Paper: A Baseline Approach for Detecting Sentences Containing Uncertainty

ACL ID W10-3022
Title A Baseline Approach for Detecting Sentences Containing Uncertainty
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2010
Authors

We apply a baseline approach to the CoNLL-2010 shared task data sets on hedge detection. Weights have been as- signed to cue words marked in the train- ing data based on their occurrences in certain and uncertain sentences. New sentences received scores that correspond with those of their best scoring cue word, if present. The best acceptance scores for uncertain sentences were determined us- ing 10-fold cross validation on the training data. This approach performed reasonably on the shared task’s biological (F=82.0) and Wikipedia (F=62.8) data sets.