Experiments on pattern-based relation learning
AuthorYap, Willy; Baldwin, Timothy
University of Melbourne Author/sBaldwin, Timothy
AffiliationFaculty of Engineering, Computer Science and Software Engineering
Document TypeWorking Paper
CitationsYap, W. & Baldwin, T. (2009). Experiments on pattern-based relation learning. Melbourne: NICTA Victorian Laboratory, Department of CSSE, The University of Melbourne.
Access StatusOpen Access
© 2009 Willy Yap & Timothy Baldwin
Relation extraction is a sub-task of Information Extraction (IE) that is concerned with extracting semantic relations---such as antonymy, synonymy or hypernymy---between word pairs from corpus data. Past work in relation extraction has concentrated on creating a small set of patterns that are good indicators of whether a word pair contains a semantic relation. In recent years, there has been work on using machine learning to automatically learn these patterns from text. We build on this research in running a series of experiments to investigate the impact of corpus type, corpus size and different parameter settings on learning a range of lexical relations.
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