Package: cleanNLP
Type: Package
Title: A Tidy Data Model for Natural Language Processing
Version: 2.3.0
Authors@R: c(person(given = "Taylor B.", family = "Arnold", email = "taylor.arnold@acm.org", role = c("aut", "cre")))
Author: Taylor B. Arnold [aut, cre]
Maintainer: Taylor B. Arnold <taylor.arnold@acm.org>
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> (>= 3.9.2)
License: LGPL-2
URL: https://statsmaths.github.io/cleanNLP/
BugReports: http://github.com/statsmaths/cleanNLP/issues
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2018-11-18 15:17:51 UTC; taylor
Repository: CRAN
Date/Publication: 2018-11-18 15:50:03 UTC
Built: R 3.4.4; ; 2019-04-25 21:37:26 UTC; windows
