Introducing spaCy v3.5

We’re excited to release v3.5 of the spaCy Natural Language Processing library. spaCy v3.5 introduces three new CLI commands, adds fuzzy matching, provides improvements to our entity linking functionality, and includes a range of language updates and bug fixes.

New CLI commands

• apply applies a pipeline to one or more .txt, .jsonl or .spacy files
• benchmark speed profiles a pipeline’s speed with a warmup and a confidence interval
• find-threshold tests a range of threshold values for spancat, textcat_multilabel, etc, to identify the most optimal one.

Examples on how to run these commands can be found in our CLI documentation as well as in our v3.5 usage notes.

Fuzzy matching

The new FUZZY operator allows fuzzy matches based on Levenshtein edit distance:

pattern = [{"LOWER": {"FUZZY": "definitely"}}]

The FUZZY and REGEX operators are now also supported for lists with IN and NOT_IN:

pattern = [{"TEXT": {"REGEX": {"NOT_IN": ["^awe(some)?$", "^wonder(ful)?"]}}}]

Entity linking

The entity linker’s knowledge base has been refactored for easier customization. KnowledgeBase is now an abstract class and the default implementation is the new class InMemoryLookupKB.

Read more about all the improvements, updates and bug fixes:

• v3.5 usage notes
• v3.5.0 release notes

New additions to spaCy universe and projects

Many cool new plugins, extensions, pipelines and tutorials have been added to the spaCy universe and spaCy projects since v3.4:

BERTopic	Leveraging BERT and c-TF-IDF to create easily interpretable topics.
concepCy	A multilingual knowledge graph in spaCy.
greCy	Trained Ancient Greek models for use in spaCy.
English Interpretation Sentence Pattern	English interpretation for accurate translation from English to Japanese.
spaCy - Partial Tagger	Sequence tagger for partially annotated datasets in spaCy.
spacy-cleaner	Easily clean text with spaCy.
spaCy-PyThaiNLP	Add Thai support for spaCy.
Speedster pipeline acceleration	Named Entity Recognition (WikiNER) accelerated using Speedster.
Zshot	Zero and Few shot named entity & relationships recognition.

View the spaCy universe

Additionally, the spaCy team has added demo projects for two newer components:

experimental/coref	Use the new experimental coref component to train a coreference model using OntoNotes.
pipelines/spancat_demo	A minimal demo spancat project.

Resources

• spaCy v3.5: What’s new in v3.5
• Release notes: Detailed overview
• spaCy models directory: Download trained pipelines
• spaCy universe: Projects, plugins and extensions
• spaCy project templates: End-to-end NLP workflows
• Video tutorials: More in-depth spaCy content on YouTube