Corpus Based PP Attachment Ambiguity Resolution with a Semantic Dictionary
Jiri Stetina, Makoto Nagao · 1997
This paper deals with two important ambiguities of natural language: prepositional phrase attachment and word sense ambiguity. We propose a new supervised learning method for PPattachment based on a semantically tagged corpus. Because any sufficiently big sense-tagged corpus does not exist, we also propose a new unsupervised context based word sense disambiguation algorithm which amends the training corpus for the PP attachment by word sense tags. We present the results of our approach and evaluate the achieved PP attachment accuracy in comparison with other methods.