Comparable Entity Mining from Comparative Questions

Comparing one thing with another is a typical part of human decision making process. However, it is not always easy to know what to compare and what are the alternatives. To address this difficulty, we present a novel way to automatically mine comparable entities from comparative questions that users posted online. 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 experimental results show our method achieves F1measure of 82.5% in comparative question identification and 83.3% in comparable entity extraction. Both significantly outperform an existing state-of-the-art method.

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Shasha Li, Chin-Yew Lin, Young-In Song, Zhoujun Li
• Keywords: ACL 2010, Comparable Entity Extraction, Comparative Question, Comparative Question Identification, Computational Linguistics