We consider the task of tagging Arabic nouns with WordNet supersenses. Three approaches are evaluated. The first uses an expertcrafted but limited-coverage lexicon, Arabic WordNet, and heuristics. The second uses unsupervised sequence modeling. The third and most successful approach uses machine translation to translate the Arabic into English, which is automatically tagged with English supersenses, the results of which are then projected back into Arabic. Analysis shows gains and remaining obstacles in four Wikipedia topical domains.
|Title of host publication||Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings, June 9-14, 2013, Westin Peachtree Plaza Hotel, Atlanta, Georgia, USA|
|Publisher||Association for Computational Linguistics|
|Number of pages||7|
|Publication status||Published - 2013|