Comparing one thing with another is a typical part of human decision making process, especially during an online purchase scheme. To assist decision making it is useful to compare entities that share common utility but have distinguishing peripheral features. Without comparing it is not fair to purchase a product, since it would not give an ideal performance. To get rid of this difficulty, my paper presents an ideal way for automatically mine comparable entities from comparative questions that users posted online. It gives an opportunity to improve the search experience by automatically offering comparisons to user. A weekly supervised bootstrapping algorithm is employed here for comparative question identification and comparable entity extraction by collecting a large online question archive. This is done by detecting whether a given question is comparative or not. A sequential pattern is generated and is called an indicative extraction pattern (IEP) if it can be used to identify comparative questions and extract comparator pairs with high reliability. The results will be very useful in helping users’ exploration of alternative choices by suggesting comparable entities based on other users’ prior requests.