1. A method of searching for and providing information about a natural language query, the method comprising: generating, using a processor, a mashup query language based on at least one query entity included in a natural language query language via a semantic analysis of the natural language query language, the mashup query language having a tree structure in a plurality of levels, each of the plurality of levels being formed by a query entity, wherein the query entity provides a search target for deriving a search result through a knowledge database, wherein said generating the mashup query language extracts the query entity for each level and assigns at least one attribute to the query entity, the attribute including attribute information; determining, using the processor, whether the plurality of levels are linked through the query entity forming the mashup query language of each of the plurality of levels based on the attribute information of the mashup query language assigned to the query entities; searching, using the processor, for physical data in the knowledge database corresponding to the query entity forming the mashup query language of each of the plurality of levels from a knowledge database based on a result of the determining, and deriving main information and at least one piece of entity information corresponding to the natural language query language from the searched data, wherein the main information comprises final result data for the natural language query derived from said searching, and the entity information comprises physical data linked to the query entity for one or more of the plurality of levels that is searched during said searching, the entity information being used to derive the main information; and laying out, using the processor, a search result screen on a display comprising the main information and the at least one piece of entity information on separate regions of the display.
2. The method of claim 1 , wherein the generating of the mashup query language comprises: determining whether at least two query phrases can be derived from the natural language query language via the semantic analysis of the natural language query language; when it is determined that the at least two query phrases can be derived, deriving the at least two query phrases from the natural language query language; and generating the mashup query language having the tree structure based on the at least two query phrases.