MIXING KNOWLEDGE SOURCES WITH AUTO LEARNING FOR IMPROVED ENTITY EXTRACTION

The disclosed embodiments of computer systems and techniques utilize an ensemble semantics framework to combine knowledge acquisition systems that yield significantly higher quality resources than each system in isolation. Gains in entity extraction are achieved by combining state-of-the-art distributional and pattern-based systems with a large set of features from, for example, a webcrawl, query logs, and wisdom of the crowd sources. This results in improved query interpretation and greater relevancy in providing search results and advertising, for example.