PII Data Extractor Model

The PII (Personally Identifiable Information) extractor model from DeepLobe is designed to automatically recognize and extract private data from unstructured data sources such as text files or social media feeds. It identifies and extracts sensitive information like names, addresses, phone numbers, email addresses, social security numbers, and more.

How the PII Extractor Model Works

DeepLobe's PII extractor model utilizes Natural Language Processing (NLP) methods to analyze the text input and locate instances of PII. The model is trained on a substantial dataset of annotated text that has been labeled to detect PII instances. Through this training, the model learns to identify patterns and context cues within the text data.

By leveraging algorithms and contextual analysis, the model predicts whether a particular piece of information is likely to be personally identifiable information (PII). This extracted information can be utilized for various purposes, including data analysis, data compliance, and data anonymization.

Testing the PII Data Extraction

To extract PII data using the model, you have two options:

• Upload a PDF or text file containing the data.
• Enter the text directly into the designated text box.

After providing the input, click on the "Run model" button. The model will process the data and generate a list of extracted PII entities. You can review and analyze the results to ensure accuracy and relevance.

API Integration

If you are satisfied with the PII extraction results, you can integrate the model within your existing systems or applications. To integrate, follow these steps:

• Click on the "Sample code" button, which will display a few lines of code.
• Copy and paste the provided code into your application.
• Replace the placeholder "REPLACE_API_KEY" with the API key generated for your account.

For information on generating an API key, refer to the "Create an API Key" section in the documentation.

API Documentation

For more detailed information on using the PII data extractor model via the API, refer to our API documentation. It provides comprehensive guidance and examples to help you leverage the model effectively within your applications.

We hope the PII data extractor model empowers you to efficiently identify and extract sensitive information from unstructured data sources, aiding you in tasks such as data analysis, compliance, and anonymization.