koRpus (version 0.04-27)

treetag: A function to call TreeTagger

Description

This function calls a local installation of TreeTagger[1] to tokenize and POS tag the given text.

Usage

treetag(file, treetagger = "kRp.env", rm.sgml = TRUE,
    lang = "kRp.env",
    sentc.end = c(".", "!", "?", ";", ":"),
    encoding = NULL, TT.options = NULL, debug = FALSE,
    TT.tknz = TRUE)

Arguments

file

A character vector, valid path to a file, containing the text to be analyzed.

treetagger

A character vector giving the TreeTagger script to be called. If set to "kRp.env" this is got from get.kRp.env. Only if set to "manual", it is assume

rm.sgml

Logical, whether SGML tags should be ignored and removed from output

lang

A character string naming the language of the analyzed corpus. See kRp.POS.tags for all supported languages. If set to "kRp.env" this is got from

sentc.end

A character vector with tokens indicating a sentence ending. This adds to TreeTaggers results, it doesn't really replace them.

encoding

A character string defining the character encoding of the input file, like "Latin1" or "UTF-8". If NULL, the encoding will either be taken from a preset (if defined in TT.options), or fall back t

TT.options

A list of options to configure how TreeTagger is called. You have two basic choices: Either you choose one of the pre-defined presets or you give a full set of valid options:

• path

{Mandatory: The absolute path to the

tokenizer

tknz.opts

tagger

abbrev

params

lexicon

lookup

filter

Value

• An object of class kRp.tagged-class. If debug=TRUE, prints internal variable settings and attempts to return the original output if the TreeTagger system call in a matrix.

code

treetagger="manual"

item

• debug
• TT.tknz

Details

Note that the value of lang must match a valid language supported by kRp.POS.tags. It will also get stored in the resulting object and might be used by other functions at a later point. E.g., treetag is being called by kRp.freq.analysis, which will by default query this language definition, unless explicitly told otherwise. The rationale behind this is to comfortably make it possible to have tokenized and POS tagged objects of various languages around in your workspace, and not worry about that too much.

References

Schmid, H. (1994). Probabilistic part-of-speec tagging using decision trees. In International Conference on New Methods in Language Processing, Manchester, UK, 44--49.

[1] http://www.ims.uni-stuttgart.de/projekte/corplex/TreeTagger/DecisionTreeTagger.html

See Also

kRp.freq.analysis, get.kRp.env, kRp.tagged-class

Examples

# first way to invoke POS tagging, using a built-in preset:
tagged.results <- treetag("~/my.data/speech.txt", treetagger="manual", lang="en",
   TT.options=list(path="~/bin/treetagger", preset="en"))
# second way, use one of the batch scripts that come with TreeTagger:
tagged.results <- treetag("~/my.data/speech.txt",
   treetagger="~/bin/treetagger/cmd/tree-tagger-english", lang="en")
# third option, set the above batch script in an environment object first:
set.kRp.env(TT.cmd="~/bin/treetagger/cmd/tree-tagger-english", lang="en")
tagged.results <- treetag("~/my.data/speech.txt")

# after tagging, use the resulting object with other functions in this package:
readability(tagged.results)
lex.div(tagged.results)