In: Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology-Volume 1, pp. Toutanova, K., Klein, D., Manning, C.D., Singer, Y.: Feature-rich part-of-speech tagging with a cyclic dependency network. Van den Bosch, A., Marsi, E., Soudi, A.: Memory-based morphological analysis and part-of-speech tagging of Arabic. Maamouri, M., Bies, A., Kulick, S., Gaddeche, F., Mekki, W., Krouna, S., Bouziri, B., Zaghouani, W.: Arabic treebank: part 1 v 4.1. In: Proceedings of the Second International Conference on Arabic Language Resources and Tools, Cairo, Egypt (2009)Īltabba, M., Al-Zaraee, A., Shukairy, M.A.: An Arabic morphological analyzer and part-of-speech tagger. In: Proceedings of the INFOtheca ‘12 Conference (2011)ĪlGahtani, S., Black, W., McNaught, J.: Arabic part-of-speech tagging using transformation-based learning. Utvić, M.: Annotating the corpus of contemporary Serbian. Association for Computational Linguistics (2004)įarghaly, A., Shaalan, K.: Arabic natural language processing: challenges and solutions. In: Proceedings of HLT-NAACL 2004: Short Papers, pp. Springer, Cham (2018)ĭiab, M., Hacioglu, K., Jurafsky, D.: Automatic tagging of Arabic text: from raw text to base phrase chunks. In: Intelligent Natural Language Processing: Trends and Applications, pp. Zeroual, I., Lakhouaja, A.: Arabic Corpus linguistics: major progress, but still a long way to go. Zeroual, I., Lakhouaja, A.: Data science in light of natural language processing: an overview. Routledge (2013)Ībumalloh, R.A., Al-Sarhan, H.M., Ibrahim, O., Abu-Ulbeh, W.: Arabic part-of-speech tagging. In: New Methods in Language Processing, p. Schmid, H.: Probabilistic part-ofispeech tagging using decision trees. Giménez, J., Marquez, L.: SVMTool: a general POS tagger generator based on support vector machines (2004) Association for Computational Linguistics (2000) In: Proceedings of the Sixth Conference on Applied Natural Language Processing, pp. In: FLAIRS Conference (2009)īrants, T.: TnT: a statistical part-of-speech tagger. Henrich, V., Reuter, T., Loftsson, H.: CombiTagger: a system for developing combined taggers. Basically, Arabic PoS taggers are very sensitive to the number of the tagsets used and the text form processed, therefore, four different tagsets and two text forms (i.e., Classical and Modern Standard Arabic) have been used. In fact, this article presents very important topic which concerns, on the one hand, an adaptation of Standard PoS taggers for the Arabic language, and in the other hand conducting very rich and comparative studies and evaluation. Based on these methods, language-independent PoS taggers have been developed namely TnT, SVMTool, and Treetagger. Some well-known probabilistic methods were adapted for PoS tagging such as Hidden Markov Models (HMMs), Support Vector Machines (SVM), and Decision Tree (DT). Therefore, deeper investigation regarding their performance is required especially for under-resourced languages like Arabic. Several PoS taggers and tools are already in service as open source or as commercialized solutions. It is an essential task in several fields, particularly corpus linguistics and Natural Language Processing (NLP). The Part of Speech (PoS) tagging is resolving ambiguity during text processing to assign morphosyntactic tags to each word according to the context.
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