Unsupervised Pos-Tagging Improves Parsing Accuracy And Parsing Efficiency
Robbert Prins, Gertjan van Noord · 2001
It is shown that a simple POS-tagger can be used to filter the results of lexical analysis of a widecoverage computational grammar. The reduction of the number of lexical categories not only greatly improves parsing efficiency, but in our experiments also gave rise to a mild increase in parsing accuracy; in contrast to results reported in earlier work on supervised tagging. The novel aspect of our approach is that the POS-tagger does not require any human-annotated data - but rather uses the parser output obtained on a large training set.