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

TLDR

Stanza is an open‑source Python NLP toolkit that supports 66 human languages. It implements a language‑agnostic fully neural pipeline for tokenization, lemmatization, POS and morphological tagging, dependency parsing, NER, and, via a native Python interface to Stanford CoreNLP, also offers coreference resolution and relation extraction, trained on 112 multilingual datasets. Stanza’s pretrained models for 66 languages are publicly available at https://stanfordnlp.github.io/stanza/.

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/.