Extracting information with corresponding fields I have large pool of scanned county documents. I need to extract information like document title, borrower name&amp;address, lender name&amp;address etc. 

The text is like this 
Eg: the deed of trust, between abc llc, a limited company, whose address is XXXXXX, herein called "borrower", and  xyz, whose address is XXXXX,herein called "lender".

I used Named entity recognition method to  extract the names, it works well. but how would i know which name is borrower and which one is lender? can anyone help me
you’re definitely on the right track with NER. As for determining the ‘class’ of what you’ve extracted, I think you have two major options:


Train a new entity type for each. 
Use a set of rules that examine the term in context to determine the class. 


I think you might have more luck with 2, if the language surrounding the terms is pretty static. Also, I haven’t watched it yet, but I thought this might help as well - seems to be about exactly your problem domain. https://www.youtube.com/watch?v=KrXJmaSHBJU.