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Spacy Stanza

Spacy Stanza is a Python library that wraps Stanza so developers can use pretrained Stanza models in a spaCy pipeline and receive results as spaCy Doc objects.

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Independent OpenViST project profile, based on linked sources.

Spacy Stanza — OpenViST project profile in AI Developer Tools & SDKs.
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Understand the project

Practical overview

When it fits

Use it when your workflow relies on spaCy but needs annotations produced by pretrained Stanza models, or when you want to combine those annotations with spaCy components and Doc-based processing.

Who it is for

  • Python developers building NLP workflows with spaCy.
  • Teams that want Stanza model annotations in a spaCy-compatible pipeline.

Documented uses

  • Add Stanza-backed language processing to a spaCy pipeline.
  • Obtain tokenization, part-of-speech tags, morphology, lemmas, dependency parses and sentence boundaries in spaCy Doc objects.
  • Use selected-language named entity recognition in a spaCy workflow.
  • Combine Stanza processing with custom spaCy components or batch processing.
Before you choose

Requirements & limits

The repository identifies the project as MIT-licensed. Current installation instructions specify spaCy 3.x; spaCy 2 users are directed to the 0.2.x package series and its separate usage documentation.

  • The current package instructions specify spaCy 3.x; spaCy 2 requires the older 0.2.x series.
  • A pretrained Stanza model must also be downloaded.
  • Named entity recognition is available only for selected languages, and model choice affects supported processing.
  • The wrapper exposes Stanza pipeline settings through keyword arguments; languages without spaCy support can use the documented "xx" spaCy language setting with a Stanza language code.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up a Stanza-backed spaCy pipeline

Install the wrapper, obtain a pretrained Stanza model, and initialize a pipeline that processes text into a spaCy Doc.

Before you start

  • Python environment with spaCy 3.x for the current package instructions
  • The spacy-stanza package
  • A pretrained Stanza model for the language to process

Steps

  1. Install the package with pip install spacy-stanza.

  2. Download a pretrained Stanza model; the README example uses stanza.download("en").

  3. Import stanza and spacy_stanza, then initialize the pipeline with spacy_stanza.load_pipeline("en").

  4. Pass text to the returned nlp object to create a spaCy Doc and inspect its annotations.

Expected outcome

A spaCy-compatible pipeline processes text using Stanza and returns annotations in a spaCy Doc.

Guide limitations

  • The current package instructions specify spaCy 3.x; spaCy 2 uses the 0.2.x package series and separate usage instructions.
  • Named entity recognition is supported only for selected languages; available processing depends on the selected Stanza model.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
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Sources checked
15 October 2026
Original website title
explosion/spacy-stanza · Official homepage title · retained in its source language
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