Paper: Detecting Hedge Cues and their Scopes with Average Perceptron

ACL ID W10-3005
Title Detecting Hedge Cues and their Scopes with Average Perceptron
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2010
Authors

In this paper, we proposed a hedge de- tection method with average perceptron, which was used in the closed challenge in CoNLL-2010 Shared Task. There are two subtasks: (1) detecting uncertain sen- tences and (2) identifying the in-sentence scopes of hedge cues. We use the unified learning algorithm for both subtasks since that the hedge score of sentence can be de- composed into scores of the words, espe- cially the hedge words. On the biomedical corpus, our methods achieved F-measure with 77.86% in detecting in-domain un- certain sentences, 77.44% in recognizing hedge cues, and 19.27% in identifying the scopes.