The Application of Combined Linguistic Features in Semantic Relation Extraction
Peide Qian · Zhongwen xinxi xuebao · 2008
Semantic relation extraction is one of the important fields in information extraction research.The present feature vector based approach for semantic relation extraction can hardly be improved simply by mining new features.This paper presents a novel method through combining the diverse basic lexical,syntactic and semantic features to form new combined features.The experiments show that these combined features positively improve the precision and recall of the SVM based relation extraction.The F-score of relation extraction for the 7 major types and 23 subtypes in ACE 2004 corpora achieves 66.6% and 59.50% respectively.