Paper: A Unified Framework for Scope Learning via Simplified Shallow Semantic Parsing

ACL ID D10-1070
Title A Unified Framework for Scope Learning via Simplified Shallow Semantic Parsing
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2010
Authors

This paper approaches the scope learning problem via simplified shallow semantic pars- ing. This is done by regarding the cue as the predicate and mapping its scope into several constituents as the arguments of the cue. Evaluation on the BioScope corpus shows that the structural information plays a critical role in capturing the relationship between a cue and its dominated arguments. It also shows that our parsing approach significantly outper- forms the state-of-the-art chunking ones. Al- though our parsing approach is only evaluated on negation and speculation scope learning here, it is portable to other kinds of scope learning.