使用nltk从文本中提取操作/任务

嗨我第一次使用nltk,我想使用nltk从文本中提取动作/任务

Hi prakash, how are you ?. We need to complete the speech to action by 8 June  then you will have to finish the UI by 15 july

在这里,演讲与行动和UI 是行动.

我已经开始创建令牌,不知道下一步该做什么,请指导.

from nltk import sent_tokenize
sample_text ="""Hi prakash, how are you ?. We need to complete the speech to action demo by 8 June  then you will have to finish the Ui by 15 july"""
sentences = sent_tokenize(sample_text)
print(sentences)    import nltk
from nltk.tag import pos_tag
from nltk.tokenize import word_tokenize

sample_text = """Hi prakash, how are you ?. We need to complete the speech to action by today
then you will have to finish the UI by 15 july after that you may go finish the mobile view"""
sample_text = "need to complete the speech to action by today"
tokens = word_tokenize(sample_text.lower())
# the lower is very much required, as June and june have diffrent code NN, NNP

pos_tags = pos_tag(tokens)

result = []
for i in range(len(tokens)):
    if (pos_tags[i][1] == 'VB') and (pos_tags[i][0] in ['complete','finish']):
        # Here we are looking for text like (finish, complete, done)
        owner = ''
        for back_tag in  pos_tags[:i][::-1]:
            #traverse in back direction to know the owner who will (finish, complete, done)
            if back_tag[1]=='PRP':
                owner = back_tag[0]
                break

        message = ''
        date = ''
        for messae_index , token in enumerate(pos_tags[i:],i):
            #traverse forward to know what has to be done
            if token[1]=='IN':
                for date_index, date_lookup in  enumerate(pos_tags[messae_index:],messae_index):
                    if date_lookup[1]=='NN':
                        date = pos_tags[date_index-1][0] + ' ' + pos_tags[date_index][0]
                    if date_lookup[1]=='PRP':
                        # This is trick to stop further propegation
                        # Don't ask me why i am doing this, if you are still reading then read the nest line
                        # Save futher interation as the next sentance is i/we/you
                        break
                break
            else:
                message = message + ' ' + token[0]
        result += [dict(owner=owner, message=message, date=date)]
print(result)

请指导如何从段落中提取动作(动作演示,UI).

如果你正在使用NLTK,你可以获得你的令牌的POS标签,并使用这些标签提出正则表达式或模式.例如,动作将是动词.(为了更好的标记,您可能需要Spacy.还有另一个库Pattern用于这些目的)

但我不确定这是否会对缩放应用程序有很大帮助.

注意:有训练有素的命名实体识别器,您可以试试.