@inproceedings{firmino-etal-2026-retrato,
    title = "{R}etrato{\_}{C}antado: Cria{\c{c}}{\~a}o e An{\'a}lise de um Corpus para Representa{\c{c}}{\~o}es de Identidade em Letras de M{\'u}sicas Brasileiras",
    author = "Firmino, Vit{\'o}ria P.  and
      Lopes, Janaina N. de S.  and
      Nogueira, Bruno M.  and
      Reis, Val{\'e}ria Q. dos",
    editor = "Souza, Marlo  and
      de-Dios-Flores, Iria  and
      Santos, Diana  and
      Freitas, Larissa  and
      Souza, Jackson Wilke da Cruz  and
      Ribeiro, Eug{\'e}nio",
    booktitle = "Proceedings of the 17th International Conference on Computational Processing of {P}ortuguese ({PROPOR} 2026) - Vol. 1",
    month = apr,
    year = "2026",
    address = "Salvador, Brazil",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-dnd/2026.propor-1.68/",
    pages = "687--696",
    ISBN = "979-8-89176-387-6",
    abstract = "This paper presents the development of Retrato{\_}Cantado, a dataset of sentences extracted from Brazilian song lyrics and manually annotated to identify and categorize predicative constructions that describe individuals. The corpus findings validate the effectiveness of lexical-syntactic patterns for identifying predicative sentences, confirming their suitability for large-scale linguistic annotation tasks. The dataset also serves as a valuable resource for the analysis of textual discourse and the representation of social groups in Brazilian culture. We additionally trained a person-characterization classifier to illustrate the applicability of the dataset to the automatic detection of predicative descriptions, which achieved high accuracy and highlights the potential for creating more specialized models capable of detecting physical and sociocognitive categories, as well as performing sentiment polarity analysis."
}