[mikecapizzi]

If you're looking for a tool that allows you to incorporate legitimate NLP approaches, you should have a look at `odin`. Here's a paper https://doi.org/10.1093/database/bay098 showing its usage in the medical domain.

And the code is open-sourced as part of the `processors` library out of the CLULab at the University of Arizona: https://github.com/clulab/processors

The most detailed (though not completely up-to-date) documentation is probably in the manual here: https://arxiv.org/abs/1509.07513

I'm using it at my current job to build an analysis tool for customer-agent phone calls.

It allows you to build rules that match on different levels of abstraction: tokens, pos-tags, dependency paths. You can even match tokens based on word similarity (as measured by cosine similarity of word vectors).

And these rules can "cascade" (i.e. build off of each other). So you can find an entity or event in rule 1 and then look for how that interacts with another matched entity or event in a later rule.