The paper titled "Meaning as a Marker of Metaphoricity Towards a Computational Identification of Metaphor in the Ever-Glorious Qur’ān" focuses on establishing a semantic criterion for the computational identification of metaphors in the Qur'ān. The primary research question centers on whether a basic/non-basic meaning criterion can effectively serve as a marker for identifying metaphors within the text.
The purpose of the study is to contribute to computational linguistics by developing a method for detecting metaphors in the Qur'ān, specifically within Sūrat Hūd. The study aims to classify and score metaphors based on their degree of metaphoricity using the proposed semantic criterion.
The methodology involves a three-step process. First, candidate metaphors are manually identified by referring to four authentic exegeses and a widely known interpretation of the Qur'ān. Second, these metaphors are analyzed using the basic/non-basic meaning criterion. Finally, the metaphors are scored along a continuum of metaphoricity, where the degree of deviation from the basic meaning determines the score.
The key findings reveal that the basic/non-basic meaning criterion successfully identifies candidate metaphors and categorizes them by their degree of metaphoricity. Metaphors that deviate significantly from their basic meaning and acquire abstract or figurative interpretations are considered highly metaphorical. The study presents a lexicon-based approach for feeding these findings into a computational system for metaphor detection.
The conclusions of the study suggest that the proposed semantic criterion is an effective linguistic marker for metaphoricity and can be integrated into computational tools for analyzing metaphors in the Qur'ān. The study's implications extend to the broader field of computational linguistics, offering a framework that can be adapted for similar analyses in other texts.