Practical overview
When it fits
Use Stanza when a Python workflow needs text analysis with its neural NLP pipeline, or when Python code needs a wrapper for Stanford CoreNLP.
Who it is for
- Python developers adding language analysis to software or research workflows
- Teams processing multilingual text
- Researchers working with biomedical literature or clinical notes using the available English model packages
Documented uses
- Tokenize text and segment it into sentences
- Identify named entities in supported text
- Parse sentences and inspect word-level dependency relations
- Call Java Stanford CoreNLP software from Python
Requirements & limits
The README supports Python 3.6 or later and recommends pip installation; it notes PyTorch 1.3.0 or above among dependencies. Conda installation is documented, with a Python 3.10 limitation.
- The README describes language support across more than 60 languages.
- The neural pipeline can automatically download models when needed; pre-downloading them is optional in the documented English example.
- The CoreNLP wrapper requires a separate CoreNLP distribution and language model JARs.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Install Stanza and process a sentence
Set up the Python package and run the documented English pipeline example to print dependency relations.
Before you start
- Python 3.6 or later
- pip; the README recommends pip and notes PyTorch 1.3.0 or above among Stanza’s dependencies
- A connection may be needed to download English models
Steps
Install the package with the command below.
pip install stanzaIn Python, import Stanza and optionally call
stanza.download('en')to pre-download English models.Create a pipeline with
stanza.Pipeline('en')and pass it the documented sample sentence.Print dependencies for the first sentence with
doc.sentences[0].print_dependencies().
Expected outcome
A Stanza document for the sample text and printed dependency relations for its first sentence.
Guide limitations
- The README says the pipeline can automatically download models if needed.
- If model download raises a connection error, the README demonstrates passing proxy settings to
stanza.download. - The README says Anaconda installation does not work for Python 3.10 and recommends pip for that Python version.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 16 October 2026
- Original website title
- stanfordnlp/stanza · Official homepage title · retained in its source language