2025/10/14 by Antonio San Martín, Catherine Trekker · 1 voice
Arts and Humanities · Computer Science · #Lexicography and Language Studies #Natural Language Processing Techniques #linguistics and terminology studies
paper · doi:10.1075/term.25022.san
openalex publication_date 2025/10/14 · openalex created_date 2025/10/15 · openalex updated_date 2026/07/16
Abstract Identifying hyponymy is essential in terminology work. This article addresses the lack of a comprehensive inventory of hyponymic knowledge patterns (KPs) in English by presenting a robust methodology for their collection. Drawing on six complementary strategies — literature review, machine translation, parallel corpora, human translation, bootstrapping, and generative artificial intelligence — the study identified and validated 110 distinct English hyponymic patterns, many of which had not been previously documented. These patterns will serve to update the English version of the EcoLexicon Semantic Sketch Grammar (ESSG-en), a KP-based tool for extracting semantic relations from corpora in Sketch Engine. The findings highlight the strengths and limitations of each strategy and underscore the value of combining methods to achieve coverage. Ultimately, this research fills a significant gap by delivering the most extensive list of English hyponymic patterns to date.