v2.2.3: Tokenizer.explain, Korean base support, dependency scores per label and bug fixes

✨ New features and improvements

• NEW: Tokenizer.explain method to see which rule or pattern was matched.

  tok_exp = nlp.tokenizer.explain("(don't)")
  assert [t[0] for t in tok_exp] == ["PREFIX", "SPECIAL-1", "SPECIAL-2", "SUFFIX"]
  assert [t[1] for t in tok_exp] == ["(", "do", "n't", ")"]

• NEW: Official Python 3.8 wheels for spaCy and its dependencies.
• Base language support for Korean.
• Add Scorer.las_per_type (labelled depdencency scores per label).
• Rework Chinese language initialization and tokenization
• Improve language data for Luxembourgish.

🔴 Bug fixes

• Fix issue #4573, #4645: Improve tokenizer usage docs.
• Fix issue #4575: Add error in debug-data if no dev docs are available.
• Fix issue #4582: Make as_tuples=True in Language.pipe work with multiprocessing.
• Fix issue #4590: Correctly call on_match in DependencyMatcher.
• Fix issue #4593: Build wheels for Python 3.8.
• Fix issue #4604: Fix realloc in Retokenizer.split.
• Fix issue #4656: Fix conllu2json converter when -n > 1.
• Fix issue #4662: Fix Language.evaluate for components without .pipe method.
• Fix issue #4670: Ensure EntityRuler is deserialized correctly from disk.
• Fix issue #4680: Raise error if non-string labels are added to Tagger or TextCategorizer.
• Fix issue #4691: Make Vectors.find return keys in correct order.

📖 Documentation and examples

• Fix various typos and inconsistencies.

👥 Contributors

Thanks to @yash1994, @walterhenry, @prilopes, @f11r, @questoph, @erip, @richardpaulhudson and @GuiGel for the pull requests and contributions.