TY - GEN
T1 - Morphological analysis and generation of Arabic Nouns
T2 - 7th International Conference on Language Resources and Evaluation, LREC 2010
AU - Altantawy, Mohamed
AU - Habash, Nizar
AU - Rambow, Owen
AU - Saleh, Ibrahim
N1 - Funding Information:
The work reported in this paper was supported by NSF Award 0329163 and the DARPA GALE program, contracts HR0011-06-C-0023 and HR0011-08-C-0110. We would like to thank Tim Buckwalter, Otakar Smrž, Richard Sproat and Ryan Roth for helpful discussions.
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
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M3 - Conference contribution
AN - SCOPUS:84903611965
T3 - Proceedings of the 7th International Conference on Language Resources and Evaluation, LREC 2010
SP - 851
EP - 858
BT - Proceedings of the 7th International Conference on Language Resources and Evaluation, LREC 2010
A2 - Tapias, Daniel
A2 - Russo, Irene
A2 - Hamon, Olivier
A2 - Piperidis, Stelios
A2 - Calzolari, Nicoletta
A2 - Choukri, Khalid
A2 - Mariani, Joseph
A2 - Mazo, Helene
A2 - Maegaard, Bente
A2 - Odijk, Jan
A2 - Rosner, Mike
PB - European Language Resources Association (ELRA)
Y2 - 17 May 2010 through 23 May 2010
ER -