This research was done with Marius Pasca, while an intern at Google. Papers on this and related work will appear at this year's ACL and AAAI.
If there is time, I will follow with an overview of current work showing that so-called "old school" methods of extraction based on traditional NLP are competitive with state of the art systems recently developed within the community (where competing systems are built using shallow methods, giving results not useable for symbolic inference). In addition, we've we shown that our system, KNEXT, can produce the same sorts of "class attributes" that have thus far been best acquired through the use of commercial search engine query logs, a propriety resource currently unavailable to the research community.
This later research was done with Lenhart Schubert, and Ting Qian, with assistance in result evaluation provided by Daphne Liu and Matt Post.