Nlp 在项目符号和编号处拆分句子？

我试着把文字输入文字处理器，先把文字分成句子，然后再分成文字

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)

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']
]

[
['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']
]

所需输出

[
['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']
]

[
['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？

---

spaCy的解决方案也会很有帮助

我不确定spaCy的情况。在Ruby中，您可以使用和

text="当重击的时候,再加上孩子气的训诫,他翻了个身,，以一种特殊的方式握住爪子。\n\n1）这是一个编号的句子\n2）这是第二个编号的句子\n\n同时他用耳朵和眼睛向孩子做了一个小小的祈祷。\n\n下面是例子\n-这是一个要点句的例子\n-这也是一个要点句的例子“
最终_数组=[]
segments=practicsegmenter:：Segmenter.new（文本：text）.segment
分段。每个do |分段|
final_array这可以是一个解决方案。您可以根据您的数据进行自定义

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']
]

这是一个python端口：尝试了上面的python端口，但它给了我奇怪的结果。它可以用任何其他python方法解决吗