What is the default chunker for NLTK toolkit in Python?
You can get out of the box named entity chunking with the nltk.ne_chunk() method.  It takes a list of POS tagged tuples:
nltk.ne_chunk([('Barack', 'NNP'), ('Obama', 'NNP'), ('lives', 'NNS'), ('in', 'IN'), ('Washington', 'NNP')])
results in:
Tree('S', [Tree('PERSON', [('Barack', 'NNP')]), Tree('ORGANIZATION', [('Obama', 'NNP')]), ('lives', 'NNS'), ('in', 'IN'), Tree('GPE', [('Washington', 'NNP')])])
It identifies Barack as a person, but Obama as an organization.  So, not perfect.
I am using their default POS tagging and default tokenization..and it seems sufficient.  I'd like their default chunker too.
I am reading the NLTK toolkit book, but it does not seem like they have a default chunker?