Harnessing LLMs for Educational Content-Driven Italian Crossword Generation
Kamyar Zeinalipour, Achille Fusco, Asya Zanollo, Marco Maggini, Marco, Gori

TL;DR
This paper presents a novel AI-powered tool that generates Italian crossword puzzles from educational texts, using advanced language models and a large dataset to create diverse, contextually relevant clues for enhanced language learning.
Contribution
It introduces a new AI-based crossword generator tailored for Italian educational content, utilizing a comprehensive dataset and multiple clue styles to improve language learning tools.
Findings
Successfully generated diverse Italian crossword puzzles from educational texts.
Demonstrated the effectiveness of multiple clue styles in enhancing engagement.
Provided a scalable approach for AI-driven educational game creation.
Abstract
In this work, we unveil a novel tool for generating Italian crossword puzzles from text, utilizing advanced language models such as GPT-4o, Mistral-7B-Instruct-v0.3, and Llama3-8b-Instruct. Crafted specifically for educational applications, this cutting-edge generator makes use of the comprehensive Italian-Clue-Instruct dataset, which comprises over 30,000 entries including diverse text, solutions, and types of clues. This carefully assembled dataset is designed to facilitate the creation of contextually relevant clues in various styles associated with specific texts and keywords. The study delves into four distinctive styles of crossword clues: those without format constraints, those formed as definite determiner phrases, copular sentences, and bare noun phrases. Each style introduces unique linguistic structures to diversify clue presentation. Given the lack of sophisticated…
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Taxonomy
TopicsNatural Language Processing Techniques · Mathematics, Computing, and Information Processing · Text Readability and Simplification
