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cleanNLP (version 3.0.4)

A Tidy Data Model for Natural Language Processing

Description

Provides a set of fast tools for converting a textual corpus into a set of normalized tables. Users may make use of the 'udpipe' back end with no external dependencies, or two Python back ends with 'spaCy' or 'CoreNLP' . Exposed annotation tasks include tokenization, part of speech tagging, named entity recognition, and dependency parsing.

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Version

Install

install.packages('cleanNLP')

Monthly Downloads

518

Version

3.0.4

License

LGPL-2

Maintainer

Taylor Arnold

Last Published

August 15th, 2022

Functions in cleanNLP (3.0.4)

cnlp_download_spacy

Download model files needed for spacy
word_frequency

Most frequent English words
un

Universal Declaration of Human Rights
cnlp_init_udpipe

Interface for initializing the udpipe backend
cnlp_init_spacy

Interface for initializing the spacy backend
cnlp_utils_pca

Compute Principal Components and store as a Data Frame
cnlp_download_corenlp

Download model files needed for coreNLP
cnlp_init_stringi

Interface for initializing the standard R backend
cleanNLP-package

cleanNLP: A Tidy Data Model for Natural Language Processing
cnlp_init_corenlp

Interface for initializing the coreNLP backend
cnlp_utils_tfidf

Construct the TF-IDF Matrix from Annotation or Data Frame
cnlp_annotate

Run the annotation pipeline on a set of documents