You are building a Language Understanding model for an e-commerce platform. You need to construct an entity to capture billing addresses.
Which entity type should you use for the billing address?
A . machine learned
B . Regex
C . geographyV2
D . Pattern.any
E . list
A regular expression entity extracts an entity based on a regular expression pattern you provide. It ignores case and ignores cultural variant. Regular expression is best for structured text or a predefined sequence of alphanumeric values that are expected in a certain format.
C: The prebuilt geographyV2 entity detects places. Because this entity is already trained, you do not need to add example utterances containing GeographyV2 to the application intents. GeographyV2 entity is supported in English culture.
The geographical locations have subtypes:
D: Pattern.any is a variable-length placeholder used only in a pattern’s template utterance to mark where the entity begins and ends.
E: A list entity represents a fixed, closed set of related words along with their synonyms. You can use list entities to recognize multiple synonyms or variations and extract a normalized output for them. Use the recommend option to see suggestions for new words based on the current list.