Developing a chunker using pos-tagged corpora
Chunking is the process used to perform entity detection. It is used for the segmentation and labeling of multiple sequences of tokens in a sentence.
To design a chunker, a chunk grammar should be defined. A chunk grammar holds the rules of how chunking should be done.
Let's consider the example that performs Noun Phrase Chunking by forming the chunk rules:
>>> import nltk >>> sent=[("A","DT"),("wise", "JJ"), ("small", "JJ"),("girl", "NN"), ("of", "IN"), ("village", "N"), ("became", "VBD"), ("leader", "NN")] >>> sent=[("A","DT"),("wise", "JJ"), ("small", "JJ"),("girl", "NN"), ("of", "IN"), ("village", "NN"), ("became", "VBD"), ("leader", "NN")] >>> grammar = "NP: {<DT>?<JJ>*<NN><IN>?<NN>*}" >>> find = ...Get Natural Language Processing: Python and NLTK now with the O’Reilly learning platform.
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