Paper: A Unified Model of Phrasal and Sentential Evidence for Information Extraction

ACL ID D09-1016
Title A Unified Model of Phrasal and Sentential Evidence for Information Extraction
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2009
Authors

Information Extraction (IE) systems that extract role fillers for events typically look at the local context surrounding a phrase when deciding whether to extract it. Of- ten, however, role fillers occur in clauses that are not directly linked to an event word. We present a new model for event extraction that jointly considers both the local context around a phrase along with the wider sentential context in a proba- bilistic framework. Our approach uses a sentential event recognizer and a plausible role-fillerrecognizerthatisconditionedon event sentences. We evaluate our system on two IE data sets and show that our model performs well in comparison to ex- isting IE systems that rely on local phrasal context.