Analyzing Multilingual French and Russian Text using NLTK, spaCy, and Stanza

This lesson covers tokenization, part-of-speech tagging, and lemmatization, as well as automatic language detection, for non-English and multilingual text. You’ll learn how to use the Python packages NLTK, spaCy, and Stanza to analyze a multilingual Russian and French text.

Authors

Publication Details

Journal
The Programming Historian
Published
2024-11-13
DOI
https://doi.org/10.46430/phen0121
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
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article

Analyzing Multilingual French and Russian Text using NLTK, spaCy, and Stanza

Ian Goodale
The Programming Historian
Natural Language Processing Techniques
article

Analyzing Multilingual French and Russian Text using NLTK, spaCy, and Stanza

Ian Goodale
article en

Abstract

This lesson covers tokenization, part-of-speech tagging, and lemmatization, as well as automatic language detection, for non-English and multilingual text. You’ll learn how to use the Python packages NLTK, spaCy, and Stanza to analyze a multilingual Russian and French text.

The Programming Historian(13)
Quality Education
Openalex Percentile: Top 82%
Natural Language Processing Techniques
DOIOpen Access PDFOpenAlex
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Analyzing Multilingual French and Russian Text using NLTK, spaCy, and Stanza — Ian Goodale · The Programming Historian (2024) | TGRS Research Map | TGRS