---
title: "Bayesian Information Extraction Network"
authors:
  - "Leonid Peshkin"
  - "Avi Pfeffer"
doi: ""
url: "https://ijcai.org/proceedings/2003/63"
pdf: "https://ijcai.org/proceedings/2003/0063.pdf"
venue: "Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence"
year: 2003
pages: "421-425"
track: ""
keywords:
---

# Bayesian Information Extraction Network

Leonid Peshkin, Avi Pfeffer

*Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence*, pages 421-425.

## Abstract

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 ofDBNs 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.