Eliminating Incorrect Events from Large‐Scale Event Networks by Trigger Word Clustering and Pruning




Farrokh Mehryary, Suwisa Kaewphan, Kai Hakala, Filip Ginter

Bodenreider Olivier, Oliveira José Luis, Rinaldi Fabio

International symposium on semantic mining in biomedicine

2014

Proceedings of the 6th International Symposium on Semantic Mining in Biomedicine (SMBM 2014)

75

79

DOIhttps://doi.org/10.5167/uzh-98982

http://www.zora.uzh.ch/98982/17/Eliminating Incorrect Events from Large‐Scale Event Networks by Trigger Word Clustering.pdf



In this short paper, we investigate hierarchical

clustering of event triggers in the EVEX large-scale event resource. As the primary application, we utilize the clustering to identify incorrect trigger event words and subsequently eliminate events extracted with these triggers. We evaluate the method on the BioNLP 2011 and 2013 Shared Task test sets and show that the method can further increase the precision and F-score of the winning system of the 2013 BioNLP Shared Task on Event extraction.



Last updated on 2024-26-11 at 23:23