python – 滥用nltk的word_tokenize(已发送)的后果

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

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.

底层tokenize方法本身非常简单：

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.

（编辑：安卓应用网）

【声明】本站内容均来自网络，其相关言论仅代表作者个人观点，不代表本站立场。若无意侵犯到您的权利，请及时与联系站长删除相关内容!