University of Isfahan Literary Arts 20088027 18 1 2026 03 21 Explicating Saʿdi’s Sahl e Momtaneʿ Composition Strategies from the Perspective of Artificial Intelligence Explicating Saʿdi’s Sahl e Momtaneʿ Composition Strategies from the Perspective of Artificial Intelligence 105 132 29969 10.22108/liar.2025.145185.2454 FA Mostafa Mirdar Rezaei Assistant Professor, Department of Persian Language and Literature, Faculty of Literature and Human Sciences, University of Guilan, Rasht, Iran Journal Article 2025 05 07 The present study adopts a mixed‑methods approach, combining an empirical framework (for data collection) and a descriptive–analytical framework (for data analysis), to elucidate Saʿdi’s Sahl‑e Momtaneʿ (“deceptive simplicity”) composition strategies through the lens of artificial intelligence. In the empirical phase, a selected ghazal by Saʿdi was submitted as input to four intelligent models—Grok‑3, ChatGPT, Gemini, and DeepSeek. In the analytical phase, the outputs produced by these models were examined, compared, and evaluated, with the dual aim of both identifying the strategies underlying Saʿdi’s Sahl‑e Momtaneʿ style from the perspective of artificial intelligence and assessing the analytical potential of these intelligent tools in literary studies. The findings of the study reveal that all four AI models provided successful definitions and explanations of the Sahl‑e Momtaneʿ concept, identifying its core components in Saʿdi’s ghazal as: linguistic simplicity, depth of meaning, vivid imagery, musicality, conciseness, ambiguity, and universality. Moreover, artificial intelligence demonstrated capacities such as detecting hidden patterns, analyzing the syntactic function of prepositions, evaluating the impact of meter and rhyme, and interpreting semantic contrasts. These analyses indicate that Sahl‑e Momtaneʿ in Saʿdi’s poetry derives not only from the use of plain, fluent language, but also from an intricate network of semantic relations, subtle literary devices, and an intense experiential engagement with themes of love and the human condition. Keywords: Saʿdi; Sahl‑e Momtaneʿ (Deceptive Simplicity); Artificial Intelligence; Literary Analysis. Introduction Literary studies represent one of the most promising areas in which the capabilities of artificial intelligence (AI) can be meaningfully manifested. The present research seeks, on one hand, to elucidate the elements and mechanisms of Saʿdi’s Sahl‑e Momtaneʿ (“deceptive simplicity”) from the perspective of artificial intelligence, and, on the other hand, to assess, analyze, and evaluate the potential of large language models (LLMs) in interpreting classical Persian texts—here, Saʿdi’s ghazals. The study addresses the following three research questions: Does artificial intelligence comprehend the concept of Sahl‑e Momtaneʿ? To what extent do AI-generated responses resemble human intellectual reasoning? Has artificial intelligence identified any strategies of Sahl‑e Momtaneʿ composition in Saʿdi’s poetry that might remain unnoticed from a human perspective? Materials and Methods This study employs a mixed‑method design, combining an empirical and a descriptive–analytical approach to explore Saʿdi’s Sahl‑e Momtaneʿ style through the lens of artificial intelligence. In the empirical phase, a selected ghazal by Saʿdi was provided as input to four intelligent models—Grok‑3, ChatGPT, Gemini, and DeepSeek. In the analytical phase, the responses produced by these models were systematically examined, compared, and evaluated, both to explicate Saʿdi’s strategies of Sahl‑e Momtaneʿ poetry as understood by AI and to assess the analytical capacities of these tools within the scope of literary inquiry. Research Findings Each AI model articulated specific features and mechanisms underlying Saʿdi’s Sahl‑e Momtaneʿ poetry: Grok‑3 attributes Saʿdi’s mastery of Sahl‑e Momtaneʿ to seven key factors: (1) simplicity and fluency of language; (2) emotional and semantic depth; (3) natural musical rhythm; (4) simple yet powerful imagery; (5) narrative coherence and internal consistency; (6) conciseness; and (7) universality and empathy. ChatGPT identifies five indicators of Sahl‑e Momtaneʿ: (1) linguistic simplicity coupled with depth of meaning; (2) contrast and paradox; (3) imagery and visualization; (4) repetition and emphasis; and (5) poetical self-awareness. Its analysis follows a structuralist orientation, with special focus on linguistic microstructures—particularly the precise role of Persian prepositions. Gemini investigates the concept on two levels. At the macro level, it introduces (1) linguistic simplicity (Sahl) and (2) depth of meaning and theme (Momtaneʿ) as complementary factors, illustrating them through textual samples. At the micro level, it delineates three analytic dimensions: (1) linguistic–syntactic, (2) rhetorical–imagistic, and (3) semantic–emotional. DeepSeek enumerates six attributes that define Sahl‑e Momtaneʿ in Saʿdi’s poetry: (1) fluent and transparent language; (2) semantic depth beneath simplicity (via natural similes, subtle paradoxes, and implicit metaphors); (3) inner musicality and rhythmic flow; (4) brevity and precision; (5) universal emotions in personal expression; and (6) latent artistic delicacy (such as imperceptible allusions and harmony between sound and meaning). Discussion of Results and Conclusions A comparative evaluation of these analyses reveals both convergences and distinctive emphases among the four AI models: Simple and Fluent Language: All models underscore Saʿdi’s linguistic simplicity as the core of Sahl‑e Momtaneʿ. ChatGPT and Grok‑3 highlight natural diction and conversational fluency, whereas Gemini and DeepSeek emphasize the lack of rhetorical complexity. The first two employ structural and statistical analyses of vocabulary and syntax, while the latter pair link linguistic simplicity to mystical depth and humanistic meaning. Emotional and Semantic Depth: Shared across all models, this dimension is accentuated differently—Grok‑3 and DeepSeek focus on affective intensity and hidden metaphors; ChatGPT and Gemini attend to semantic depth and organic imagery. Musicality and Natural Rhythm: Each model acknowledges Saʿdi’s internal rhythm and euphonic balance. ChatGPT and Grok‑3 attribute it to repetition and rhyme alignment, while DeepSeek explicates it through phonetic synergy—such as the harmony between “hearing” (samʿ) and “seeing” (baṣar) in verse 6—reflecting Saʿdi’s awareness of Persian sound patterns. Gemini analyzes this aspect less extensively. Imagery and Conciseness: ChatGPT and Grok‑3 stress the suggestive impact and economy of expression, often through wordplay and ambiguity; Gemini and DeepSeek focus on implicit metaphors (e.g., “the elixir of love”) and the balance between word and meaning. Narrative Structure and Internal Coherence: Grok‑3 and DeepSeek perceive narrative unity across the verses, interpreting the poem as an integrated emotional experience. Universality and Empathy: All AIs converge on the universality of Saʿdi’s portrayal of love. Grok‑3 ascribes it to narrative coherence, whereas DeepSeek relates it to the union of simplicity and shared human experience—together showing that Sahl‑e Momtaneʿ transcends the boundary between poetry and philosophy by transforming the individual into the universal. Artistic Subtlety: ChatGPT and DeepSeek emphasize multilayered meanings and rhetorical delicacy, while Grok‑3 and Gemini highlight artistic craftsmanship and unobtrusive allusions. Overall, the findings demonstrate that all four artificial intelligences successfully define and interpret Sahl‑e Momtaneʿ as poetry that appears deceptively simple and fluent on the surface but conceals structural, semantic, and aesthetic complexities that defy imitation. Notably, their analyses reveal the following capabilities of AI in literary studies: Pattern Recognition: Detecting recurring lexical, structural, and sensory motifs often overlooked by traditional human readings. Fine‑grained Syntactic Analysis: Investigating the semantic depth created by prepositional choices and subtle grammatical relations. Prosodic Evaluation: Assessing the influence of meter and rhyme on lexical selection and rhythmic balance. Interpretation of Semantic Contrasts: Identifying nuanced contradictions embedded within the poem’s emotional structure. Ultimately, this research indicates that Sahl‑e Momtaneʿ in Saʿdi’s poetry arises not merely from plain and fluent diction, but from a complex semantic network, refined literary devices, and profound experiential insight into love and human emotion. Through systematic analysis of these elements, artificial intelligence demonstrates an enhanced capacity to apprehend this multilayered phenomenon, revealing Sahl‑e Momtaneʿ as the fusion of linguistic simplicity with intricate semantic interrelations and the deep embodiment of the human condition. The present study adopts a mixed‑methods approach, combining an empirical framework (for data collection) and a descriptive–analytical framework (for data analysis), to elucidate Saʿdi’s Sahl‑e Momtaneʿ (“deceptive simplicity”) composition strategies through the lens of artificial intelligence. In the empirical phase, a selected ghazal by Saʿdi was submitted as input to four intelligent models—Grok‑3, ChatGPT, Gemini, and DeepSeek. In the analytical phase, the outputs produced by these models were examined, compared, and evaluated, with the dual aim of both identifying the strategies underlying Saʿdi’s Sahl‑e Momtaneʿ style from the perspective of artificial intelligence and assessing the analytical potential of these intelligent tools in literary studies. The findings of the study reveal that all four AI models provided successful definitions and explanations of the Sahl‑e Momtaneʿ concept, identifying its core components in Saʿdi’s ghazal as: linguistic simplicity, depth of meaning, vivid imagery, musicality, conciseness, ambiguity, and universality. Moreover, artificial intelligence demonstrated capacities such as detecting hidden patterns, analyzing the syntactic function of prepositions, evaluating the impact of meter and rhyme, and interpreting semantic contrasts. These analyses indicate that Sahl‑e Momtaneʿ in Saʿdi’s poetry derives not only from the use of plain, fluent language, but also from an intricate network of semantic relations, subtle literary devices, and an intense experiential engagement with themes of love and the human condition. Keywords: Saʿdi; Sahl‑e Momtaneʿ (Deceptive Simplicity); Artificial Intelligence; Literary Analysis. Introduction Literary studies represent one of the most promising areas in which the capabilities of artificial intelligence (AI) can be meaningfully manifested. The present research seeks, on one hand, to elucidate the elements and mechanisms of Saʿdi’s Sahl‑e Momtaneʿ (“deceptive simplicity”) from the perspective of artificial intelligence, and, on the other hand, to assess, analyze, and evaluate the potential of large language models (LLMs) in interpreting classical Persian texts—here, Saʿdi’s ghazals. The study addresses the following three research questions: Does artificial intelligence comprehend the concept of Sahl‑e Momtaneʿ? To what extent do AI-generated responses resemble human intellectual reasoning? Has artificial intelligence identified any strategies of Sahl‑e Momtaneʿ composition in Saʿdi’s poetry that might remain unnoticed from a human perspective? Materials and Methods This study employs a mixed‑method design, combining an empirical and a descriptive–analytical approach to explore Saʿdi’s Sahl‑e Momtaneʿ style through the lens of artificial intelligence. In the empirical phase, a selected ghazal by Saʿdi was provided as input to four intelligent models—Grok‑3, ChatGPT, Gemini, and DeepSeek. In the analytical phase, the responses produced by these models were systematically examined, compared, and evaluated, both to explicate Saʿdi’s strategies of Sahl‑e Momtaneʿ poetry as understood by AI and to assess the analytical capacities of these tools within the scope of literary inquiry. Research Findings Each AI model articulated specific features and mechanisms underlying Saʿdi’s Sahl‑e Momtaneʿ poetry: Grok‑3 attributes Saʿdi’s mastery of Sahl‑e Momtaneʿ to seven key factors: (1) simplicity and fluency of language; (2) emotional and semantic depth; (3) natural musical rhythm; (4) simple yet powerful imagery; (5) narrative coherence and internal consistency; (6) conciseness; and (7) universality and empathy. ChatGPT identifies five indicators of Sahl‑e Momtaneʿ: (1) linguistic simplicity coupled with depth of meaning; (2) contrast and paradox; (3) imagery and visualization; (4) repetition and emphasis; and (5) poetical self-awareness. Its analysis follows a structuralist orientation, with special focus on linguistic microstructures—particularly the precise role of Persian prepositions. Gemini investigates the concept on two levels. At the macro level, it introduces (1) linguistic simplicity (Sahl) and (2) depth of meaning and theme (Momtaneʿ) as complementary factors, illustrating them through textual samples. At the micro level, it delineates three analytic dimensions: (1) linguistic–syntactic, (2) rhetorical–imagistic, and (3) semantic–emotional. DeepSeek enumerates six attributes that define Sahl‑e Momtaneʿ in Saʿdi’s poetry: (1) fluent and transparent language; (2) semantic depth beneath simplicity (via natural similes, subtle paradoxes, and implicit metaphors); (3) inner musicality and rhythmic flow; (4) brevity and precision; (5) universal emotions in personal expression; and (6) latent artistic delicacy (such as imperceptible allusions and harmony between sound and meaning). Discussion of Results and Conclusions A comparative evaluation of these analyses reveals both convergences and distinctive emphases among the four AI models: Simple and Fluent Language: All models underscore Saʿdi’s linguistic simplicity as the core of Sahl‑e Momtaneʿ. ChatGPT and Grok‑3 highlight natural diction and conversational fluency, whereas Gemini and DeepSeek emphasize the lack of rhetorical complexity. The first two employ structural and statistical analyses of vocabulary and syntax, while the latter pair link linguistic simplicity to mystical depth and humanistic meaning. Emotional and Semantic Depth: Shared across all models, this dimension is accentuated differently—Grok‑3 and DeepSeek focus on affective intensity and hidden metaphors; ChatGPT and Gemini attend to semantic depth and organic imagery. Musicality and Natural Rhythm: Each model acknowledges Saʿdi’s internal rhythm and euphonic balance. ChatGPT and Grok‑3 attribute it to repetition and rhyme alignment, while DeepSeek explicates it through phonetic synergy—such as the harmony between “hearing” (samʿ) and “seeing” (baṣar) in verse 6—reflecting Saʿdi’s awareness of Persian sound patterns. Gemini analyzes this aspect less extensively. Imagery and Conciseness: ChatGPT and Grok‑3 stress the suggestive impact and economy of expression, often through wordplay and ambiguity; Gemini and DeepSeek focus on implicit metaphors (e.g., “the elixir of love”) and the balance between word and meaning. Narrative Structure and Internal Coherence: Grok‑3 and DeepSeek perceive narrative unity across the verses, interpreting the poem as an integrated emotional experience. Universality and Empathy: All AIs converge on the universality of Saʿdi’s portrayal of love. Grok‑3 ascribes it to narrative coherence, whereas DeepSeek relates it to the union of simplicity and shared human experience—together showing that Sahl‑e Momtaneʿ transcends the boundary between poetry and philosophy by transforming the individual into the universal. Artistic Subtlety: ChatGPT and DeepSeek emphasize multilayered meanings and rhetorical delicacy, while Grok‑3 and Gemini highlight artistic craftsmanship and unobtrusive allusions. Overall, the findings demonstrate that all four artificial intelligences successfully define and interpret Sahl‑e Momtaneʿ as poetry that appears deceptively simple and fluent on the surface but conceals structural, semantic, and aesthetic complexities that defy imitation. Notably, their analyses reveal the following capabilities of AI in literary studies: Pattern Recognition: Detecting recurring lexical, structural, and sensory motifs often overlooked by traditional human readings. Fine‑grained Syntactic Analysis: Investigating the semantic depth created by prepositional choices and subtle grammatical relations. Prosodic Evaluation: Assessing the influence of meter and rhyme on lexical selection and rhythmic balance. Interpretation of Semantic Contrasts: Identifying nuanced contradictions embedded within the poem’s emotional structure. Ultimately, this research indicates that Sahl‑e Momtaneʿ in Saʿdi’s poetry arises not merely from plain and fluent diction, but from a complex semantic network, refined literary devices, and profound experiential insight into love and human emotion. Through systematic analysis of these elements, artificial intelligence demonstrates an enhanced capacity to apprehend this multilayered phenomenon, revealing Sahl‑e Momtaneʿ as the fusion of linguistic simplicity with intricate semantic interrelations and the deep embodiment of the human condition.

https://liar.ui.ac.ir/article_29969_cce98f84db6f0482d6a77490ae98bd56.pdf