I have a massive text block of poorly written statements, some facts, some opinions. It's all scraped from various public internet resources and all in english.
I am now using nltk in python to try to work out some basic statements from this massive text block.
My goal is not to capture all statements, false positives are not too bad either. I would simply like to get a few probably true and simple assertions from this text block.
Bob is married to Lisa since 1983.
Lisa's cat Snowball died two years ago.
Bob and Lisa has a 30 year old son named George.
From these simple sentences, I would like to parse out some simple facts, like:
"Bob is married", "Lisa is married", "George is Lisa's son", "George is Bobs son", "Snowball is a cat"
It does not need to be exactly this.
What is this kind of processing called? (Except for that it is a subcategory of Natural Language Processing.)
What are the simpler and the harder approaches to this problem?
How well has this problem been solved by public and proprietary algorithms?