我试图将一个段落分成单词.我手头有可爱的nltk.tokenize.word_tokenize(发送),但是帮助(word_tokenize)说,“这个标记器设计用于一次一个句子.”
有没有人知道如果你在一个段落上使用它会发生什么,即最多5个句子呢？我自己尝试了一些简短的段落,似乎有效,但这几乎不是确凿的证据.
解决方法
nltk.tokenize.word_tokenize(text)只是一个瘦的
wrapper function,它调用
TreebankWordTokenizer类实例的tokenize方法,它显然使用简单的正则表达式来解析一个句子.
该类的文档声明：
This tokenizer assumes that the text has already been segmented into
sentences. Any periods — apart from those at the end of a string —
are assumed to be part of the word they are attached to (e.g. for
abbreviations,etc),and are not separately tokenized.
def tokenize(self,text):
for regexp in self.CONTRACTIONS2:
text = regexp.sub(r'\1 \2',text)
for regexp in self.CONTRACTIONS3:
text = regexp.sub(r'\1 \2 \3',text)
# Separate most punctuation
text = re.sub(r"([^\w\.\'\-\/,&])",r' \1 ',text)
# Separate commas if they're followed by space.
# (E.g.,don't separate 2,500)
text = re.sub(r"(,\s)",r' \1',text)
# Separate single quotes if they're followed by a space.
text = re.sub(r"('\s)",text)
# Separate periods that come before newline or end of string.
text = re.sub('\. *(\n|$)',' . ',text)
return text.split()
基本上,该方法通常做的是将句点标记为单独的标记,如果它落在字符串的末尾：
>>> nltk.tokenize.word_tokenize("Hello,world.")
['Hello',','world','.']
落在字符串中的任何句点都被标记为单词的一部分,假设它是缩写：
>>> nltk.tokenize.word_tokenize("Hello,world. How are you?")
['Hello','world.','How','are','you','?']
只要这种行为是可以接受的,你应该没事.