From Ghazals to Sonnets: Decoding the Polysemous Expressions of Love Across Languages

• URL: http://arxiv.org/abs/2510.15569v1
• Date: Fri, 17 Oct 2025 12:00:09 GMT
• Title: From Ghazals to Sonnets: Decoding the Polysemous Expressions of Love Across Languages
• Authors: Syed Mohammad Sualeh Ali,
• Abstract summary: This paper delves into the intricate world of Urdu poetry, exploring its thematic depths through a lens of polysemy.<n>By focusing on the nuanced differences between three seemingly synonymous words (pyaar, muhabbat, and ishq) we expose a spectrum of emotions and experiences unique to the Urdu language.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: This paper delves into the intricate world of Urdu poetry, exploring its thematic depths through a lens of polysemy. By focusing on the nuanced differences between three seemingly synonymous words (pyaar, muhabbat, and ishq) we expose a spectrum of emotions and experiences unique to the Urdu language. This study employs a polysemic case study approach, meticulously examining how these words are interwoven within the rich tapestry of Urdu poetry. By analyzing their usage and context, we uncover a hidden layer of meaning, revealing subtle distinctions which lack direct equivalents in English literature. Furthermore, we embark on a comparative analysis, generating word embeddings for both Urdu and English terms related to love. This enables us to quantify and visualize the semantic space occupied by these words, providing valuable insights into the cultural and linguistic nuances of expressing love. Through this multifaceted approach, our study sheds light on the captivating complexities of Urdu poetry, offering a deeper understanding and appreciation for its unique portrayal of love and its myriad expressions

Related papers

• Crossing Borders: A Multimodal Challenge for Indian Poetry Translation and Image Generation [14.583411423291233]
  Indian poetry, known for its linguistic complexity and deep cultural resonance, has a rich and varied heritage spanning thousands of years.<n>Despite its cultural significance, existing works on poetry have largely overlooked Indian language poems.<n>We propose the Translation and Image Generation (TAI) framework, leveraging Large Language Models (LLMs) and Latent Diffusion Models.
  arXiv  Detail & Related papers  (2025-11-17T18:41:16Z)
• When Semantics Mislead Vision: Mitigating Large Multimodal Models Hallucinations in Scene Text Spotting and Understanding [75.57997630182136]
  We investigate the underlying causes of semantic hallucination and identify a key finding: Transformer layers in Large Multimodal Models with stronger attention focus on scene text regions are less prone to producing semantic hallucinations.<n>We propose a training-free semantic hallucination mitigation framework comprising two key components: ZoomText and Grounded Layer Correction.<n>Our method not only effectively mitigates semantic hallucination but also achieves strong performance on public benchmarks for scene text spotting and understanding.
  arXiv  Detail & Related papers  (2025-06-05T19:53:19Z)
• Is It JUST Semantics? A Case Study of Discourse Particle Understanding in LLMs [47.462635654670386]
  This work investigates the capacity of LLMs to distinguish the fine-grained senses of English "just"<n>Our findings reveal that while LLMs exhibit some ability to differentiate between broader categories, they struggle to fully capture more subtle nuances.
  arXiv  Detail & Related papers  (2025-06-05T00:59:05Z)
• BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages [93.92804151830744]
  We present BRIGHTER, a collection of multi-labeled, emotion-annotated datasets in 28 different languages.<n>We highlight the challenges related to the data collection and annotation processes.<n>We show that the BRIGHTER datasets represent a meaningful step towards addressing the gap in text-based emotion recognition.
  arXiv  Detail & Related papers  (2025-02-17T15:39:50Z)
• Understanding Literary Texts by LLMs: A Case Study of Ancient Chinese Poetry [9.970908656435066]
  In genres such as poetry, jokes, and short stories, numerous AI tools have emerged, offering refreshing new perspectives. evaluating literary works is often complex and hard to fully quantify, which directly hinders the further development of AI creation. This paper attempts to explore the mysteries of literary texts from the perspective of large language models.
  arXiv  Detail & Related papers  (2024-08-22T04:25:06Z)
• Aesthetics of Sanskrit Poetry from the Perspective of Computational Linguistics: A Case Study Analysis on Siksastaka [11.950202012146498]
  This article explores the intersection of Sanskrit poetry and computational linguistics. We propose a roadmap of an interpretable framework to analyze and classify the qualities and characteristics of fine Sanskrit poetry. We provide a deep analysis of Siksastaka, a Sanskrit poem, from the perspective of 6 prominent kavyashastra schools.
  arXiv  Detail & Related papers  (2023-08-14T11:26:25Z)
• Ashaar: Automatic Analysis and Generation of Arabic Poetry Using Deep Learning Approaches [7.021140304091526]
  This paper introduces a framework called textitAshaar, which encompasses a collection of datasets and pre-trained models designed specifically for the analysis and generation of Arabic poetry. The pipeline established within our proposed approach encompasses various aspects of poetry, such as meter, theme, and era classification. As part of this endeavor, we provide four datasets: one for poetry generation, another for diacritization, and two for Arudi-style prediction.
  arXiv  Detail & Related papers  (2023-07-12T15:07:16Z)
• Multi-lingual and Multi-cultural Figurative Language Understanding [69.47641938200817]
  Figurative language permeates human communication, but is relatively understudied in NLP. We create a dataset for seven diverse languages associated with a variety of cultures: Hindi, Indonesian, Javanese, Kannada, Sundanese, Swahili and Yoruba. Our dataset reveals that each language relies on cultural and regional concepts for figurative expressions, with the highest overlap between languages originating from the same region. All languages exhibit a significant deficiency compared to English, with variations in performance reflecting the availability of pre-training and fine-tuning data.
  arXiv  Detail & Related papers  (2023-05-25T15:30:31Z)
• Exploratory Data Analysis of Urdu Poetry [0.0]
  This study explores the main features of Urdu ghazal that make it popular and admired more than other forms. A detailed explanation is provided as to the types of words used for expressing love, nature, birds, and flowers etc.
  arXiv  Detail & Related papers  (2021-12-03T20:06:11Z)
• Semantics of European poetry is shaped by conservative forces: The relationship between poetic meter and meaning in accentual-syllabic verse [0.0]
  We provide the first large-scale formal evidence of the persistent association between poetic meter and semantics in 18-19th European literatures. Our study traces this association through a series of clustering experiments using the abstracted semantic features of 150,000 poems.
  arXiv  Detail & Related papers  (2021-09-15T08:20:01Z)
• CCPM: A Chinese Classical Poetry Matching Dataset [50.90794811956129]
  We propose a novel task to assess a model's semantic understanding of poetry by poem matching. This task requires the model to select one line of Chinese classical poetry among four candidates according to the modern Chinese translation of a line of poetry. To construct this dataset, we first obtain a set of parallel data of Chinese classical poetry and modern Chinese translation.
  arXiv  Detail & Related papers  (2021-06-03T16:49:03Z)
• MixPoet: Diverse Poetry Generation via Learning Controllable Mixed Latent Space [79.70053419040902]
  We propose MixPoet, a novel model that absorbs multiple factors to create various styles and promote diversity. Based on a semi-supervised variational autoencoder, our model disentangles the latent space into some subspaces, with each conditioned on one influence factor by adversarial training. Experiment results on Chinese poetry demonstrate that MixPoet improves both diversity and quality against three state-of-the-art models.
  arXiv  Detail & Related papers  (2020-03-13T03:31:29Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.