R/pkg.R

In statsmaths/cleanNLP: A Tidy Data Model for Natural Language Processing

#' cleanNLP: A Tidy Data Model for Natural Language Processing
#'
#' Provides a set of fast tools for converting a textual corpus into a set
#' of normalized tables. Multiple NLP backends can be used, with the output
#' standardized into a normalized format. Options include stringi (very fast,
#' but only provides tokenization), udpipe (fast, many languages, includes
#' part of speech tags and dependencies), coreNLP (using its Python backend),
#' and spacy (python backend; includes named entity recognition).
#'
#' Once the package is set up, run one of \code{\link{cnlp_init_stringi}},
#' \code{\link{cnlp_init_spacy}}, \code{\link{cnlp_init_corenlp}}, or
#' \code{\link{cnlp_init_udpipe}} to load the desired NLP backend.
#' After this function is done running, use \code{\link{cnlp_annotate}}
#' to run the annotation engine over a corpus of text. The package vignettes
#' provide more detailed set-up information.
#'
#' @examples
#'
#'\dontrun{
#' library(cleanNLP)
#'
#' # load the annotation engine
#' cnlp_init_stringi()
#'
#' # annotate your text
#' input <- data.frame(
#'  text=c(
#'    "This is a sentence.",
#'    "Here is something else to parse!"
#'  ),
#'  stringsAsFactors=FALSE
#' )
# anno <- cnlp_annotate(input)
# anno
#'}
#'
#' @docType package
"_PACKAGE"