Python - Parçalar ve Parçalar
Parçalama, benzer kelimeleri, kelimenin doğasına göre bir araya getirme işlemidir. Aşağıdaki örnekte, parçanın oluşturulması gereken bir dilbilgisi tanımlıyoruz. Dilbilgisi, öbekleri oluştururken izlenecek olan isimler ve sıfatlar gibi ifadelerin sırasını önerir. Parçaların resimsel çıktısı aşağıda gösterilmiştir.
import nltk
sentence = [("The", "DT"), ("small", "JJ"), ("red", "JJ"),("flower", "NN"),
("flew", "VBD"), ("through", "IN"), ("the", "DT"), ("window", "NN")]
grammar = "NP: {
?
*
}" cp = nltk.RegexpParser(grammar) result = cp.parse(sentence) print(result) result.draw()
When we run the above program we get the following output −
Changing the grammar, we get a different output as shown below.
import nltk
sentence = [("The", "DT"), ("small", "JJ"), ("red", "JJ"),("flower", "NN"),
("flew", "VBD"), ("through", "IN"), ("the", "DT"), ("window", "NN")]
grammar = "NP: {
?
*
}" chunkprofile = nltk.RegexpParser(grammar) result = chunkprofile.parse(sentence) print(result) result.draw()
When we run the above program we get the following output −
Chinking
Chinking is the process of removing a sequence of tokens from a chunk. If the sequence of tokens appears in the middle of the chunk, these tokens are removed, leaving two chunks where they were already present.
import nltk
sentence = [("The", "DT"), ("small", "JJ"), ("red", "JJ"),("flower", "NN"), ("flew", "VBD"), ("through", "IN"), ("the", "DT"), ("window", "NN")]
grammar = r"""
NP:
{<.*>+} # Chunk everything
}
+{ # Chink sequences of JJ and NN
"""
chunkprofile = nltk.RegexpParser(grammar)
result = chunkprofile.parse(sentence)
print(result)
result.draw()
When we run the above program, we get the following output −
As you can see the parts meeting the criteria in grammar are left out from the Noun phrases as separate chunks. This process of extracting text not in the required chunk is called chinking.