Review of linguistic rules used for extracting entities of conceptual models from natural language text

Abstract EN

Designing conceptual models from natural language text that describes a problem statement can be difficult for inexperienced database designers.

Thus, many research studies attempted to improve inexperienced designer’s performance in designing conceptual models.

Researchers suggested linguistic rules for extracting entities from natural language text.

However, the rules of linguistic can provide a simple service only when creating a method for obtaining entities from text.

This paper reviewed linguistic rules and defined their limitations.

Furthermore, the paper suggested to integrate linguistic rules and machine learning classifiers for producing enhanced set of linguistic rules that can work more effectively than existing linguistic rules in extracting entities from natural language text.