[精通Python自然語言處理] Ch1 - 將句子切分為單詞

實驗對比了一下三種切分方式：

1,2 : nltk.word_tokenize :  分離縮略詞，(“Don't” =>'Do', "n't"） 表句子切分的“,” "." 單獨成詞。

3 :  TreebankWordTokenizer: 分離縮略詞， 表句子切分的 “,"單獨成詞，句號“.”被刪去。

4 : PunktWordTokenizer: 報錯： cannot import name 'PunktWordTokenizer'

5 : WordPunctTokenizer: 將標點轉化為全新標識符實現切分。(“Don't” =>'Don', "'", 't')

import nltk
text = "We're excited to let you know that. Harry, 18 years old, will join us on Nov. 29. Don't tell him."

text_tokenized = nltk.word_tokenize(text)
print("1: word_tokenize:", text_tokenized)
print("length: ", len(text_tokenized))

from nltk import word_tokenize
text_tokenized_2 = word_tokenize(text)
print("2: word_tokenize:", text_tokenized_2)
print("length: ", len(text_tokenized_2))

from nltk.tokenize import TreebankWordTokenizer
tokenizer3 = TreebankWordTokenizer()
text_tokenized_3 = tokenizer3.tokenize(text)
print("3: TreebankWordTokenizer", text_tokenized_3)
print("length: ", len(text_tokenized_3))

# from nltk.tokenize import PunktWordTokenizer
# tokenizer4 = PunktWordTokenizer()
# text_tokenized_4 = tokenizer4.tokenize(text)
# print("4: PunktWordTokenizer", text_tokenized_4)
# print("length: ", len(text_tokenized_4))

from nltk.tokenize import WordPunctTokenizer
tokenizer5 = WordPunctTokenizer()
text_tokenized_5 = tokenizer5.tokenize(text)
print("5: WordPunctTokenizer", text_tokenized_5)
print("length: ", len(text_tokenized_5))

輸出：

1: word_tokenize: ['We', "'re", 'excited', 'to', 'let', 'you', 'know', 'that', '.', 'Harry', ',', '18', 'years', 'old', ',', 'will', 'join', 'us', 'on', 'Nov.', '29', '.', 'Do', "n't", 'tell', 'him', '.']
length:  27
2: word_tokenize: ['We', "'re", 'excited', 'to', 'let', 'you', 'know', 'that', '.', 'Harry', ',', '18', 'years', 'old', ',', 'will', 'join', 'us', 'on', 'Nov.', '29', '.', 'Do', "n't", 'tell', 'him', '.']
length:  27
3: TreebankWordTokenizer ['We', "'re", 'excited', 'to', 'let', 'you', 'know', 'that.', 'Harry', ',', '18', 'years', 'old', ',', 'will', 'join', 'us', 'on', 'Nov.', '29.', 'Do', "n't", 'tell', 'him', '.']
length:  25
5: WordPunctTokenizer ['We', "'", 're', 'excited', 'to', 'let', 'you', 'know', 'that', '.', 'Harry', ',', '18', 'years', 'old', ',', 'will', 'join', 'us', 'on', 'Nov', '.', '29', '.', 'Don', "'", 't', 'tell', 'him', '.']
length:  30