I am looking for any NLP/ML/Deep learning technique to extract and detect a useful information from a large amount of text data. Specifically, I am focusing on detecting whether a person actually visited a restaurant and eat some food at a specific time.

For example, we may have three different sentences:

• S1. John enjoyed spaghetti at Terranova located in New York City.
• S2. John read an article about Terranova, the best spaghetti restaurant in New York City
• S3. John wanted to eat spaghetti at Terranova when he visited New York City, but he could not.

For these three sentences, my program should be able to detect only S1 that embeds important information related to his actual visit and eating activity at a the restaurant in contrast to S2 and S3 (the S2 and S3 doesn't indicate he actually visited the restaurant.) Additionally, once S1 has been detected, how can I extract specific entities involved person, location, and time information from the sentences?

Could you please recommend any useful tools and algorithms to support this kind of a task?

Thanks!