Abstract: Various methods, apparatuses/systems, and media for end-to-end entity linking are disclosed. The system includes a processor; and a memory operatively connected to the processor via a communication interface, the memory storing computer readable instructions, when executed, causes the processor to: detect all named entity mentions from a plurality of data sources; compute, in response to detecting, entity embeddings in a knowledge graph by implementing context information and a margin-based loss function; validate the entity embeddings; deploy, in response to validating the entity embeddings, a machine learning model to match character and semantic information, respectively; and link, in response to deployment of the wide and deep learning model, the named mentions in text with corresponding entities in the knowledge graph.