Yap, Willy and Timothy Baldwin (2009) Experiments on Pattern-based Relation Learning, in Proceedings of the 18th ACM Conference on Information and Knowledge Management (CIKM 2009), Hong Kong, China

Relation extraction is the task of extracting semantic relations— such as synonymy or hypernymy—between word pairs from corpus data. Past work in relation extraction has concentrated on manually creating templates to use in directly extracting word pairs for a given semantic relation from corpus text. Recently, there has been a move towards using machine learning to automatically learn these patterns. We build on this research by running experiments investigating the impact of corpus type, corpus size and different parameter settings on learning a range of lexical relations.