Summary of the paper

Title Using Stem-Templates to Improve Arabic POS and Gender/Number Tagging
Authors Kareem Darwish, Ahmed Abdelali and Hamdy Mubarak
Abstract This paper presents an end-to-end automatic processing system for Arabic. The system performs: correction of common spelling errors pertaining to different forms of alef, ta marbouta and ha, and alef maqsoura and ya; context sensitive word segmentation into underlying clitics, POS tagging, and gender and number tagging of nouns and adjectives. We introduce the use of stem templates as a feature to improve POS tagging by 0.5\% and to help ascertain the gender and number of nouns and adjectives. For gender and number tagging, we report accuracies that are significantly higher on previously unseen words compared to a state-of-the-art system.
Topics Part-of-Speech Tagging
Full paper Using Stem-Templates to Improve Arabic POS and Gender/Number Tagging
Bibtex @InProceedings{DARWISH14.335,
  author = {Kareem Darwish and Ahmed Abdelali and Hamdy Mubarak},
  title = {Using Stem-Templates to Improve Arabic POS and Gender/Number Tagging},
  booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)},
  year = {2014},
  month = {may},
  date = {26-31},
  address = {Reykjavik, Iceland},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-8-4},
  language = {english}
 }
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