Introduction to Special Issue on Machine Learning Approaches to Shallow Parsing
James Hammerton, Miles Osborne, Susan Armstrong, Walter Daelemans;
2(Mar):551-558, 2002.
Abstract
This article introduces the problem of partial or shallow parsing
(assigning partial syntactic structure to sentences) and explains why
it is an important natural language processing (NLP) task. The
complexity of the task makes Machine Learning an attractive option in
comparison to the handcrafting of rules. On the other hand, because of the
same task complexity, shallow parsing makes an excellent benchmark
problem for evaluating machine learning algorithms. We sketch the
origins of shallow parsing as a specific task for machine learning of
language, and introduce the articles accepted for this special issue,
a representative sample of current research in this area. Finally,
future directions for machine learning of shallow parsing are
suggested.
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