Bayesian Information Extraction Network

Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs are applicable to probabilistic language modeling. To demonstrate the potential of DBNs for natural language processing, we employ a DBN in an information extraction task. We show how to assemble wealth of emerging linguistic instruments for shallow parsing, syntactic and semantic tagging, morphological decomposition, named entity recognition etc. in order to incrementally build a robust information extraction system. Our method outperforms previously published results on an established benchmark domain. 1 Information Extraction Information extraction (IE) is the task of filling in template information from previously unseen text which belongs to a pre-defined domain. The resulting database is suited for formal queries and filtering. IE systems generally work by detecting patterns in the text that help identi...

• Type: Conference
• Year: 2003
• Where: IJCAI
• Authors: Leonid Peshkin, Avi Pfeffer
• Keywords: Dynamic Bayesian Networks, Ie System, IJCAI 2003, IJCAI 2007, Information Extraction