Parsing Geo Data from text documents

I am currently have a python script that watches a directory and every time a new file shows up, it calls Apache Tika to parse the file. I am parsing a WIDE variety of document types and the script posts the parsed data to the appropriate type in an elastic search index.
My question is:
Is there a way for Elastic search to recognize various geo-coordinates from the parsed text of the various document types and possibly automatically pin them on the Kibana map?

If the coordinates are in a specific field and you use a template/mapping for that field, then yes.

What if they're not? Is there a plugin or anything that could search all of the parsed text for strings that look like geocoords and tag them in a way that they can be recognized as such?

You could try https://github.com/spinscale/elasticsearch-ingest-opennlp

I read the documentation for the repo you linked, but am confused as to what exactly it does.

It uses natural language processing to do entity extraction, an entity in this instance could be a location.

I guess the simple way of putting this is there isn't a really easy way to do this at the moment, unless you want to spend $$$ on a off the shelf solution or spend some time to build something out of base technology like OpenNLP.

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