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Extracting information with corresponding fields

Data Science Asked by user10351235 on June 24, 2021

I have large pool of scanned county documents. I need to extract information like document title, borrower name&address, lender name&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

One Answer

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:

  1. Train a new entity type for each.
  2. 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.

Answered by oneextrafact on June 24, 2021

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