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MADAMIRA: A Fast, Comprehensive Tool for Morphological Analysis and Disambiguation of Arabic
MADAMIRA is a system for morphological analysis and disambiguation of Arabic that combines some of the best aspects of two previously commonly used systems for Arabic processing with a more streamlined Java implementation that is more robust, portable, extensible, and is faster than its ancestors by more than an order of magnitude. Expand
Introduction to Arabic Natural Language Processing
  • Nizar Habash
  • Computer Science
  • Introduction to Arabic Natural Language…
  • 30 August 2010
The goal is to introduce Arabic linguistic phenomena and review the state-of-the-art in Arabic processing to provide system developers and researchers in natural language processing and computational linguistics with the necessary background information for working with the Arabic language. Expand
Arabic Tokenization, Part-of-Speech Tagging and Morphological Disambiguation in One Fell Swoop
An approach to using a morphological analyzer for tokenizing and morphologically tagging Arabic words in one process using classifiers for individual morphological features, as well as ways of using these classifiers to choose among entries from the output of the analyzer. Expand
MADA + TOKAN : A Toolkit for Arabic Tokenization , Diacritization , Morphological Disambiguation , POS Tagging , Stemming and Lemmatization
We describe the MADA+TOKAN toolkit, a versatile and freely available system that can derive extensive morphological and contextual information from raw Arabic text, and then use this information forExpand
CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
The task and evaluation methodology is defined, how the data sets were prepared, report and analyze the main results, and a brief categorization of the different approaches of the participating systems are provided. Expand
Arabic Morphological Tagging, Diacritization, and Lemmatization Using Lexeme Models and Feature Ranking
We investigate the tasks of general morphological tagging, diacritization, and lemmatization for Arabic. We show that for all tasks we consider, both modeling the lexeme explicitly, and retuning theExpand
Arabic Diacritization through Full Morphological Tagging
We present a diacritization system for written Arabic which is based on a lexical resource. It combines a tagger and a lexeme language model. It improves on the best results reported in theExpand
Morphological Annotation of Quranic Arabic
How the unique challenge of morphological annotation of Quranic Arabic is solved using a multi-stage approach is discussed, which includes automatic morphological tagging using diacritic edit-distance, two-pass manual verification, and online collaborative annotation. Expand
Overview of the SPMRL 2013 Shared Task: A Cross-Framework Evaluation of Parsing Morphologically Rich Languages
This paper presents and analyzes parsing results obtained by the task participants, and provides an analysis and comparison of the parsers across languages and frameworks, reported for gold input as well as more realistic parsing scenarios. Expand
Universal Dependencies 2.1
The annotation scheme is based on (universal) Stanford dependencies, Google universal part-of-speech tags, and the Interset interlingua for morphosyntactic tagsets for morpho-lingual tagsets. Expand