Tagging inflective languages: prediction of morphological categories for a rich, structured tagset
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Improving Arabic dependency parsing with lexical and inflectional morphological features
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HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
A corpus for modeling morpho-syntactic agreement in Arabic: gender, number and rationality
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
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
Dependency parsing of modern standard arabic with lexical and inflectional features
Computational Linguistics
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We explore the contribution of morphological features -- both lexical and inflectional -- to dependency parsing of Arabic, a morphologically rich language. Using controlled experiments, we find that definiteness, person, number, gender, and the undiacritzed lemma are most helpful for parsing on automatically tagged input. We further contrast the contribution of form-based and functional features, and show that functional gender and number (e.g., "broken plurals") and the related rationality feature improve over form-based features. It is the first time functional morphological features are used for Arabic NLP.