Natural language processing using Python NLTK package, WILL RATE ASAP E-book: ht

Question

Natural language processing using Python NLTK package, WILL RATE ASAP

E-book: http://victoria.lviv.ua/html/fl5/NaturalLanguageProcessingWithPython.pdf

The strings are two qoutes:

http://www.goodreads.com/quotes/408470-consider-how-common-illness-is-how-tremendous-the-spiritual-change

Considering how common illness is, how tremendous the spiritual change that it brings, how...

and this one

qoute by John Updike: http://www.barnesandnoble.com/blog/7-of-the-most-memorable-long-sentences-in-lit/

But then they were married (she felt awful about being pregnant before but Harry had been ...

2. Consider the following long literary sentences and for each do the following: i) Draw brackets around all the complete sentences ii) Give a set of complete S-level parse trees for each sentence, using the compressed notation described in question 1. You will likely need to add additional recursive rules, including one that allow non- binary conjunctions or that require punctuation (such as commas or semicolons). binary conjunctions or that require punctuation (such as commas or semicolons)

Explanation / Answer

groucho_dep_grammar = nltk.DependencyGrammar.fromstring(""" ... 'shot' -> 'I' | 'elephant' | 'in' ... 'elephant' -> 'an' | 'in' ... 'in' -> 'pajamas' ... 'pajamas' -> 'my' ... """) >>> print(groucho_dep_grammar) Dependency grammar with 7 productions 'shot' -> 'I' 'shot' -> 'elephant' 'shot' -> 'in' 'elephant' -> 'an' 'elephant' -> 'in' 'in' -> 'pajamas' 'pajamas' -> 'my'

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