Traditional Chinese text retrieval systems return a ranked list of documents in response to a user?s request. While a ranked list of documents can be an appropriate response for the user, frequently it is not. Usually it would be better for the system to provide the answer itself instead of requiring the user to search for the answer in a set of documents. Since Chinese text retrieval has just been developed lately, and due to various specific characteristics of Chinese language, the approaches of its retrieval are quite different from those studies and researches proposed to deal with Western language. Thus, we have developed an architecture that augments existing search engines so that they support Chinese natural language question answering. In this paper we describe a new approach to build Chinese question answering system. Which we believe to be the first general-purpose, fully-automated Chinese question-answering system available on the web. Our system performs quite well given the simplicity of the techniques being utilized. Experimental results show that question answering accuracy can be greatly improved by analyzing more and more matching ERE relation data lists. Simple ERE relation data extraction techniques work well in our system making it efficient to use with many backend retrieval engines.