From extended chunking to dependency parsing using traditional Arabic grammar.

We describe in this paper the adopted approach combining a phrase structure grammar and dependency rules to develop AlkhalilPArser. The general architecture of this parser is composed of three main levels. The first level includes basic tasks such as tokenization, part-of-speech tagging, and chunkin...

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Publicado en:Language Resources & Evaluation Vol. 57; no. 3; pp. 1011 - 1044
Autores principales: Ababou, Nabil, Mazroui, Azzeddine, Belehbib, Rachid
Formato: Artículo
Publicado: Springer Nature Sep2023
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: From extended chunking to dependency parsing using traditional Arabic grammar.
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        au:
          Ababou, Nabil
          Mazroui, Azzeddine
          Belehbib, Rachid
        affil:
          Systems Engineering Laboratory, Faculty of Science and Technology, Sultan Moulay Slimane University, Beni Mellal, Morocco
          LaRI Laboratory, Faculty of Sciences, Mohammed First University, Oujda, Morocco
          LaRI Laboratory, Faculty of Arts and Humanities, University Mohammed First, Oujda, Morocco
      su:
        Grammar
        Task analysis
        Arabic language
      sug:
        subj:
          Grammar
          Task analysis
          Arabic language
      keyword:
        Chunking
        Dependency relation
        Parsing
        Phrases
      ab: We describe in this paper the adopted approach combining a phrase structure grammar and dependency rules to develop AlkhalilPArser. The general architecture of this parser is composed of three main levels. The first level includes basic tasks such as tokenization, part-of-speech tagging, and chunking. The next level deals with analysis tasks such as managing common, internal and external dependencies according to the nature of the proposal. The last level detects and corrects anomalies. This parser is an extension to verbal sentences of a system previously designed for parsing the nominal sentences. Several modifications have been made to adapt this system to all types of sentences and improve its accuracy. The tests carried out on a representative corpus and the comparisons with other parsers testify to the robustness of our system.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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      custom: Language Resources & Evaluation is a copyright of Springer, 2023. All Rights Reserved.
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