Is Arabic Part of Speech Tagging Feasible Without Word Segmentation?

In this paper, we compare two novel methods for part of speech tagging of Arabic without the use of gold standard word segmentation but with the full POS tagset of the Penn Arabic Treebank. The first approach uses complex tags without any word segmentation, the second approach is segmention-based, using a machine learning segmenter. Surprisingly, word-based POS tagging yields the best results, with a word accuracy of 94.74%.

• Type: Journal
• Year: 2010
• Where: NAACL
• Authors: Emad Mohamed, Sandra Kübler
• Keywords: Computational Linguistics, NAACL 2010, Penn Arabic Treebank, Standard Word Segmentation, Word Segmentation