Improving Pun Detection with an Ensemble of Traditional Machine Learning Methods - Leal, Jhúlia de Souza; Inácio, Marcio Lima; Oliveira, Hugo Gonçalo; Anchiêta, Rafael Torres (Anais do Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana (STIL); 2025: Anais do XVI Simpósio Brasileiro de Tecnologia da Informação e da Linguagem HumanaDO - 10.5753/stil.2025.37826, 2025)
Humor is a remarkably complex emotional process, defined as any object or event that causes laughter or amusement or is considered funny. Therefore, recognizing humor is considered one of the most challenging tasks in Natural Language Processing. In this paper, we approached the pun detection task for the Portuguese language. Puns are a form of wordplay that exploits multiple meanings of a term or similar-sounding words to create an intended humorous or rhetorical effect. Our strategy is straightforward: we trained and evaluated an ensemble learning approach of traditional machine learning models on PUNTUGUESE, a recent corpus of Portuguese puns. With this, we outperformed a BERT-based model by 11 p.p. in accuracy and achieved state-of-the-art results. More than that, we performed a detailed error analysis and found that our approach has limitations in identifying puns that contain neologisms.