ALBA: A European Portuguese Benchmark for Evaluating Language and Linguistic Dimensions in Generative LLMs

Inês Vieira; Inês Calvo; Iago Paulo; James Furtado; Rafael Ferreira; Diogo Tavares; Diogo Glória-Silva; David Semedo; João Magalhães

arXiv · 2603.26516

ALBA: A European Portuguese Benchmark for Evaluating Language and Linguistic Dimensions in Generative LLMs

Inês Vieira·Inês Calvo·Iago Paulo·James Furtado·Rafael Ferreira·Diogo Tavares·Diogo Glória-Silva·David Semedo·João Magalhães

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Abstract

As Large Language Models (LLMs) expand across multilingual domains, evaluating their performance in under-represented languages becomes increasingly important. European Portuguese (pt-PT) is particularly affected, as existing training data and benchmarks are mainly in Brazilian Portuguese (pt-BR). To address this, we introduce ALBA, a linguistically grounded benchmark designed from the ground up to assess LLM proficiency in linguistic-related tasks in pt-PT across eight linguistic dimensions, including Language Variety, Culture-bound Semantics, Discourse Analysis, Word Plays, Syntax, Morphology, Lexicology, and Phonetics and Phonology. ALBA is manually constructed by language experts and paired with an LLM-as-a-judge framework for scalable evaluation of pt-PT generated language. Experiments on a diverse set of models reveal performance variability across linguistic dimensions, highlighting the need for comprehensive, variety-sensitive benchmarks that support further development of tools in pt-PT.

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Inês Vieira, Inês Calvo, Iago Paulo, James Furtado, Rafael Ferreira, Diogo Tavares, Diogo Glória-Silva, David Semedo, João Magalhães. 2026-03-27. ALBA: A European Portuguese Benchmark for Evaluating Language and Linguistic Dimensions in Generative LLMs. https://arxiv.org/abs/2603.26516

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