These are a series of programs inspired by the basic functionality of the prodigy system modified to use keyboard entry and the terminal-based curses library. They have been used in various phases of the Political Instability Task Force New Generation Event Coder project (2021-2022) and the formats have gradually morphed away from prodigy but should be fairly easy to figure out/modify.
Out of historical circumstance, these are primarily located in https://github.com/openeventdata/plovigy but I'm including this as a stub with the main programs
A lightweight program that duplicates the basic functionality of the "mark" function in the prodigy system using the same input and output formats; output is saved to a file which is coder- and time-stamped rather than to a database.
A subset of plovigy-mark.py which uses the PITF-DEDI jsonl format—see the file plovigy-DEDI-input-sample.jsonl for a sample of the input—and mostly does simple accept/reject classification without
any other options, though it does allow dates to be moved forward and back. This also does quite a bit of autocoding: see the sample files autocodes-DEDI.txt and autocodes-202212-DEDI.txt. Requires utilDEDI.py
DEDI is an internal PITF data set on protests which is derived from the government version of the ICEWS event data. plovigy-PITF-DEDI.py is just one piece of an extended pipeline used in this production but has been extensively used for several years and I've got more documentation for the program if that would be helpful.
Radical simplification of plovigy-PITF-DEDI.py to work with the PITF PLOVER/NGEC human annotations. The more complex actor-annot-lite replaces this for annotation purposes, but this forms the basis for the later plovigy-NGEC programs.
A Python program for annotating event files with sentence segmentation, actor, recipient, and location spans. It is designed to use minimal machine resources—in the Macintosh OS-X system—it takes about 6Mb of memory versus the 350Mb required for a single Google Chrome web page—and does not require connection to a server. The program is implemented using the C/Python ncurses terminal emulation and uses a small set of keyboard commands rather than a mouse, and is designed to run on a laptop. Like on an airplane.
plovigy for selecting cases either from the Release data (.json suffix) or from the cases selected by assess_context.py(.txt suffix). Writes to the training-case format: see internal commenting for additional details
plovigy for additional annotating of event training cases and documentation for same.