  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.
