What You Seek is What You Get: Extraction of Class Attributes from Query Logs

Marius Pasca, Benjamin Van Durme

Within the larger area of automatic acquisition of knowledge from the Web, we introduce a method for extracting relevant attributes, or quantifiable properties, for various classes of objects. The method extracts attributes such as "capital city" and "President" for the class Country, or "cost," "manufacturer" and "side effects" for the class Drug, without relying on any expensive language resources or complex processing tools. In a departure from previous approaches to large-scale information extraction, we explore the role of Web query logs, rather than Web documents, as an alternative source of class attributes. The quality of the extracted attributes recommends query logs as a valuable, albeit little explored, resource for information extraction.