Syntactic Parsing of Simple Arabic Nominal Sentence Using the NooJ Linguistic Platform

Bourahma, Said; Mbarki, Samir; Mourchid, Mohammed; Mouloudi, Abdelaziz

doi:10.1007/978-3-319-73500-9_18

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…Some works have made notable contributions in this area. Bourahma et al [21] developed a parser on the NooJ platform that recognizes and annotates all possible grammatical structures of simple Arabic nominal sentences. In addition, the authors implemented a set of syntactic grammars that model Arabic NP structures.…”

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confidence: 99%

Syntactic analysis of complex sentences containing Arabic psychological verbs

Amzali,

Kourtin,

Mourchid

et al. 2024

IJEECS

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Complex Arabic sentences, especially those containing Arabic psychological verbs, follow a common underlying structure characterized by two essential components: the predicate and the subject. In addition, there are two optional elements: the head and the complement. These sentences, rooted in basic noun phrases (NPs), can be expanded within the predicate, subject, or complement, resulting in compound structures. This study aims to develop a syntactic analyzer for parsing complex sentences containing Arabic psychological verbs. To achieve this, we will use the dictionary generated from the lexicon-grammar table of Arabic psychological verbs, which contains all lexical, syntactic, semantic, and transformational information related to these verbs. Then, we will extend an existing analyzer to recognize and label all grammatical structures within complex sentences containing Arabic psychological verbs. Finally, we will evaluate the efficiency of this analyzer through tests on different texts and corpora.

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Syntactic analysis of complex sentences containing Arabic psychological verbs

Amzali,

Kourtin,

Mourchid

et al. 2024

IJEECS

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“…In particular, dictionaries linked to their grammars provide simple solutions for the weakness mentioned above. NooJ text annotation systems can easily refer to syntactical grammars to solve the previous-mentioned ambiguity problem [5]- [8]. Furthermore, adding local, morphological, and syntactical grammars to the linguistic resources solve problems that may appear during the resource testing; this process is much easier than modifying the reference corpus.…”

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confidence: 99%

“…Two different uses of Arabic masdar can be distinguished. [5], verbal use and nominal use. Therefore, we have applied a transformational rule using our resources, which allows the transformation of the nominal phrases into verbal ones.…”

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confidence: 99%

The use of Arabic linguistic resources to develop learning applications

Blanchete

Mourchid

2022

IJEECS

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<span>This paper aims at explaining how Arabic linguistic resources are generated and exploited to enhance Arabic acquisition. We have adopted the root and pattern approach to generate our resources using the linguistic NooJ platform. This work has been carried out in two phases: generating the linguistic resources and developing the application that exploits the pre-built resources. First, we have generated three different resources: comprehensive verbs and masdar resources linked to each other. A nouns-and-adjectives resource, where nouns and adjectives are linked to their broken plural forms. NooJ calls these resources to apply linguistic analysis to a given corpus and returns detailed annotations, which provides accurate morphological, syntactical, and semantic properties of each analyzed word. We have also used the mixed nature of Arabic masdar to implement transformational rules, which generate nominal sentences from verbal ones and vice versa. Second, we have developed an application that provides valuable learning functionalities, like full/semi verb conjugation, the extraction of broken plural forms of a given singular form, the extraction of masdar forms of a given verb form, and return words that share the same root. The developed application can be used by teachers, students/learners, and computational linguists interested in Arabic acquisition.</span>

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