Paper: Constructing Information Networks Using One Single Model

ACL ID D14-1198
Title Constructing Information Networks Using One Single Model
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

In this paper, we propose a new frame- work that unifies the output of three infor- mation extraction (IE) tasks - entity men- tions, relations and events as an informa- tion network representation, and extracts all of them using one single joint model based on structured prediction. This novel formulation allows different parts of the information network fully interact with each other. For example, many rela- tions can now be considered as the re- sultant states of events. Our approach achieves substantial improvements over traditional pipelined approaches, and sig- nificantly advances state-of-the-art end-to- end event argument extraction.