An XML-based semantic parser for traditional arabic

Alrabiah, Maha; Al-Salman, AbdulMalik S.

doi:10.1109/iucs.2010.5666184

Cited by 2 publications

(3 citation statements)

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“…Evaluate the accuracy of the model as a whole including the ontology by comparing the model results to the actual results based on a pre-parsed set of sentences representing all possibilities of verbal sentence. This is followed by briefly comparing the model to the XML semantic parser proposed by Al-Rabiah & Al-Salman [3] which is used to resolve parsing problems based on defined parsing-related factors.…”

Section: Model Evaluationmentioning

confidence: 99%

“…Other semantic parsing approach such as [3] has collected traditional Arabic grammar rules and presented them into extended Backus Normal Form (EBNF) grammar to serve as a base for other Arabic NLP researches. They presented the architecture of an XML-based semantic parser.…”

Section: Semantic Approachesmentioning

confidence: 99%

“…Compared to the XML-based semantic parser of Al-Rabiah & Al-Salman [3], our AVSP model uses OWL (which is more expressive than XML) as a formalism to represent Arabic grammar rules while their parser uses XML only to represent the grammar rules. AVSP depends on the syntactic analysis using morphological analyzers to reduce the word"s possibilities.…”

Section: Evaluating the Avsp Modelmentioning

confidence: 99%

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Parsing Arabic Verbal Sentence Using Grammar Ontology

2021

JERT

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We build a model to parse the Arabic verbal sentence based on Arabic grammar ontology. The ontology conceptualizes the Arabic verbal sentence through the representation of grammar parsing classes, verb properties, and conjunction checking. By populating the ontology with verbal sentences and adding grammar rules, we form a verbal sentence knowledge base. The parsing model is supported by morphological analysis for sentence syntactic analysis and supported by Arabic synonyms extractor for deriving synonyms. We have implemented the model and have provided it with a user interface where the user can enter a sentence to be parsed and obtains the parsing results. The interface has the options to partially or totally add diacritics to the words of the sentence and it has the possibility to remove ambiguity by choosing the most appropriate analysis from lexicon results. To evaluate the model, we have selected a representative set of Arabic verbal sentences from Arabic grammar books that represent all the possibilities of a verbal sentence. We have performed several parsing tests on these sentences with and without diacritics. The results prove the ability of the model to parse the various forms of the verbal sentence. The accuracy increases when the sentence is diacriticized while avoiding free word order and following the Arabic verbal sentence general form.

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Section: Model Evaluationmentioning

confidence: 99%

Section: Semantic Approachesmentioning

confidence: 99%

Section: Evaluating the Avsp Modelmentioning

confidence: 99%

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