15. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: receiving a query, wherein the query is associated at least in part with a type of entity; generating search results based at least in part on the query; ranking the search results based on relevance to the query; retrieving previously generated data associated with at least one search result of the search results, the previously generated data comprising one or more entity references in the at least one search result corresponding to the type of entity; determining, based on the relevance to the query, a subset of the ranked search results that are above a first predetermined ranking threshold; determining, for each entity reference, a weighted sum of the frequencies of occurrence of the entity reference in each search result in the subset of ranked search results, wherein the weighted sum normalizes the frequency of occurrence of each respective entity reference for each previously generated data; ranking the one or more entity references based on the respective weighted sums; selecting an entity result from the one or more entity references based at least in part on the ranking of the one or more entity references; and providing an answer to the query based at least in part on the entity result.
15. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: receiving a query, wherein the query is associated at least in part with a type of entity; generating search results based at least in part on the query; ranking the search results based on relevance to the query; retrieving previously generated data associated with at least one search result of the search results, the previously generated data comprising one or more entity references in the at least one search result corresponding to the type of entity; determining, based on the relevance to the query, a subset of the ranked search results that are above a first predetermined ranking threshold; determining, for each entity reference, a weighted sum of the frequencies of occurrence of the entity reference in each search result in the subset of ranked search results, wherein the weighted sum normalizes the frequency of occurrence of each respective entity reference for each previously generated data; ranking the one or more entity references based on the respective weighted sums; selecting an entity result from the one or more entity references based at least in part on the ranking of the one or more entity references; and providing an answer to the query based at least in part on the entity result. 18. The computer-readable medium of claim 15 , wherein the operations performed by the one or more processors further comprise: determining that the ranking of the one or more entity references results in a tie; determining, for each ranked search result below the first predetermined ranking threshold and above a second predetermined threshold, a ranking signal for each entity reference; and reranking the one or more entity references based on a new weighted sum of the determined ranking signals associated with each ranked search result below the first predetermined ranking threshold and above the second predetermined threshold; wherein selecting an entity result is based at least in part on the rerank of the one or more entity references.