Zuora, Inc.
DYNAMICALLY TRAINED MODELS OF NAMED ENTITY RECOGNITION OVER UNSTRUCTURED DATA

Abstract:

A computing server configured to process data of a domain from unstructured data sources to generate natural language phrases describing relationships between entities identified from the unstructured data. The computing server may receive master data schema and domain knowledge ontology of a domain including relationship definitions in the domain. The computing server may identify targeted types of named entities of the domain from the master data schema according to the relationship definitions in the domain knowledge ontology. The computing server may extract a plurality of named entities from unstructured data of the domain. The computing server may generate one or more sequences of named entities and assign entity labels to the named entities. The computing server may, based on the entity labels, generate natural language phrases describing relationships of sets of named entities.