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Class Entity

Entity Detection

With Entity Detection, you can identify a wide range of entities that are spoken in your audio files, such as person and company names, email addresses, dates, and locations.

To include Entity Detection in your transcript response, add the entity_detection parameter in your POST request when submitting audio files for transcription, and set this parameter to true.

When your transcription is complete, you will see an entities key in the JSON response, as shown on the right. Below, we drill into the data that is returned within the list of results in the entities key.

Entity Types Detected

When Entity Detection is enabled, the entity types listed below are automatically detected and, if found in the transcription text, will be included in the entities key as shown above. They will be listed individually in the order that they appear in the transcript.

Entity Name Description
blood_type Blood type (e.g., O-, AB positive)
credit_card_cvv Credit card verification code (e.g., CVV: 080)
credit_card_expiration Expiration date of a credit card
credit_card_number Credit card number
date Specific calendar date (e.g., December 18)
date_of_birth Date of Birth (e.g., Date of Birth: March 7, 1961)
drug Medications, vitamins, or supplements (e.g., Advil, Acetaminophen, Panadol)
event Name of an event or holiday (e.g., Olympics, Yom Kippur)
email_address Email address (e.g., support@assemblyai.com)
injury Bodily injury (e.g., I broke my arm, I have a sprained wrist)
language Name of a natural language (e.g., Spanish, French)
location Any Location reference including mailing address, postal code, city, state, province, or country
medical_condition Name of a medical condition, disease, syndrome, deficit, or disorder (e.g., chronic fatigue syndrome, arrhythmia, depression)
medical_process Medical process, including treatments, procedures, and tests (e.g., heart surgery, CT scan)
money_amount Name and/or amount of currency (e.g., 15 pesos, $94.50)
nationality Terms indicating nationality, ethnicity, or race (e.g., American, Asian, Caucasian)
occupation Job title or profession (e.g., professor, actors, engineer, CPA)
organization Name of an organization (e.g., CNN, McDonalds, University of Alaska)
person_age Number associated with an age (e.g., 27, 75)
person_name Name of a person (e.g., Bob, Doug Jones)
phone_number Telephone or fax number
political_affiliation Terms referring to a political party, movement, or ideology (e.g., Republican, Liberal)
religion Terms indicating religious affiliation (e.g., Hindu, Catholic)
us_social_security_number Social Security Number or equivalent
drivers_license Driver’s license number (e.g., DL# 356933-540)
banking_information Banking information, including account and routing numbers

Hierarchy

  • Entity

Index

Constructors

Properties

Constructors

constructor

Properties

Optional end

end?: number

Ending timestamp, in milliseconds, of the entity in the transcript.

Optional entity_type

entity_type?: string

The entity type detected.

Optional start

start?: number

Starting timestamp, in milliseconds, of the entity in the transcript.

Optional text

text?: string

The text containing the entity.

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