+ 1

What is Stanza?

It is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. The toolkit is designed to be parallel among more than 70 languages, using the Universal Dependencies formalism.
Stanza is a tool in the NLP / Sentiment Analysis category of a tech stack.
Stanza is an open source tool with 6.7K GitHub stars and 855 GitHub forks. Here’s a link to Stanza's open source repository on GitHub

Who uses Stanza?


6 developers on StackShare have stated that they use Stanza.

Stanza Integrations

Stanza's Features

  • Native Python implementation requiring minimal efforts to set up
  • Full neural network pipeline for robust text analytics, including tokenization, multi-word token (MWT) expansion, lemmatization, part-of-speech (POS) and morphological features tagging, dependency parsing, and named entity recognition
  • Pretrained neural models supporting 66 (human) languages
  • A stable, officially maintained Python interface to CoreNLP

Stanza Alternatives & Comparisons

What are some alternatives to Stanza?
It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
prose is a natural language processing library (English only, at the moment) in pure Go. It supports tokenization, segmentation, part-of-speech tagging, and named-entity extraction.
It is a suite of libraries and programs for symbolic and statistical natural language processing for English written in the Python programming language.
rasa NLU
rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.
It provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch.
See all alternatives

Stanza's Followers
28 developers follow Stanza to keep up with related blogs and decisions.