Weighting dictionary entities for language understanding models

A computer-implemented method comprising:

• accessing positive sample entities that belong to an entity class and negative sample entities that do not belong to the entity class;
• identifying clicked URLs from search click logs for at least a portion of the positive sample entities and negative sample entities;
• identifying search result URLs for at least a portion of the positive sample entities and negative sample entities;
• identifying attributes from an entity graph for at least a portion of the positive sample entities and negative sample entities;
• training, using a computing device, a classifier model using the clicked URLs, search result URLs, and attributes from the entity graph as features of the positive sample entities and negative sample entities;
• and
• employing the classifier model to weight entities in a candidate dictionary to provide weightings for the entities from the candidate dictionary.

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.