Summary of the paper
| Title | Morphological Analysis and Generation of Arabic Nouns: A Morphemic Functional Approach |
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| Authors | Mohamed Altantawy, Nizar Habash, Owen Rambow and Ibrahim Saleh |
| Abstract | MAGEAD is a morphological analyzer and generator for Modern Standard Arabic (MSA) and its dialects. We introduced MAGEAD in previous work with an implementation of MSA and Levantine Arabic verbs. In this paper, we port that system to MSA nominals (nouns and adjectives), which are far more complex to model than verbs. Our system is a functional morphological analyzer and generator, i.e., it analyzes to and generates from a representation consisting of a lexeme and linguistic feature-value pairs, where the features are syntactically (and perhaps semantically) meaningful, rather than just morphologically. A detailed evaluation of the current implementation comparing it to a commonly used morphological analyzer shows that it has good morphological coverage with precision and recall scores in the 90s. An error analysis reveals that the majority of recall and precision errors are problems in the gold standard or a result of the discrepancy between different models of form-based/functional morphology. |
| Topics | Morphology, Tools, systems, applications, Lexicon, lexical database |
Full paper |
Morphological Analysis and Generation of Arabic Nouns: A Morphemic Functional Approach |
Slides |
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| Bibtex | @InProceedings{ALTANTAWY10.442, author = {Mohamed Altantawy and Nizar Habash and Owen Rambow and Ibrahim Saleh}, title = {Morphological Analysis and Generation of Arabic Nouns: A Morphemic Functional Approach}, booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |