1. A method comprising: crawling, via an entity extraction computer, a corpus of a plurality of electronic documents; extracting, via the entity extraction computer, a plurality of features from each of the crawled electronic documents in the corpus; aggregating, via a knowledge base aggregator computer, instances of co-occurrence of two or more of the plurality of features across the crawled electronic documents to determine a count of the instances of co-occurrence across the plurality of electronic documents, wherein the count of the instances of co-occurrence of two or more features are determined by adding up number of co-occurrences of the two or more features co-occurred in each of the plurality of electronic documents, wherein the knowledge base aggregator computer includes a main memory hosting a feature co-occurrence in-memory database, wherein the entity extraction computer is distinct from the knowledge base aggregator computer, wherein the feature co-occurrence in-memory database comprises one or more entries of the plurality of features, wherein each entry of the one or more entries contains semantically-related features of the plurality of features, and wherein the co-occurrence is an instance of a feature of the plurality of features identified by an entry of the one or more entries in the corpus of the electronic documents in the co-occurrence database, and wherein the co-occurrence corresponds to determination of related entities upon the occurrence of the two or more of the plurality of features that are related to each other across the crawled electronic documents in no defined order; and adding, via the knowledge base aggregator computer, the instances of the co-occurrence of the two or more features to the feature co-occurrence database based on the count of the instances of co-occurrence across the plurality of electronic documents exceeding a predetermined threshold.