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Proficiency-Controlled Text Simplification in European Portuguese: A Preliminary Study using Prompting Approaches

This paper presents a preliminary study on proficiency-controlled text simplification in European Portuguese using multiple prompting strategies. We focus on the iRead4Skills dataset, which defines four complexity levels targeted at adult native speakers with low literacy. Specifically, we simplify 40 texts from the highest complexity level into three easier levels (plain, easy, and very easy), corresponding approximately to Common European Framework of Reference for Languages (CEFR) levels B1, A2, and A1. We evaluate zero-shot and few-shot prompting configurations, exploring the impact of CEFR anchoring, explicit meaning-preservation instructions, and example-based guidance. Automatic evaluation relies on a fine-tuned proficiency classifier and semantic similarity metrics, including BERTScore and document embeddings. The results show that while exact target-level accuracy remains below 40%, target-or-below accuracy reaches up to 61.39%, indicating that the model generally simplifies texts but struggles to consistently match precise proficiency targets. Human evaluation confirms the overall trends observed automatically, while highlighting the subjectivity inherent to proficiency assessment and meaning preservation. Our findings suggest that prompt engineering alone is insufficient for robust proficiency control in European Portuguese, motivating future work on model adaptation and improved evaluation protocols.