Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

Peng Qi, Yuhao Zhang, Yuhui Zhang, Jason Bolton, Christopher D. Manning
3/16/2020
cs.CL

Official code: stanfordnlp/stanza (7,905 stars, PyTorch, last commit 2026-10-20).

Abstract

We introduce Stanza, an open-source Python natural language processing toolkit supporting 66 human languages. Compared to existing widely used toolkits, Stanza features a language-agnostic fully neural pipeline for text analysis, including tokenization, multi-word token expansion, lemmatization, part-of-speech and morphological feature tagging, dependency parsing, and named entity recognition. We have trained Stanza on a total of 112 datasets, including the Universal Dependencies treebanks and other multilingual corpora, and show that the same neural architecture generalizes well and achieves competitive performance on all languages tested. Additionally, Stanza includes a native Python interface to the widely used Java Stanford CoreNLP software, which further extends its functionality to cover other tasks such as coreference resolution and relation extraction. Source code, documentation, and pretrained models for 66 languages are available at https://stanfordnlp.github.io/stanza.

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Code Implementations(1)

stanfordnlp/stanzaOfficial100%
PyTorch

Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages

7,905962CSS, JinjaSep 26, 2017yesterdayNOASSERTION
artificial-intelligencecorenlpdeep-learningmachine-learningnamed-entity-recognition+5 more

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Cite this paper

@article{qi2020stanza,
  title  = {Stanza: A Python Natural Language Processing Toolkit for Many Human Languages},
  author = {Peng Qi and Yuhao Zhang and Yuhui Zhang and Jason Bolton and Christopher D. Manning},
  year   = {2020},
  eprint = {2003.07082},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2003.07082}
}

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