Abstract
The identification of psychological verbs is very important in corpora analyses in order to give the polarity of a given text and define the emotional component. The classification of those verbs represents a challenge for linguists since they classify them according to their needs and their understanding. The aim of this paper is the identification and classification of Arabic psychological verbs through lexicon-grammar tables that are well structured, easy to use for linguists and allow them to describe all the grammatical, syntactic and semantic characteristics of the lexicon. In this work we create lexicon-grammar tables of Arabic psychological verbs with about 400 verbs entries in three main classes and subclasses to use them in lexical, syntactic and semantic analyzers. Using NooJ as an automatic natural language processing platform, we can automatically recognize Arabic psychological verbs by transforming our lexicon-grammar tables into NooJ dictionaries and syntactic grammars enabling the detection of those verbs in texts and corpora.
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Amzali, A., Kourtin, A., Mourchid, M., Mouloudi, A., Mbarki, S. (2020). Lexicon-Grammar Tables Development for Arabic Psychological Verbs. In: Fehri, H., Mesfar, S., Silberztein, M. (eds) Formalizing Natural Languages with NooJ 2019 and Its Natural Language Processing Applications. NooJ 2019. Communications in Computer and Information Science, vol 1153. Springer, Cham. https://doi.org/10.1007/978-3-030-38833-1_2
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