Paper: Using LSA And Noun Coordination Information To Improve The Recall And Precision Of Automatic Hyponymy Extraction

ACL ID W03-0415
Title Using LSA And Noun Coordination Information To Improve The Recall And Precision Of Automatic Hyponymy Extraction
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2003
Authors

In this paper we demonstrate methods of im- proving both the recall and the precision of au- tomatic methods for extraction of hyponymy (IS A) relations from free text. By applying la- tent semantic analysis (LSA) to filter extracted hyponymy relations we reduce the rate of er- ror of our initial pattern-based hyponymy ex- traction by 30%, achieving precision of 58%. Applying a graph-based model of noun-noun similarity learned automatically from coordi- nation patterns to previously extracted correct hyponymy relations, we achieve roughly a five- fold increase in the number of correct hy- ponymy relations extracted.