BNOSAC is happy to announce the release of the udpipe R package (https://bnosac.github.io/udpipe/en) which is a Natural Language Processing toolkit that provides language-agnostic ‘tokenization’, ‘parts of speech tagging’, ‘lemmatization’, ‘morphological feature tagging’ and ‘dependency parsing’ of raw text. Next to text parsing, the package also allows you to train annotation models based on data of ‘treebanks’ in ‘CoNLL-U’ format as provided at http://universaldependencies.org/format.html.

Language models

The package provides direct access to language models trained on more than 50 languages. The following languages are directly available:

afrikaans, ancient_greek-proiel, ancient_greek, arabic, basque, belarusian, bulgarian, catalan, chinese, coptic, croatian, czech-cac, czech-cltt, czech, danish, dutch-lassysmall, dutch, english-lines, english-partut, english, estonian, finnish-ftb, finnish, french-partut, french-sequoia, french, galician-treegal, galician, german, gothic, greek, hebrew, hindi, hungarian, indonesian, irish, italian, japanese, kazakh, korean, latin-ittb, latin-proiel, latin, latvian, lithuanian, norwegian-bokmaal, norwegian-nynorsk, old_church_slavonic, persian, polish, portuguese-br, portuguese, romanian, russian-syntagrus, russian, sanskrit, serbian, slovak, slovenian-sst, slovenian, spanish-ancora, spanish, swedish-lines, swedish, tamil, turkish, ukrainian, urdu, uyghur, vietnamese

We hope that the package will allow other R users to build natural language applications on top of the resulting parts of speech tags, tokens, morphological features and dependency parsing output. And we hope in particular that applications will arise which are not limited to English only (like the textrank R package or the cleanNLP package to name a few)

Easy installation, great docs

• Note that the package has no external software dependencies (no java nor python) and depends only on 2 R packages (Rcpp and data.table), which makes the package easy to install on any platform. The package is available for download at https://CRAN.R-project.org/package=udpipe and is developed at https://github.com/bnosac/udpipe. A small docusaurus website is made available at https://bnosac.github.io/udpipe/en
• We hope you enjoy using it and we would like to thank Milan Straka for all the efforts done on UDPipe as well as all persons involved in http://universaldependencies.org

Training on Text Mining with R

Are you interested in text mining. Feel free to register for the upcoming course on text mining

• Location & Time: March 22-23 2018 in Leuven, Belgium
• Register at https://lstat.kuleuven.be/training/coursedescriptions/text-mining-with-r

Example

Want to get started with it right away? Example annotating Polish text in UTF-8 encoding, but you can pick any language of choice listed above. Enjoy.

library(udpipe)
model <- udpipe_download_model(language = "polish")
model <- udpipe_load_model(file = model$file_model)
x <- udpipe_annotate(model, x = "Budynek otrzymany od parafii wymaga remontu, a placówka nie otrzymała jeszcze żadnej dotacji.")
x <- as.data.frame(x)
x