Translating scientific questions expressed in natural language into SPARQL queries that can be executed over knowledge graphs remains a significant challenge in the field of question answering. Recently, several prominent benchmarks, notably SciQA and DBLP-QuAD, have emerged to evaluate performance in this domain. In this paper, we provide a comprehensive analysis of the performance of language models on these benchmarks, assessing various optimization strategies. Our results indicate that the combined use of fine-tuning and prompting techniques, especially when incorporating strategic few-shot selection, produces excellent results on both benchmarks. These findings underscore an urgent need for more challenging benchmarks to better assess model capabilities. We identify key insights, common error patterns, and potential opportunities for transfer learning, and we discuss their implications for optimizing the performance of large language models in knowledge graph-based question answering tasks.
What happens when students in the same country learn markedly different versions of its past? This article examines divergent narratives in French- and English-language history curricula across six Canadian provinces outside Québec. Drawing on a comparative analysis of Grades 7–11 curriculum documents and critical discourse analysis of key expectations and rationales, it identifies persistent asymmetries in how francophone minority histories are represented… or omitted. French-language curricula tend to foreground resistance, community survival, and political agency, whereas English-language curricula frequently marginalise or dilute episodes such as the Conquest (1759), Regulation 17, and the legacy of Louis Riel. These contrasts are not merely lexical; they organise different distributions of agency, responsibility, and visibility, with significant consequences for how students learn to imagine who belongs to the national “we”. To capture this structural imbalance, the article develops the concept of narrative asymmetry in bilingual curriculum ecosystems and argues that such curricular inequity undermines both bilingualism and civic pluralism. The discussion then explores the identity and pedagogical implications of these asymmetries, showing how they shape francophone and anglophone students’ sense of recognition, legitimacy, and historical understanding. The article concludes by outlining avenues toward narrative equity in history education through curriculum reform, teacher education, and historical-thinking pedagogy, and suggests how this framework might be adapted to other multilingual societies grappling with tensions between official narratives and marginalised histories.
O objetivo deste artigo é relatar A experiência de visualização de dados, utilizando Metabase, naSecretaria de Saúde do Estado do Acre, desde as primeiras solicitações até o desenvolvimento de umametodologia própria adequada ao número de membros na equipe de BI da Divisão de SistemasTecnológicos do Departamento de Tecnologia da Informação da Secretaria de Estado de Saúde doAcre – SESACRE. Descrevendo o caso de maior sucesso e reconhecimento por parte dos órgãos decontrole e a sociedade em geral: O Portal Covid-19 Acre, e a sua evolução no ranking do Índice deTransparência da Covid-19 da organização não governamental Open Knowledge Brasil – OKBR, bemcomo a utilização interna por parte da Diretoria Executiva do Fundo Estadual de Saúde na partefinanceira e orçamentária. A metodologia utilizada neste artigo é o relato de experiência.
