arWaC: Arabic corpus from the Web
The Arabic Web Corpus (arWaC) is an Arabic corpus made up of texts collected from the Arabic Web domain. The corpus was created by Serge Sharoff and was tagged by AMIRA-1.2. The corpus consists of 174 million Arabic words and texts are cleaned and deduplicated.
The arWaC Arabic corpus was PoS tagged by AMIRA version 1.2 with the following tagset summary.
Tools to work with the Arabic corpus
A complete set of tools is available to work with this Arabic corpus to generate:
- word sketch – Arabic collocations categorized by grammatical relations
- thesaurus – synonyms and similar words for every word
- word lists – lists of Arabic nouns, verbs, adjectives etc. organized by frequency
- keywords– terminology extraction of one-word units
- n-grams – frequency list of multi-word units
- concordance – examples in context
- text type analysis – statistics of metadata in the corpus
BARONI, Marco, et al. The WaCky wide web: a collection of very large linguistically processed web-crawled corpora. Language resources and evaluation, 2009, 43.3: 209-226.
BARONI, Marco; KILGARRIFF, Adam. Large linguistically-processed web corpora for multiple languages. In: Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations. Association for Computational Linguistics, 2006, pp. 87–90.
Arabic part-of-speech tag set
Mona T. Diab (2007) Towards an optimal POS tag set for Modern Standard Arabic Processing Recent Advances. In Natural Language Processing (RANLP), August, Borovets, Bulgaria.
Search the Arabic corpus
Sketch Engine offers a range of tools to work with this Arabic corpus from the web.
Use Sketch Engine in minutes
Generating collocations, frequency lists, examples in contexts, n-grams or extracting terms. Use our Quick Start Guide to learn it in minutes.