Tagging inflective languages: prediction of morphological categories for a rich, structured tagset
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Three-dimensional parametrization for parsing morphologically rich languages
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Improving Arabic dependency parsing with form-based and functional morphological features
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IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
Morphological features for parsing morphologically-rich languages: a case of Arabic
SPMRL '11 Proceedings of the Second Workshop on Statistical Parsing of Morphologically Rich Languages
Identifying broken plurals, irregular gender, and rationality in Arabic text
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Getting more from morphology in multilingual dependency parsing
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Part of speech tagging for arabic
Natural Language Engineering
Morphological and syntactic case in statistical dependency parsing
Computational Linguistics
Dependency parsing of modern standard arabic with lexical and inflectional features
Computational Linguistics
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We explore the contribution of different lexical and inflectional morphological features to dependency parsing of Arabic, a morphologically rich language. We experiment with all leading POS tagsets for Arabic, and introduce a few new sets. We show that training the parser using a simple regular expressive extension of an impoverished POS tagset with high prediction accuracy does better than using a highly informative POS tagset with only medium prediction accuracy, although the latter performs best on gold input. Using controlled experiments, we find that definiteness (or determiner presence), the so-called phi-features (person, number, gender), and undi-acritzed lemma are most helpful for Arabic parsing on predicted input, while case and state are most helpful on gold.