Prepositional Phrase Attachment in Shallow Parsing
Vincent Van Asch and Walter Daelemans
In: 7th International Conference on Recent Advances in Natural Language Processing, 14-16 Sep 2009, Borovets, Bulgaria.
In this paper we extend a shallow parser with
prepositional phrase attachment. Although the
PP attachment task is a well-studied task in a
discriminative learning context, it is mostly ad-
dressed in the context of articial situations like
the quadruple classication task in which
only two possible attachment sites, each time
a noun or a verb, are possible. In this pa-
per we provide a method to evaluate the task
in a more natural situation, making it possible
to compare the approach to full statistical pars-
ing approaches. First, we show how to extract
anchor-pp pairs from parse trees in the GENIA
and WSJ treebanks. Next, we discuss the exten-
sion of the shallow parser with a PP-attacher.
We compare the PP attachment module with
a statistical full parsing approach and ana-
lyze the results. More specically, we investi-
gate the domain adaptation properties of both
approaches (in this case domain shifts between
journalistic and medical language).