Names and Similarities on the Web: Fact Extraction in the Fast Lane

In a new approach to large-scale extraction of facts from unstructured text, distributional similarities become an integral part of both the iterative acquisition of high-coverage contextual extraction patterns, and the validation and ranking of candidate facts. The evaluation measures the quality and coverage of facts extracted from one hundred million Web documents, starting from ten seed facts and using no additional knowledge, lexicons or complex tools.

• Type: Conference
• Year: 2006
• Where: ACL
• Authors: Marius Pasca, Dekang Lin, Jeffrey Bigham, Andrei Lifchits, Alpa Jain
• Keywords: ACL 2006, ACL 2007, Candidate Facts, Contextual Extraction Patterns, Large-scale Extraction