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DESCRIPTION
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Package: cleanNLP
Type: Package
Title: A Tidy Data Model for Natural Language Processing
Version: 2.0.3
Authors@R: c(person(given = "Taylor B.", family = "Arnold", email = "[email protected]", role = c("aut", "cre")))
Author: Taylor B. Arnold [aut, cre]
Maintainer: Taylor B. Arnold <[email protected]>
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, a Python back
end with 'spaCy' <https://spacy.io> or the Java back end 'CoreNLP'
<http://stanfordnlp.github.io/CoreNLP/>. Exposed annotation tasks include
tokenization, part of speech tagging, named entity recognition, entity linking, sentiment
analysis, dependency parsing, coreference resolution, and word embeddings. Summary
statistics regarding token unigram, part of speech tag, and dependency type frequencies
are also included to assist with analyses.
Depends:
R (>= 2.10)
Imports:
dplyr (>= 0.7.4),
Matrix (>= 1.2),
stringi,
stats,
methods,
utils
Suggests:
udpipe (>= 0.3),
reticulate (>= 1.4),
rJava (>= 0.9-8),
RCurl (>= 1.95),
knitr (>= 1.15),
rmarkdown (>= 1.4),
testthat (>= 1.0.1),
covr (>= 2.2.2)
SystemRequirements: Python (>= 2.7.0); spaCy <https://spacy.io/> (>= 2.0); Java (>= 7.0); Stanford CoreNLP <http://nlp.stanford.edu/software/corenlp.shtml> (>= 3.7.0)
License: LGPL-2
URL: https://statsmaths.github.io/cleanNLP/
BugReports: http://github.com/statsmaths/cleanNLP/issues
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.0.1