Comments (3)
Thanks.
Added Token.check_flag method, used like so:
>>> tokens = nlp('Apple computers')
>>> tokens[0].check_flag(IS_ALPHA)
True
This is a less convenient API than the token.is_alpha, but plays more nicely with user and language-specific flags. I want to avoid sub-classing Token per language, but different languages will want different flag features.
If you have strong feelings either way on this, I'm happy to listen.
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Thanks!
Definitely makes sense not to subclass Token per language. Another option could be to have the token.is_alpha
style API for those flags common to all languages and some kind of language specific flag API like token.lang_spec(FLAG)
, but this could be unnecessarily confusing.
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This thread has been automatically locked since there has not been any recent activity after it was closed. Please open a new issue for related bugs.
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