在项目符号和编号处拆分句子? [英] Split Sentences at Bullets and Numbering?

问题描述

我正在尝试将文本输入到文字处理器中，然后先将其拆分为句子，然后再分解为单词.

I am trying to input text into my word processor to be split into sentences first and then into words.

一个示例段落:

When the blow was repeated,together with an admonition in
childish sentences, he turned over upon his back, and held his paws in a peculiar manner.

1) This a numbered sentence
2) This is the second numbered sentence

At the same time with his ears and his eyes he offered a small prayer to the child.

Below are the examples
- This an example of bullet point sentence
- This is also an example of bullet point sentence

我尝试了以下代码

from nltk.tokenize import TweetTokenizer, sent_tokenize

tokenizer_words = TweetTokenizer()
tokens_sentences = [tokenizer_words.tokenize(t) for t in 
nltk.sent_tokenize(input_text)]
print(tokens_sentences)

import nltk

sent_text = nltk.sent_tokenize(text) # this gives us a list of sentences
# now loop over each sentence and tokenize it separately
for sentence in sent_text:
    tokenized_text = nltk.word_tokenize(sentence)
    print(tokenized_text)

我得到的输出

[
['When', 'the', 'blow', 'was', 'repeated', ',', 'together', 'with', 'an', 'admonition', 'in', 'childish', 'sentences', ',', 'he', 'turned', 'over', 'upon', 'his', 'back', ',', 'and', 'held', 'his', 'paws', 'in', 'a', 'peculiar', 'manner', '.'], 
['1', ')', 'This', 'a', 'numbered', 'sentence', '2', ')', 'This', 'is', 'the', 'second', 'numbered', 'sentence','At', 'the', 'same', 'time', 'with', 'his', 'ears', 'and', 'his', 'eyes', 'he', 'offered', 'a', 'small', 'prayer', 'to', 'the', 'child', '.']
['Below', 'are', 'the', 'examples', '-', 'This', 'an', 'example', 'of', 'bullet', 'point', 'sentence',
'-', 'This', 'also','an', 'example', 'of', 'bullet', 'point', 'sentence']
]

必需的输出

[
['When', 'the', 'blow', 'was', 'repeated', ',', 'together', 'with', 'an', 'admonition', 'in', 'childish', 'sentences', ',', 'he', 'turned', 'over', 'upon', 'his', 'back', ',', 'and', 'held', 'his', 'paws', 'in', 'a', 'peculiar', 'manner', '.'], 
['1', ')', 'This', 'a', 'numbered', 'sentence']
['2', ')', 'This', 'is', 'the', 'second', 'numbered', 'sentence']
['At', 'the', 'same', 'time', 'with', 'his', 'ears', 'and', 'his', 'eyes', 'he', 'offered', 'a', 'small', 'prayer', 'to', 'the', 'child', '.']
['Below', 'are', 'the', 'examples']
['-', 'This', 'an', 'example', 'of', 'bullet', 'point', 'sentence']
['-', 'This', 'also','an', 'example', 'of', 'bullet', 'point', 'sentence']
]

如何在项目符号和编号"处拆分句子?

关于spaCy的解决方案也将非常有帮助

Solutions on spaCy also would be very helpful

推荐答案

这可以解决.您可以根据自己的数据进行自定义

this can be a solution. you can customize it according to your data

text = """When the blow was repeated,together with an admonition in
childish sentences, he turned over upon his back, and held his paws in a peculiar manner.

1) This a numbered sentence
2) This is the second numbered sentence

At the same time with his ears and his eyes he offered a small prayer to the child.

Below are the examples
- This an example of bullet point sentence
- This is also an example of bullet point sentence"""



import re
import nltk

sentences = nltk.sent_tokenize(text)
results = []

for sent in sentences:
    sent = re.sub(r'(\n)(-|[0-9])', r"\1\n\2", sent)
    sent = sent.split('\n\n')
    for s in sent:
        results.append(nltk.word_tokenize(s))

results

[
['When', 'the', 'blow', 'was', 'repeated', ',', 'together', 'with', 'an', 'admonition', 'in', 'childish', 'sentences', ',', 'he', 'turned', 'over', 'upon', 'his', 'back', ',', 'and', 'held', 'his', 'paws', 'in', 'a', 'peculiar', 'manner', '.'], 
['1', ')', 'This', 'a', 'numbered', 'sentence']
['2', ')', 'This', 'is', 'the', 'second', 'numbered', 'sentence']
['At', 'the', 'same', 'time', 'with', 'his', 'ears', 'and', 'his', 'eyes', 'he', 'offered', 'a', 'small', 'prayer', 'to', 'the', 'child', '.']
['Below', 'are', 'the', 'examples']
['-', 'This', 'an', 'example', 'of', 'bullet', 'point', 'sentence']
['-', 'This', 'also','an', 'example', 'of', 'bullet', 'point', 'sentence']
]

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