udpipe_annotate: Tokenising, Lemmatising, Tagging and Dependency Parsing Annotation of raw text

Description

Tokenising, Lemmatising, Tagging and Dependency Parsing Annotation of raw text

Usage

udpipe_annotate(object, x, doc_id = paste("doc", seq_along(x), sep = ""),
  tokenizer = "tokenizer", tagger = c("default", "none"),
  parser = c("default", "none"), trace = FALSE, ...)

Arguments

object

an object of class udpipe_model as returned by udpipe_load_model

a character vector in UTF-8 encoding where each element of the character vector contains text which you like to tokenize, tag and perform dependency parsing.

doc_id

an identifier of a document with the same length as x. This should be a character vector. doc_id[i] corresponds to x[i].

tokenizer

a character string of length 1, which is either 'tokenizer' (default udpipe tokenisation) or a character string with more complex tokenisation options as specified in http://ufal.mff.cuni.cz/udpipe/users-manual in which case tokenizer should be a character string where the options are put after each other using the semicolon as separation.

tagger

a character string of length 1, which is either 'default' (default udpipe POS tagging and lemmatisation) or 'none' (no POS tagging and lemmatisation needed) or a character string with more complex tagging options as specified in http://ufal.mff.cuni.cz/udpipe/users-manual in which case tagger should be a character string where the options are put after each other using the semicolon as separation.

parser

a character string of length 1, which is either 'default' (default udpipe dependency parsing) or 'none' (no dependency parsing needed) or a character string with more complex parsing options as specified in http://ufal.mff.cuni.cz/udpipe/users-manual in which case parser should be a character string where the options are put after each other using the semicolon as separation.

trace

A non-negative integer indicating to show progress on the annotation. If positive it prints out a message before each trace number of elements of x for which annotation is to be executed, allowing you to see how much of the text is already annotated. Defaults to FALSE (no progress shown).

...

currently not used

Value

a list with 3 elements

x: The x character vector with text.
conllu: A character vector of length 1 containing the annotated result of the annotation flow in CONLL-U format. This format is explained at http://universaldependencies.org/format.html
error: A vector with the same length of x containing possible errors when annotating x

References

https://ufal.mff.cuni.cz/udpipe, https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-2364, http://universaldependencies.org/format.html

Examples

Run this code

# NOT RUN {
model    <- udpipe_download_model(language = "dutch-lassysmall")
if(!model$download_failed){
ud_dutch <- udpipe_load_model(model$file_model)

## Tokenise, Tag and Dependency Parsing Annotation. Output is in CONLL-U format.
txt <- c("Dus. Godvermehoeren met pus in alle puisten, 
  zei die schele van Van Bukburg en hij had nog gelijk ook. 
  Er was toen dat liedje van tietenkonttieten kont tieten kontkontkont, 
  maar dat hoefden we geenseens niet te zingen. 
  Je kunt zeggen wat je wil van al die gesluierde poezenpas maar d'r kwam wel 
  een vleeswarenwinkel onder te voorschijn van heb je me daar nou.
  
  En zo gaat het maar door.",
  "Wat die ransaap van een academici nou weer in z'n botte pan heb gehaald mag 
  Joost in m'n schoen gooien, maar feit staat boven water dat het een gore 
  vieze vuile ransaap is.")
x <- udpipe_annotate(ud_dutch, x = txt)
cat(x$conllu)
as.data.frame(x)

## Only tokenisation
x <- udpipe_annotate(ud_dutch, x = txt, tagger = "none", parser = "none")
as.data.frame(x)

## Only tokenisation and POS tagging + lemmatisation, no dependency parsing
x <- udpipe_annotate(ud_dutch, x = txt, tagger = "default", parser = "none")
as.data.frame(x)

## Only tokenisation and dependency parsing, no POS tagging nor lemmatisation
x <- udpipe_annotate(ud_dutch, x = txt, tagger = "none", parser = "default")
as.data.frame(x)

## Provide doc_id for joining and identification purpose
x <- udpipe_annotate(ud_dutch, x = txt, doc_id = c("id1", "feedbackabc"),
                     tagger = "none", parser = "none", trace = TRUE)
as.data.frame(x)

## Mark on encodings: if your data is not in UTF-8 encoding, make sure you convert it to UTF-8 
## This can be done using iconv as follows for example
udpipe_annotate(ud_dutch, x = iconv('Ik drink melk bij mijn koffie.', to = "UTF-8"))
}



## cleanup for CRAN only - you probably want to keep your model if you have downloaded it
if(file.exists(model$file_model)) file.remove(model$file_model)
# }