16. A computerized system comprising: one or more processors; and a plurality of components that include computer-executable instructions that are executed by the one or more processors, the components including: a model building component that trains a classifier model for an entity class using positive sample entities that belong to the entity class and negative sample entities that do not belong to the entity class, the model building component also using clicked URLs, search result URLs, and attributes from an entity graph as features of the positive sample entities and negative sample entities to train the classifier model; and a weighting component that employs the classifier model to weight entities in a candidate dictionary to provide weightings for the entities from the candidate dictionary.
16. A computerized system comprising: one or more processors; and a plurality of components that include computer-executable instructions that are executed by the one or more processors, the components including: a model building component that trains a classifier model for an entity class using positive sample entities that belong to the entity class and negative sample entities that do not belong to the entity class, the model building component also using clicked URLs, search result URLs, and attributes from an entity graph as features of the positive sample entities and negative sample entities to train the classifier model; and a weighting component that employs the classifier model to weight entities in a candidate dictionary to provide weightings for the entities from the candidate dictionary. 17. The system of claim 16 , wherein the positive sample entities are from a seed list and the negative sample entities are from a background entity list, and wherein the seed list and background entity list are generated based on information from at least one selected from the following: an existing entity graph and training data from a spoken language understanding system.