SigmaKB: Integrating Multiple Knowledge Bases

SigmaKB: Integrating Multiple Knowledge Bases

 

There are many knowledge bases that are currently available to the public. Each of these knowledge bases can vary widely in implementation and purpose. The Sigma Knowledge Base, or SigmaKB, aims to unify these other knowledge bases and thus create a powerful query answering system that is more flexible and informative than any single knowledge base. This is achieved via schema mapping and query translation algorithms between each of the component knowledge bases. Scroll down to learn more about the knowledge bases that have been integrated into SigmaKB.

Visit the alpha version of SigmaKB

Video Demo of SigmaKB

If you are experiencing low-quality video, view this video directly on YouTube.

Integrated Knowledge Bases:

Yago
Yago is a knowledge base developed by Max Planck Institute with unusually high confidence values extracted from a number of high-quality sources, including wikipedia and wordnet.

Nell
Nell is a knowledge base developed by CMU that is incrementally extracted via continuous crawling of webpages and aided by parsing techniques such as natural language processing.

Faculty: Daisy Zhe Wang
Students: Mugdha Kumar, Jeremy Baker, A V Shrinivass, Sean Goldberg, Miguel Rodriguez
Collaborators: Milenko Petrovic (IHMC)