name : detect-pii-entities.rst **To detect pii entities in input text** The following ``detect-pii-entities`` example analyzes the input text and identifies entities that contain personally identifiable information (PII). The pre-trained model's confidence score is also output for each prediction. :: aws comprehend detect-pii-entities \ --language-code en \ --text "Hello Zhang Wei, I am John. Your AnyCompany Financial Services, LLC credit card \ account 1111-XXXX-1111-XXXX has a minimum payment of $24.53 that is due by July 31st. Based on your autopay settings, \ we will withdraw your payment on the due date from your bank account number XXXXXX1111 with the routing number XXXXX0000. \ Customer feedback for Sunshine Spa, 123 Main St, Anywhere. Send comments to Alice at AnySpa@example.com." Output:: { "Entities": [ { "Score": 0.9998322129249573, "Type": "NAME", "BeginOffset": 6, "EndOffset": 15 }, { "Score": 0.9998878240585327, "Type": "NAME", "BeginOffset": 22, "EndOffset": 26 }, { "Score": 0.9994089603424072, "Type": "CREDIT_DEBIT_NUMBER", "BeginOffset": 88, "EndOffset": 107 }, { "Score": 0.9999760985374451, "Type": "DATE_TIME", "BeginOffset": 152, "EndOffset": 161 }, { "Score": 0.9999449253082275, "Type": "BANK_ACCOUNT_NUMBER", "BeginOffset": 271, "EndOffset": 281 }, { "Score": 0.9999847412109375, "Type": "BANK_ROUTING", "BeginOffset": 306, "EndOffset": 315 }, { "Score": 0.999925434589386, "Type": "ADDRESS", "BeginOffset": 354, "EndOffset": 365 }, { "Score": 0.9989161491394043, "Type": "NAME", "BeginOffset": 394, "EndOffset": 399 }, { "Score": 0.9994171857833862, "Type": "EMAIL", "BeginOffset": 403, "EndOffset": 418 } ] } For more information, see `Personally Identifiable Information (PII) <https://docs.aws.amazon.com/comprehend/latest/dg/pii.html>`__ in the *Amazon Comprehend Developer Guide*.