Open Information Extraction

How can a computer accumulate a massive body of knowledge? What will Web search engines look like in ten years?


To address these questions, the Open IE project has been developing a Web-scale information extraction system that reads arbitrary text from any domain on the Web, extracts meaningful information, and stores it in a unified knowledge base for efficient querying. In contrast to traditional information extraction, the Open Information Extraction paradigm attempts to overcome the knowledge acquisition bottleneck by extracting a large number of relations at once.

Demo: TextRunner extracted over 500,000,000 assertions from 100 million Web pages.
Software: ReVerb Open Information Extraction Software and additional information.
Data: Horn-clause inference rules learned by the Sherlock system.
Demo: Selectional Preferences from Web Text compute admissible argument values for a relation.
Data: 10,000 Functional Relations learned from Web Text predict the functionality of a phrase.

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Last changed Sun, 2013-03-10 22:15