如何使用 Python 提取特定单词周围的当前句子和周围句子？答案

【问题标题】：How extract the current sentence and surrounding sentences around a particular word with Python?如何使用 Python 提取特定单词周围的当前句子和周围句子？
【发布时间】：2021-07-16 01:05:21
【问题描述】：

有没有办法让句子中任何选定单词周围的句子。假设我们的目标是获取下面示例中包含单词“Champion”的当前句子以及围绕它的前后句子，无论它们的位置、标签或单词 Champion 重复了多少次。

text = "This is sentence 1. We are the champions. This is sentence 3. This is sentence 4. This is sentence 5. You are champions too."

在上面的例子中，单词 Champion 在句子 2 和 6 中重复出现。所以我们想要发送 1、2、3、5、6 并排除发送 4。

我们如何使用 Spacy 或其他工具来实现这一目标？

【问题讨论】：

标签： python-3.x nlp spacy

【解决方案1】：

您可以只使用re.split 分割标点符号，确定哪些句子包含该单词，然后抓取任何与该句子匹配或与该句子相邻的索引。

>>> import re    
>>> text = "This is sentence 1. We are the champions. This is sentence 3. This is sentence 4. This is sentence 5. You are champions too."
>>> sentences = sentences = re.split('[\.\!\?] *',text)[:-1]
>>> sentences
['This is sentence 1', 'We are the champions', 'This is sentence 3', 'This is sentence 4', 'This is sentence 5', 'You are champions too']
>>> champion_indices = set(
    [
      i for i in range(len(sentences))
      if 'champions' in sentences[i].casefold()]
    )
>>> champion_indices
{1, 5}
>>> champion_adjacent_sentences = [
      sentences[i] for i in range(len(sentences))
      if (i - 1 in champion_indices
         or i in champion_indices
         or i+1 in champion_indices)]
>>> champion_adjacent_sentences
['This is sentence 1', 'We are the champions', 'This is sentence 3', 'This is sentence 5', 'You are champions too']

这里唯一可能不熟悉的是casefold 的使用，这是一种巧妙的方法，可以将两个字符串小写以便对它们进行不区分大小写的比较。

【讨论】：

【解决方案2】：

使用这个函数会给出周围的句子。

from nltk.tokenize import sent_tokenize
from nltk.tokenize import word_tokenize

def surrounding_sentences(text, word):

    sentences=sent_tokenize(text)
    
    my_sents=[]
    for i in range(len(sentences)):
        if word in word_tokenize(sentences[i].lower()): 
            if i-1>0 : 
                previous_sent = sentences[i-1]
                my_sents.append(previous_sent)
            else: pass
            sent= sentences[i]
            my_sents.append(sent)
            if i+1 < len(sentences):
                nextsent = sentences[i+1]
                my_sents.append(nextsent)
            else: pass
    my_sents = list(set(my_sents))
    return my_sents

【讨论】：