Analyse text entities, sentiment, syntax and categorisation using the Google Natural Language API

gl_nlp(string, nlp_type = c("annotateText", "analyzeEntities",
  "analyzeSentiment", "analyzeSyntax", "analyzeEntitySentiment",
  "classifyText"), type = c("PLAIN_TEXT", "HTML"), language = c("en", "zh",
  "zh-Hant", "fr", "de", "it", "ja", "ko", "pt", "es"),
  encodingType = c("UTF8", "UTF16", "UTF32", "NONE"))



A vector of text to detect language for, or Google Cloud Storage URI(s)


The type of Natural Language Analysis to perform. The default annotateText will perform all features in one call.


Whether input text is plain text or a HTML page


Language of source, must be supported by API.


Text encoding that the caller uses to process the output


A list of the following objects, if those fields are asked for via nlp_type:


string can be a character vector, or a location of a file content on Google cloud Storage. This URI must be of the form gs://bucket_name/object_name

Encoding type can usually be left at default UTF8. Read more here

The current language support is available here

See also


# NOT RUN { text <- "to administer medicince to animals is frequently a very difficult matter, and yet sometimes it's necessary to do so" nlp <- gl_nlp(text) nlp$sentences nlp$tokens nlp$entities nlp$documentSentiment ## vectorised input texts <- c("The cat sat one the mat", "oh no it didn't you fool") nlp_results <- gl_nlp(texts) # }