Evaluating information extraction from structured documents
I have worked with Structured text using OCR. OCR is prone to errors even while reading the content and a slight change in string arrangement would lead to false positives. I used Cosine Similarity and LEvenstein distance. I curated the data with pip install ftfy, Flashtext fuzzywuzzy ,chardet and set a threshold of 97% giving with 2% buffer for errors which might be unintentional/Typos or Inability of OCR to read the character etc. With this approach you are just relaxing on the 2% error and you can still use the same Precision, Recall or Specificity and Accuracy metrics. And we based on new data, you can gather observations and adjust your threshold on run time. And yes, Make your threshold configurable than hard coded which will be easier to run multiple experiments.

I hope this helps.