Graph-Assisted Culturally Adaptable Idiomatic Translation for Indic Languages

• URL: http://arxiv.org/abs/2505.21937v1
• Date: Wed, 28 May 2025 03:42:16 GMT
• Title: Graph-Assisted Culturally Adaptable Idiomatic Translation for Indic Languages
• Authors: Pratik Rakesh Singh, Kritarth Prasad, Mohammadi Zaki, Pankaj Wasnik,
• Abstract summary: Translating multi-word expressions (MWEs) and idioms requires a deep understanding of both the source and target languages.<n>Traditional static knowledge graphs (KGs) and prompt-based approaches struggle to capture these complex relationships.<n>We propose an adaptive graph neural network (GNN) based methodology that learns intricate mappings between idiomatic expressions.
• Score: 3.2498796510544636
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Translating multi-word expressions (MWEs) and idioms requires a deep understanding of the cultural nuances of both the source and target languages. This challenge is further amplified by the one-to-many nature of idiomatic translations, where a single source idiom can have multiple target-language equivalents depending on cultural references and contextual variations. Traditional static knowledge graphs (KGs) and prompt-based approaches struggle to capture these complex relationships, often leading to suboptimal translations. To address this, we propose IdiomCE, an adaptive graph neural network (GNN) based methodology that learns intricate mappings between idiomatic expressions, effectively generalizing to both seen and unseen nodes during training. Our proposed method enhances translation quality even in resource-constrained settings, facilitating improved idiomatic translation in smaller models. We evaluate our approach on multiple idiomatic translation datasets using reference-less metrics, demonstrating significant improvements in translating idioms from English to various Indian languages.

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