ArTenTen: Arabic Corpus and Word Sketches

Tressy Arts, Yonatan Belinkov, Nizar Habash, Adam Kilgarriff, Vit Suchomel

Research output: Contribution to journalArticlepeer-review

Abstract

We present arTenTen, a web-crawled corpus of Arabic, gathered in 2012. arTenTen consists of 5.8-billion words. A chunk of it has been lemmatized and part-of-speech (POS) tagged with the MADA tool and subsequently loaded into Sketch Engine, a leading corpus query tool, where it is open for all to use. We have also created 'word sketches': one-page, automatic, corpus-derived summaries of a word's grammatical and collocational behavior. We use examples to demonstrate what the corpus can show us regarding Arabic words and phrases and how this can support lexicography and inform linguistic research. The article also presents the 'sketch grammar' (the basis for the word sketches) in detail, describes the process of building and processing the corpus, and considers the role of the corpus in additional research on Arabic.

Original languageEnglish (US)
Pages (from-to)357-371
Number of pages15
JournalJournal of King Saud University - Computer and Information Sciences
Volume26
Issue number4
DOIs
StatePublished - 2014

Keywords

  • Arabic
  • Concordance
  • Corpora
  • Lexicography
  • Morphology

ASJC Scopus subject areas

  • Computer Science(all)

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