stanfordnlp/stanza
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
From the publisher
README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
Stanza: A Python NLP Library for Many Human Languages The Stanford NLP Group's official Python NLP library. It contains support for running various accurate natural language processing tools on 60+ languages and for accessing the Java Stanford CoreNLP software from Python. For detailed information please visit our official website. 🔥 A new collection of biomedical and clinical English model packages are now available, offering seamless experience for syntactic analysis and named entity recognition (NER) from biomedical literature text and clinical notes. For more information, check out our Biomedical models documentation page. If you use this library in your research, please kindly cite our ACL2020 Stanza system demo paper: If you use our biomedical and clinical models, please also cite our Stanza Biomedical Models description paper: The PyTorch implementation of the neural pipeline in this repository is due to Peng Qi (@qipeng), Yuhao Zhang (@yuhaozhang), and Yuhui Zhang (@yuhui-zh15), with help…
Read the full README ↗ · Preview checked 2026-10-28T15:32:57.602Z
Inside the original README — Document outline
- References
- Issues and Usage Q&A
- Contributing to Stanza
- Installation
- pip
- Anaconda
- From Source
- Running Stanza
- Getting Started with the neural pipeline
- Accessing Java Stanford CoreNLP software
- Online Colab Notebooks
- Trained Models for the Neural Pipeline
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What this repository does
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
Repository facts
- Owner
- stanfordnlp
- Primary language
- Python
- Stars
- 7,905
- Forks
- 965
- Open issues + pull requests
- 105
- License
- Other
- Archived
- No
- Default branch
- main
- Created
- 2017-09-26T08:00:56.000Z
- Last push
- 2026-10-30T09:24:00.000Z
Topics and intended use
Owner-supplied topics: artificial-intelligence, corenlp, deep-learning, machine-learning, named-entity-recognition, natural-language-processing, nlp, python, pytorch, universal-dependencies
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Source and freshness
Source: GitHub. Metadata observed 2026-10-31T13:20:02.570Z. Daily imports are snapshots, not real-time monitoring.
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