Extracting target information from free text

I am fairly new to the world of machine learning, although I have been a Python programmer for many years. I am making this quetsion because i have been researching this problem for hours and still haven’t foudn an answer. Probably because I am not familiar with the field enough to ask the question the right way.

I have a dataset of about 80.000 major shareholder announcements. These are basically articles about X entity now posessing Y amount of shares in a public company. I also have the text I would like to find in the announcements in a structured format (the entity and the amount of shares in an excel). If needed, I could pinpoint the position of these target texts in the announcements.

My question is, what machine learning approach is the best to train a model which could attempt to find the entitiy (person, company, fund etc) and the amount of shares they now own in an announcement? What is the route taken with these types of problems?