Paper: Weakly Supervised Learning for Hedge Classification in Scientific Literature

ACL ID P07-1125
Title Weakly Supervised Learning for Hedge Classification in Scientific Literature
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2007
Authors

We investigate automatic classification of speculative language (‘hedging’), in biomedical text using weakly supervised machine learning. Our contributions include a precise description of the task with anno- tation guidelines, analysis and discussion, a probabilistic weakly supervised learning model, and experimental evaluation of the methods presented. We show that hedge classification is feasible using weakly supervised ML, and point toward avenues for future research.