Abstract
We demonstrate ways to enhance the coverage of a symbolic NLP system through data-intensive and machine learning techniques, while preserving the advantages of using a principled symbolic grammar formalism. We automatically acquire a large syntactic CCG lexicon from the Penn Treebank and combine it with semantic and morphological information from another hand-built lexicon using decision tree and maximum entropy classifiers. We also integrate statistical preprocessing methods in our system.
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Hockenmaier, J., Bierner, G. & Baldridger, J. Extending the Coverage of a CCG System. Research on Language and Computation 2, 165–208 (2004). https://doi.org/10.1023/B:ROLC.0000016736.80096.76
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DOI: https://doi.org/10.1023/B:ROLC.0000016736.80096.76