Much of my work involves improving large-scale systems to extract political events from text (see code from our NSF project on the subject here). These systems are designed for full production use over many hundreds of sources both daily and for the past in many dozens of event categories, including protests, armed conflict, statements, arrests, and humanitarian aid.
I’ve been working a lot of automated geocoding of text over the last 6 months, and I’ve found myself consistently describing the same set of tasks or ways to extract location information from text.
As political scientists, we are often interested in identifying political actors in text. Thankfully, have a growing set of tools for doing so, including named entity recognition and dependency parses, custom event models, or hand-labeling of text.