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International Journal of Speech Technology
Erschienen in: International Journal of Speech Technology 2/2017

02.05.2017

Semantic role labeling for Arabic language using case-based reasoning approach

verfasst von: Hamza Meguehout, Tahar Bouhadada, Mohamed Tayeb Laskri

Erschienen in: International Journal of Speech Technology | Ausgabe 2/2017

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Abstract

Many natural language processing areas use semantic roles in order to improve the applications of the extracted information, the question answering and the machine translation, etc. In Arabic, the work of constructing the semantic role labeling system or the annotated corpus is extremely limited compared to their speaker’s number and to English language as well. In this paper, we present a supervised method for the semantic role labeling of Arabic sentences. Hence, we use the feedback capacity of the case-based reasoning to annotate new sentences from already annotated ones besides the use of the Arabic PropBank as a reference to the semantic labels. We test our method under a wide range corpus that contains 2332 attributes and 5291 arguments. Accordingly, an Arabic semantic role labeling system is tested, for the first time, in that corpus. As a result, our method shows the ability to annotate new sentences from the labeled sentences or the construction of the annotated corpus.
Vorheriger Artikel An algorithm for characterizing pre-fuzzified linguistic nuance using artificial neural network
Nächster Artikel Speech enhancement using MMSE estimation under phase uncertainty

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Metadaten
Titel
Semantic role labeling for Arabic language using case-based reasoning approach
verfasst von
Hamza Meguehout
Tahar Bouhadada
Mohamed Tayeb Laskri
Publikationsdatum
02.05.2017
Verlag
Springer US
Erschienen in
International Journal of Speech Technology / Ausgabe 2/2017
Print ISSN: 1381-2416
Elektronische ISSN: 1572-8110
DOI
https://doi.org/10.1007/s10772-017-9412-6

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