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Add backwards incompatibility [ci skip]
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@ -326,4 +326,33 @@ check if all of your models are up to date, you can run the
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<!-- TODO: copy from release notes once they're ready -->
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- The Dutch models have been trained on a new NER corpus (custom labelled UD
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instead of WikiNER), so their predictions may be very different compared to
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the previous version. The results should be significantly better and more
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generalizable, though.
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- The `spacy download` command does **not** set the `--no-deps` pip argument
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anymore by default, meaning that model package dependencies (if available)
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will now be also downloaded and installed. If spaCy (which is also a model
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dependency) is not installed in the current environment, e.g. if a user has
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built from source, `--no-deps` is added back automatically to prevent spaCy
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from being downloaded and installed again from pip.
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- The built-in `biluo_tags_from_offsets` converter is now stricter and will
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raise an error if entities are overlapping (instead of silently skipping
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them). If your data contains invalid entity annotations, make sure to clean it
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and resolve conflicts. You can now also use the new `debug-data` command to
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find problems in your data.
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- The default punctuation in the `sentencizer` has been extended and now
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includes more characters common in various languages. This also means that the
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results it produces may change, depending on your text. If you want the
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previous behaviour with limited characters, set `punct_chars=[".", "!", "?"]`
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on initialization.
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- Lemmatization tables (rules, exceptions, index and lookups) are now part of
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the `Vocab` and serialized with it. This means that serialized objects (`nlp`,
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pipeline components, vocab) will now include additional data, and models
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written to disk will include additional files.
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- The `Serbian` language class (introduced in v2.1.8) incorrectly used the
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language code `rs` instead of `sr`. This has now been fixed, so `Serbian` is
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now available via `spacy.lang.sr`.
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- The `"sources"` in the `meta.json` have changed from a list of strings to a
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list of dicts. This is mostly internals, but if your code used
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`nlp.meta["sources"]`, you might have to update it.
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