Analyse text for entities, sentiment, syntax and classification using the Google Natural Language API.
Usage
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")
)Arguments
- string
Character vector. Text to analyse or Google Cloud Storage URI(s) in the form
gs://bucket_name/object_name.- nlp_type
Character. Type of analysis to perform. Default
annotateTextperforms all features in a single call. Options include:analyzeEntities,analyzeSentiment,analyzeSyntax,analyzeEntitySentiment,classifyText.- type
Character. Whether the input is plain text (
PLAIN_TEXT) or HTML (HTML).- language
Character. Language of the source text. Must be supported by the API.
- encodingType
Character. Text encoding used to process the output. Default
UTF8.
Value
A list containing the requested components as specified by nlp_type:
- sentences
Sentences in the input document. API reference.
- tokens
Tokens with syntactic information. API reference.
- entities
Entities with semantic information. API reference.
- documentSentiment
Overall sentiment of the document. API reference.
- classifyText
Document classification. API reference.
- language
Detected language of the text, or the language specified in the request.
- text
Original text passed to the API. Returns
NAif input is empty.
Details
Encoding type can usually be left at the default UTF8.
Further details on encoding types.
Current language support is listed here.
Examples
if (FALSE) { # \dontrun{
library(googleLanguageR)
text <- "To administer medicine to animals is frequently difficult, yet sometimes necessary."
nlp <- gl_nlp(text)
nlp$sentences
nlp$tokens
nlp$entities
nlp$documentSentiment
# Vectorised input
texts <- c("The cat sat on the mat.", "Oh no, it did not, you fool!")
nlp_results <- gl_nlp(texts)
} # }