Carnegie Mellon University

Scone: Symbolic Knowledge Base

Knowledge Representation, Reasoning and Acquisition

By Scott Fahlman

Scone is a high-performance, open-source knowledge-base system intended for use as a component in many software applications. Scone was specifically designed to support natural language understanding and generation, so our emphasis has been on efficiency, scalability and ease of adding new knowledge — not on theorem-proving or solving logic puzzles. At the LTI, Scone has improved the performance of search engines and document classifiers through the use of background knowledge. The system has also been used to extract events and time relations from free-text recipes; to model the belief states and motivations of characters in children's stories; and to extract meaning from very informal, ungrammatical text and speech. Our long-term goal is to use Scone as the foundation for a true natural-language understanding system and develop a flexible system for planning and reasoning about actions.