51 extract citations #20
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This includes: * Update refextract to make it Python 3.6-compatible (This is done in a separate repo for the dependency and referenced in the Pipfile) * Yakshave the process until its output looks reasonably good - find most of the good citations, discard bad ones * Parallelize the first pass of citation extracting - this dramatically speeds up the process as the number of theses grows
The goal of this is to get this file comprehensible enough that it can be worked with. There's still a lot of inaccuracy in actual reference identification, but the code needs to be readable and the data types need to be documented before we can attack that.
It turns out the accuracy of the underlying extractor was actually quite good, and we didn't need the targets system. Extra-long candidate citations were parser garbage, but the shorter ones looked good, and there's a wide separation between them (<300 characters for good citations, >1500 for bad ones), so we can be quite loose on our good/bad classifier.
Most of them are blank for any given citation, because the extractor couldn't figure them out, or they were optional in the citation format in the first place.
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This adds a Citation model, plus code for a one-time process of extracting citations from thesis fulltext. The resulting citations are...sort of OK.
This results in no front-end changes but will make it possible to have citation-oriented front end features.