NLP用于从文本中提取动作

Question

我希望有人可以指出我正确的方向来学习从一堆文本中分离出行动。

假设我有这个文本

Drop off the dry cleaning, and go to the corner store and pick-up a jug of milk and get a pint of strawberries.
Then, go pick up the kids from school. First, get John who is in the daycare next to the library, and then get Sam who is two blocks away. 
By the time you've got the kids, you'll need to stop by the doctors office for the perscription. Tim's flight arrives at 4pm. 
It's American Airlines flight 331 arriving from Dallas. It will be getting close to rush hour, so make sure you leave yourself enough time.

我正试图把它分成

Drop off the dry cleaning,

 and go to the corner store and pick-up a jug of milk and get a pint of strawberries.

Then, go pick up the kids from school. First, get John who is in the daycare next to the library, and then get Sam who is two blocks away. 

By the time you've got the kids, you'll need to stop by the doctors office for the perscription.

 Tim's flight arrives at 4pm. 
It's American Airlines flight 331 arriving from Dallas. It will be getting close to rush hour, so make sure you leave yourself enough time.

我无法在搜索中找到任何基于操作的内容。它需要比挑选动词更聪明，因为有多个动词有时与一个动作相关联，例如第二个项目有'go'，'pick-up'和'get'，但这就是全部单一行动。当然，“蒂姆的飞行”仅表示与现在分词的动作，动词即将结束。

关于在哪里寻找做这种事情的任何建议？需要注意的事项，推荐阅读等等。

Answer 1

简单的方法：使用[您最喜欢的解析器]解析文本，然后选择处于命令性情绪中的句子或SBAR短语。 Stanford Parser恰好恰好在其最新版本中“改进了对命令的认可”。

除了已经包含在标准解析器程序中的内容之外，可能不需要机器学习。

Answer 2

此域名为Information Extraction。

句子理解的一般方法是：

• 提取词性标记的解析树（Python spaCy.io，nltk，CoreNLP等）
• 提取单词向量（例如word2vec）