Toward an efficient Arabic Part of Speech Tagger

The task of tagging and allotting the correct Part of Speech (POS) to text given its context is not obvious and requires expertise and use of considerable resources. Automating such task and building tools that can carry such job is crucial and imperative to advance in major areas of natural language processing. A limited numbers of Part of Speech Taggers exist currently for Arabic and their availability is not trivial. In this paper we present an effort to design and build a POS tagger that would take into consideration the richness of the language as well as the efficiency in processing volumes of text. The Light Arabic Part of Speech Tagger (LAPOST) current output is very comparable to existing system but more effective from the processing perspective.