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An efficient memory-based morphosyntactic tagger and parser for Dutch
Antal Van den Bosch, Bertjan Busser, Sander Canisius and Walter Daelemans
In:
Computational Linguistics in the Netherlands 2006: Selected papers from the seventeenth CLIN meeting
(2007)
OTS
, Utrecht, Netherlands
, .
AbstractWe describe TADP OL E, a modular memory-based morphosyntactic tagger and dependency
parser for Dutch. Though primarily aimed at being accurate, the design of the system is
also driven by optimizing speed and memory usage, using a trie-based approximation of
k-nearest neighbor classification as the basis of each module. We perform an evaluation
of its three main modules: a part-of-speech tagger, a morphological analyzer, and a depen-
dency parser, trained on manually annotated material available for Dutch – the parser is
additionally trained on automatically parsed data. A global analysis of the system shows
that it is able to process text in linear time close to an estimated 2,500 words per second,
while maintaining sufficient accuracy.
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