Re-create meta.json in model directory, even if it exists. Especially
useful when updating existing spaCy models or training with Prodigy.
Ensures user won't end up with multiple "en_core_web_sm" models, and
offers easy way to change the model's name and settings without having
to edit the meta.json file.
On fresh install via subprocess, pip.get_installed_distributions()
won't show new model, so is_package check in link command fails.
Solution for now is to get model package path explicitly and pass it to
link command.
Re-create meta.json in model directory, even if it exists. Especially
useful when updating existing spaCy models or training with Prodigy.
Ensures user won't end up with multiple "en_core_web_sm" models, and
offers easy way to change the model's name and settings without having
to edit the meta.json file.
On fresh install via subprocess, pip.get_installed_distributions()
won't show new model, so is_package check in link command fails.
Solution for now is to get model package path explicitly and pass it to
link command.
This is far from complete but it should be enough to check some things.
1. Mecab transition. Janome doesn't support Unidic, only IPAdic, but UD
tag mappings are based on Unidic. This switches out Mecab for Janome to
get around that.
2. Raw tag extension. A simple tag map can't meet the specifications for
UD tag mappings, so this adds an extra field to ambiguous cases. For
this demo it just deals with the simplest case, which only needs to look
at the literal token. (In reality it may be necessary to look at the
whole sentence, but that's another issue.)
3. General code structure. Seems nobody else has implemented a custom
Tagger yet, so still not sure this is the correct way to pass the
vocabulary around, for example.
Any feedback would be greatly appreciated. -POLM
