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

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arxiv 2003.07082 v2 pith:OANFHBHD submitted 2020-03-16 cs.CL

Peng Qi , Yuhao Zhang , Yuhui Zhang , Jason Bolton , Christopher D. Manning This is my paper
classification cs.CL
keywords stanzalanguagespythonhumanincludinglanguagenaturalneural
verification ladder T0 review T1 audit T2 compute T3 formal
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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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Cited by 6 Pith papers

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