Supported Entity Types#

Review the available entity types that NeMo Safe Synthesizer can detect and redact in your data.

NeMo Safe Synthesizer uses machine learning models, regular expressions, and custom patterns to detect personally identifiable information (PII) and sensitive data.

Entity Names#

Use the entity names shown in the tables below when configuring PII detection and replacement for best results, as these are the standardized names used across all configuration files, API calls, and transformations. The system has been fine-tuned on the entity types shown in the table below, although the PII replacement component will attempt to classify any arbitrary entity type specified.

Core Entity Types#

The following entity types are available by default:

Personal Identifiers#

Entity Type	Description	Example Values
`name`	Full person names	“John Smith”, “Maria García”
`first_name`	Given names	“John”, “Maria”, “Alice”
`last_name`	Family names	“Smith”, “García”, “Johnson”

Contact Information#

Entity Type	Description	Example Values
`email`	Email addresses	“john@company.com”, “user@domain.org”
`phone_number`	Phone numbers	“555-123-4567”, “+1-800-555-0199”
`fax_number`	Fax numbers	“555-123-4568”

Address Information#

Entity Type	Description	Example Values
`address`	Complete addresses	“123 Main St, Anytown, CA 90210”
`street_address`	Street addresses	“123 Main St”, “456 Oak Avenue”
`city`	City names	“New York”, “Los Angeles”
`county`	County names	“Harris”, “Maricopa”, “Orange”
`state`	State/province names	“California”, “NY”
`postcode`	Postal/ZIP codes	“90210”, “12345”
`country`	Country names	“United States”, “Canada”

Government Identifiers#

Entity Type	Description	Example Values
`ssn`	Social Security Numbers	“123-45-6789”
`national_id`	National ID numbers	“AB123456C”
`tax_id`	Tax identification numbers	“12-3456789”
`certificate_license_number`	Certificate/license numbers	“LIC123456”, “CERT-789012”

Financial Information#

Entity Type	Description	Example Values
`credit_debit_card`	Payment card numbers	“4111-1111-1111-1111”
`cvv`	Card verification values	“123”, “4567”
`pin`	Personal identification numbers	“1234”, “5678”
`account_number`	Bank account numbers	“1234567890”
`bank_routing_number`	Bank routing numbers	“123456789”
`swift_bic`	SWIFT/BIC codes	“CHASUS33”, “DEUTDEFF”
`iban`	International Bank Account Numbers	“GB29 NWBK 6016 1331 9268 19”

Technical Identifiers#

Entity Type	Description	Example Values
`url`	Web URLs	“https://example.com”
`ipv4`	IPv4 addresses	“192.168.1.1”
`ipv6`	IPv6 addresses	“2001:db8::1”
`mac_address`	Hardware MAC addresses	“00:1B:44:11:3A:B7”
`api_key`	API keys and tokens	“sk_test_123abc…”
`user_name`	Usernames	“jsmith”, “user123”
`password`	Passwords	“MyP@ssw0rd!”, “secret123”
`http_cookie`	HTTP Cookies	“sessionId=abc123”
`device_identifier`	Device IDs	“iPhone12,1”, “SM-G975F”

Vehicle Identifiers#

Entity Type	Description	Example Values
`vehicle_identifier`	VIN numbers	“1HGCM82633A123456”
`license_plate`	License plates	“ABC-1234”, “CA 1ABC123”

Medical Information#

Entity Type	Description	Example Values
`medical_record_number`	Medical record numbers	“MRN123456”, “H123456789”
`health_plan_beneficiary_number`	Insurance IDs	“INS-123456789”, “BCBS-987654321”
`biometric_identifier`	Biometric data references	“FP-123456”, “DNA-SAMPLE-789”

Geographic and Temporal Information#

Entity Type	Description	Example Values
`latitude`	Latitude coordinates	“37.7749”, “40.7128”
`longitude`	Longitude coordinates	“-122.4194”, “-74.0060”
`coordinate`	Coordinate pairs	“(37.7749, -122.4194)”

Other Identifiers#

Entity Type	Description	Example Values
`unique_identifier`	Generic unique IDs	“ID123456”, “UUID-abc-def”
`customer_id`	Customer identifiers	“CUST001”, “C-123456”
`employee_id`	Employee identifiers	“EMP001”, “E-789012”

Quasi-Identifiers#

Quasi-identifiers are attributes that may not directly identify individuals but can be combined with other data for identification:

Entity Type	Description	Example Values
`date`	Date values	“2023-01-15”, “01/15/2023”
`date_time`	Date and time values	“2023-01-15 14:30:00”, “01/15/2023 2:30 PM”
`date_of_birth`	Birth dates	“1985-03-15”, “March 15, 1985”
`time`	Time values	“14:30:00”, “2:30 PM”
`age`	Ages	“18”, “72”
`blood_type`	Blood type information	“A+”, “O-”, “AB+”
`gender`	Gender information	“male”, “female”, “non-binary”
`sexuality`	Sexual orientation	“heterosexual”, “gay”, “lesbian”
`political_view`	Political affiliations	“Democrat”, “Republican”, “Independent”
`race_ethnicity`	Race & ethnicity information	“Asian”, “Caucasian”, “Hispanic”
`religious_belief`	Religious affiliations	“Christian”, “Muslim”, “Jewish”
`language`	Language preferences	“English”, “Spanish”, “Mandarin”
`education_level`	Education level	“Bachelor’s Degree”, “High School”, “PhD”
`occupation`	Professional titles	“Software Engineer”, “Manager”, “Director”
`employment_status`	Employment information	“Full-time”, “Part-time”, “Unemployed”
`company_name`	Organization names	“ACME Corp”, “Tech Solutions Inc”