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Dependency Parsing
Steven Bird edited this page Jul 8, 2014
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Dependency parsing is a popular approach to natural language parsing. NLTK includes some basic algorithms, but we need more reference implementations and more corpus readers.
Existing functionality is in the parse package. It includes:
- projective dependency parser (similar to Eisner 1996) and probabilistic projective dependency parser (Eisner 1996 Model C), projectivedependencyparser.py
- non-projective dependency parser and probabilistic non-projective dependency parser (still includes diagnostic print statements?), nonprojectivedependencyparser.py
- interface to the MaltParser, malt.py
- corpus reader for the CoNLL 2007 shared task, and for a 10% sample of the dependency version of the Penn Treebank, dependency.py