types of chunking there are two types of chunking the types are as followschunking up in this process of chunkingthe objectthingsetc move towards being more general and the language gets more abstract there are more chances of agreement in this processwe zoom out for exampleif we will chunk up the question that "for what purpose cars are"we may get the answer "transportchunking down in this process of chunkingthe objectthingsetc move towards being more specific and the language gets more penetrated the deeper structure would be examined in chunking down in this processwe zoom in for exampleif we chunk down the question "tell specifically about car"we will get smaller pieces of information about the car example in this examplewe will do noun-phrase chunkinga category of chunking which will find the noun phrases chunks in the sentenceby using the nltk module in pythonfollow these steps in python for implementing noun phrase chunkingstep in this stepwe need to define the grammar for chunking it would consist of the rules which we need to follow step in this stepwe need to create chunk parser it would parse the grammar and give the output step in this last stepthe output is produced in tree format let us import the necessary nltk package as followsimport nltk nowwe need to define the sentence heredt means the determinantvbp means the verbjj means the adjectivein means the preposition and nn means the noun sentence [(" ""dt"),("clever""jj"),("fox","nn"),("was","vbp"),("jumping","vbp"),("over","in"),("the","dt"),"wall","nn")nowwe need to give the grammar herewe will give the grammar in the form of regular expression grammar "np:{?*}we need to define parser which will parse the grammar parser_chunking=nltk regexpparser(grammar