One of the most important issues in Information Retrieval is inferring the intents underlying users' queries. Thus, any tool to enrich or to better contextualized queries can proof extremely valuable. Entity extraction, provided it is done fast, can be one of such tools. Such techniques usually rely on a prior training phase involving large datasets. That training is costly, specially in environments which are increasingly moving towards real time scenarios where latency to retrieve fresh informacion should be minimal. In this paper an `on-the-fly' query decomposition method is proposed. It uses snippets which are mined by means of a na\"ive statistical algorithm. An initial evaluation of such a method is provided, in addition to a discussion on its applicability to different scenarios.