orWaC: Oromo corpus from the web

The Oromo web corpus (orWaC) is an Oromo corpus made up of texts collected from the Internet. The corpus was prepared according to standards described in the document A Corpus Factory for Many Languages (Kilgarriff et al. at LREC 2010).

Data was crawled by the SpiderLing web spider in January 2016 and comprised of 4 million words.

Document count – the most frequent web domains and domain size distribution:

Top level domains Web domains Second level domain size distribution
org 5,676 *.jw.org 2,695 At least 1000 documents 2
com 2,054 qeerroo.org 1,010 At least 500 documents 4
net 839 vidoser.org 632 At least 100 documents 16
et 213 gadaa.net|com 518 At least 50 documents 21
*.voaafaanoromoo.com 438 At least 10 documents 45
oromedia.net 304 At least 5 documents 60
bilisummaa.com 291 At least 1 document 190
*.blogspot.com 287
oromiatimes.org 276

The content of news/politics and religious sites has a significant presence in the corpus sources.

The corpus was created in the framework of the HaBiT project (Harvesting big text data for under-resourced languages), see more at https://habit-project.eu/wiki/OromoCorpus

Part-of-speech tagset

The orWaC corpus contains POS annotation based on Universal dependencies, a multilingual parser development.

Tools to work with the Oromo corpus

A complete set of Sketch Engine tools is available to work with this Oromo corpus from the web to generate:

  • word sketch – Oromo collocations categorized by grammatical relations
  • thesaurus – synonyms and similar words for every word
  • keywords – terminology extraction of one-word units
  • word lists – lists of Oromo nouns, verbs, adjectives, etc. organized by frequency
  • n-grams – frequency list of multi-word units
  • concordance – examples in context
  • text type analysis – statistics of metadata in the corpus

Corpus factory method

Kilgarriff, A., Reddy, S., Pomikálek, J., & Avinesh, P. V. S. (2010, May). A corpus factory for many languages. In LREC.

Search the Oromo corpus

Sketch Engine offers a range of tools to work with this Oromo corpus.

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