Document Type
Conference Proceeding
Publication Date
1-1-2023
Journal / Book Title
Proceedings of the Annual Meeting of the Association for Computational Linguistics
Abstract
Transformers have been shown to work well for the task of English euphemism disambiguation, in which a potentially euphemistic term (PET) is classified as euphemistic or non-euphemistic in a particular context. In this study, we expand on the task in two ways. First, we annotate PETs for vagueness, a linguistic property associated with euphemisms, and find that transformers are generally better at classifying vague PETs, suggesting linguistic differences in the data that impact performance. Second, we present novel euphemism corpora in three different languages: Yoruba, Spanish, and Mandarin Chinese. We perform euphemism disambiguation experiments in each language using multilingual transformer models mBERT and XLM-RoBERTa, establishing preliminary results from which to launch future work.
Journal ISSN / Book ISBN
85175400017 (Scopus)
Montclair State University Digital Commons Citation
Lee, Patrick; Shode, Iyanuoluwa; Trujillo, Alain Chirino; Zhao, Yuan; Ojo, Olumide Ebenezer; Plancarte, Diana Cuevas; Feldman, Anna; and Peng, Jing, "FEED PETs: Further Experimentation and Expansion on the Disambiguation of Potentially Euphemistic Terms" (2023). School of Computing Faculty Scholarship and Creative Works. 44.
https://digitalcommons.montclair.edu/computing-facpubs/44