation is negligible, so we do not report runtimes. The EasyFirst and Huang parsers cannot be evaluated this way, since labeled Basic dependencies are required for the transformation to CCprocessed. The pattern is quite similar to the Basic SD experiment, with the same top performers among c- and d-parsers. The gap between c-parsing and d-parsing is 2.6% unlabeled F1 (3.0% labeled).