To meet the demand of effectively acquiring event information, a method of Web news-oriented event multi-elements retrieval is studied through analyzing characteristics of Web news and event multi-elements retrieval process. Firstly, a model of Web news-oriented event multi-elements retrieval is proposed. Secondly, event multi-elements query terms are formally defined by using the BNF (Backus-Naur form). Finally, incorporating the importance of event action element, Web news title and the distance between event terms and constrained terms, a method of computing the relevance between query terms and the document is proposed. Sixteen event query topics are created to implement the experiments. With the proposed method, this paper evaluates the index P@n based on the Baidu search engine, getting average P@10 of 0.85 and average P@20 of 0.83. This paper also evaluates the index F-measure through manually labeling the corpus with same method, obtaining average F-measure of 0.74. The results show that the proposed method offers more effective performances.