Paper: Comparable Entity Mining from Comparative Questions

ACL ID P10-1067
Title Comparable Entity Mining from Comparative Questions
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010

Comparing one thing with another is a typical part of human decision making process. How- ever, it is not always easy to know what to compare and what are the alternatives. To ad- dress this difficulty, we present a novel way to automatically mine comparable entities from comparative questions that users posted on- line. To ensure high precision and high recall, we develop a weakly-supervised bootstrapping method for comparative question identification and comparable entity extraction by leveraging a large online question archive. The experi- mental results show our method achieves F1- measure of 82.5% in comparative question identification and 83.3% in comparable entity extraction. Both significantly outperform an existing state-of-the-art method.