Domain-specific named entity extraction and mapping

A system, comprising:

• at least one computer comprising at least one processor and at least one memory, the at least one computer configured to:
• receive a text belonging to a particular text domain;
• determine one or more named entities based on the text, the one or more named entities in a named entity taxonomy;
• generating, using a shared encoder, a respective contextual embedding for each named entity of the one or more named entities;
• determine a respective relevance score for each named entity of the one or more named entities using:
• (a) a text domain-specific neural network model specific to the particular text domain to which the text belongs, and (b) the respective contextual embedding generated for the named entity;
• and
• send the respective relevance score determined for a named entity of the one or more named entities to a named entity recommendation system for further processing.

One or more non-transitory computer-readable media comprising computer-executable instructions that, when executed, cause at least one processor to perform actions comprising:

• receiving a text;
• determining a text domain to which the text belongs;
• determining one or more named entities based on the text, the one or more named entities in a named entity taxonomy;
• generating, using a shared encoder, a respective contextual embedding for each named entity of the one or more named entities;
• determining a respective relevance score for each named entity of the one or more named entities using:
• (a) a text domain-specific machine learning model specific to the text domain to which the text belongs, and (b) the respective contextual embedding generated for the named entity;
• and
• providing the respective relevance score determined for a named entity of the one or more named entities to a named entity recommendation system for further processing.