Abstract: A computer-implemented method for retrieving named entities using semantic similarity is disclosed. A query in natural language is received from a user to identify one or more named entities associated with domain-specific data of a domain. A transformer-based deep neural network decomposes the query into one or more semantic components expressed in natural language. Each component is converted into a query embedding and compared against a semantic index storing embeddings of named entities previously analyzed within the domain. The semantic index represents extracted semantic understandings of entities based on their characteristics from structured and unstructured domain data. Semantic embeddings most similar to the query embeddings are identified, and corresponding named entities are retrieved. A response including ranked matching entities is generated and returned to the user.