An intelligent tool for syntactic annotation of Arabic corpora

  • Authors:

  • Chiraz Ben Othmane Zribi;Feriel Ben Fraj;Mohamed Ben Ahmed

  • Affiliations:

  • RIADI Laboratory, National School of Computer Science, La Manouba University, La Manouba, Tunisia.;RIADI Laboratory, National School of Computer Science, La Manouba University, La Manouba, Tunisia.;RIADI Laboratory, National School of Computer Science, La Manouba University, La Manouba, Tunisia

  • Venue:
  • International Journal of Computer Applications in Technology
  • Year:
  • 2011

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Abstract

In this paper, we propose a new technique for semi-automatic syntactic annotation of Arabic corpora. We describe a tool that takes a morpho-syntactic tagged corpus as an input and provides its syntactic annotation as output according to the ArabTAG formalism. We say it is 'intelligent' because this tool automatically learns and improves during elementary annotation (supertagging). It applies a supervised classification method that combines three classifiers (Naive Bayes, K-Nearest Neighbours, Decision tree). In order to evaluate the ability of this tool to acquire information from human intervention, we present an experimental protocol for a small Treebank of 5000 words.