Artificial Intelligence and Polysemy: A ChatGPT-Based Analysis of Arabic

Öz

This study examines the multilayered structure of semantic ambiguity in Arabic and evaluates the capacity of large language models to resolve such ambiguities through the case of ChatGPT. Its significance lies in reconsidering the phenomenon of lebs/iltibās, extensively discussed in classical Arabic linguistic scholarship, within the framework of contemporary artificial intelligence. In this respect, it comparatively analyzes two epistemological paradigms: the traditional philological heritage and statistically driven natural language processing approaches. Methodologically, the study employs stratified sampling of examples exhibiting ambiguity at the lexical, syntactic, semantic, and pragmatic levels. The model’s outputs are subjected to qualitative comparison with classical lexicographical sources and established grammatical criteria. The evaluation focuses on the model’s ability to identify alternative meanings, distinguish grammatical possibilities, incorporate contextual cues, and correspond with historically attested semantic layers. The findings suggest that the model performs relatively well in handling explicit grammatical structures. However, it frequently overlooks low-frequency meanings, historically sedimented nuances, and culturally embedded figurative expressions. The statistical prioritization mechanism tends to foreground a dominant interpretation while suppressing alternatives. In conclusion, although large language models demonstrate a partial capacity to manage Arabic polysemy, they remain limited in replicating human contextual awareness and historical depth. The study therefore emphasizes the necessity of employing such systems with a critical and corroborative approach rather than autonomous epistemic authorities.

Anahtar Kelimeler

• Arabic Language
• Artificial Intelligence
• Semantic Possibilities
• ChatGPT
• Ambiguity

Yapay Zekâ ve Çok Anlamlılık: Arapça İfadelerin ChatGPT ile Analizi

Öz

Bu çalışma, Arapçada anlam belirsizliğinin çok katmanlı yapısını merkeze alarak, büyük dil modellerinin söz konusu belirsizlikleri çözümleme kapasitesini ChatGPT örneği üzerinden değerlendirmeyi amaçlamaktadır. Araştırmanın önemi, klasik Arap dili literatüründe ayrıntılı biçimde tartışılmış olan lebs/iltibâs olgusunu, çağdaş yapay zekâ teknolojileri kapsamında yeniden ele alarak iki farklı bilgi sistemini -geleneksel dilbilimsel birikim ile istatistiksel temelli doğal dil işleme yaklaşımlarını- karşılaştırmalı biçimde analiz etmesinden kaynaklanmaktadır. Çalışmada yöntem olarak, sözcüksel, sözdizimsel, anlambilimsel ve edimsel düzeylerde belirsizlik içeren örnekleri katmanlı örneklem yoluyla seçilmiş; modelin ürettiği yanıtları klasik sözlükler ve dilbilgisel ölçütlerle nitel karşılaştırmaya tabi tutulmuştur. Analiz sürecinde alternatif anlamları tespit edebilme, dilbilgisel olasılıkları ayırt etme, bağlamsal unsurları dikkate alma ve tarihsel anlam katmanlarıyla örtüşme gibi ölçütler esas alınmıştır. Bulgular, modelin biçimsel ve açık dilbilgisel yapılarda görece başarılı olduğunu; ancak düşük sıklıklı anlamları, tarihsel-semiyotik katmanları ve kültürel bağlama dayalı mecazları çoğu zaman göz ardı ettiğini göstermektedir. Özellikle istatistiksel önceliklendirme mekanizmasının tekil anlamı öne çıkararak alternatif ihtimalleri bastırdığı tespit edilmiştir. Sonuç olarak çalışma, büyük dil modellerinin Arapça çok anlamlılığı kısmen yönetebildiğini, ancak insanî bağlam bilgisi ve tarihsel derinliği tam olarak taklit edemediğini ortaya koymakta; bu sistemlerin eleştirel ve teyit edici bir yaklaşımla kullanılması gerektiğini vurgulamaktadır.

Anahtar Kelimeler

• Arap Dili
• Yapay Zekâ
• Anlam İhtimalleri
• ChatGPT
• Dilsel Belirsizlik

Kaynakça

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