What does “spill the tea” mean? (Not a kitchen disaster)
Idioms are expressions where words do not mean what they say, and that is exactly where AI starts to struggle.
Humans understand them naturally. Machines… not so much.
Most existing idiom datasets are small, limited, not multilingual, and focused on simple tasks. In short, they do not reflect how people communicate.
IdiomX was built through a structured and scalable pipeline:
The pipeline is modular and extensible, making it easy to scale to new languages and add richer annotations.
The full workflow was implemented using Python, combining data engineering pipelines with LLM-based enrichment and validation to ensure reproducibility and scalability.
IdiomX supports multiple tasks:
Models were trained and evaluated on structured train and test splits with careful data selection to avoid leakage and ensure reliable benchmarking. The workflow spans raw data collection, model training, retrieval benchmarking, idiom interpretation, and deployment-ready artifacts.
Beyond these tasks, IdiomX can support chatbots, translation systems, idiom explanation assistants, language learning tools, sarcasm detection, and human-interacting robots.
Why It Matters Language is not just words, it is meaning, context, and sometimes sarcasm. If AI is going to understand humans, it needs to know that “break a leg” is encouragement, not a medical emergency. The project was developed using modern NLP and deep learning tools, integrating transformer models, embedding techniques, and retrieval architectures.
Idiom Interpretation Example
IdiomX helps move AI beyond literal language toward real understanding.
It is a step toward making machines interpret language the way humans actually use it.
Ayman Sharara, a student in DSTI’s MSc in Data Science & AI, developed IdiomX as part of his Deep Learning project, a large-scale multilingual dataset designed to help AI understand idioms, retrieve figurative expressions, and interpret hidden meaning across languages.
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