Is Arabic part of speech tagging feasible without word segmentation?

Authors:
Emad Mohamed;Sandra Kübler
Affiliations:
Indiana University, Bloomington, IN;Indiana University, Bloomington, IN
Venue:
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Year:
2010

Citing 3
Cited 3

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Abstract

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%.