Colloquium Details
Recent Advances in Open Information Extraction
| Author: | Mausam University of Washington |
|---|---|
| Date: | February 07, 2013 |
| Time: | 15:30 |
| Location: | 220 Deschutes |
Abstract
Open Information Extraction is an attractive paradigm for extracting large amounts of relational facts from natural language text in a domain-independent manner. In this talk I describe our recent progress using this model, including our latest open extractors, ReVerb and OLLIE, which substantially improve on the previous state of the art. I will end with our ongoing work that uses open extractions for various end tasks, including multi-document summarization and unsupervised event extraction.
Biography
Dr. Mausam is a Research Assistant Professor at the Turing Center in the Department of Computer Science at the University of Washington, Seattle. His research interests span various sub-fields of artificial intelligence, including sequential decision making under uncertainty, large scale natural language processing, and AI applications to crowd-sourcing. Mausam obtained a PhD from University of Washington in 2007 and a Bachelor of Technology from IIT Delhi in 2001.