Corpus-driven hyponym acquisition refers to the process of automatically identifying and extracting subordinate concepts or categories from a larger set of words or phrases using corpus linguistics techniques. Synonyms for this term include corpus-based hyponymy extraction, data-driven hyponym identification, and text-mining for hypernym-hyponym relationships. This approach is commonly used in natural language processing, information retrieval, and ontology learning applications. The goal is to generate more accurate and comprehensive semantic networks that can be used for various language-related tasks, such as text classification, information extraction, and knowledge representation. Overall, corpus-driven hyponym acquisition is a powerful method for discovering semantic relationships between words and expanding our understanding of language.