期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2009
卷号：2009
出版社：ACL Anthology
摘要：A corpus-based technique is described to
improve the efficiency of wide-coverage
high-accuracy parsers. By keeping track
of the derivation steps which lead to the
best parse for a very large collection of
sentences, the parser learns which parse
steps can be filtered without significant
loss in parsing accuracy, but with an important
increase in parsing efficiency. An
interesting characteristic of our approach
is that it is self-learning, in the sense that
it uses unannotated corpora.
