Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Semantic taxonomy induction from heterogenous evidence
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
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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.