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An entity type is what DryvIQ is detecting. The DryvIQ Platform comes with pre-installed entity types that cover a wide range of data, but you also have the option to create custom entity types. Entity types are assigned to a category that identifies the type of data being detected and a match type that identifies how the data is being detected. This page provides a high-level overview to help you understand entity types. To learn more about a specific match type, refer to the Help Center DryvIQ Platform documentation page for that specific match type.
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Categories
Categories identify the type of data being detected. DryvIQ comes with the five default categories listed below. You can also create custom categories if one of the default categories doesn’t capture what your entity type will be identifying. (See Managing Categories for information about creating and managing custom categories.)
Category | Description | ||
|---|---|---|---|
| 1 | FinancialAI Classifier | This category includes entity types that use DryvIQ’s Artificial Intelligence (AI) engine to classify documents. These include
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| 2 | File Details | These entity types leverage file details to classify documents. | |
| 3 | Finance | These entity types are for financial information such as
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| 24 | General | This is a catch-all category for any entity type that doesn’t fall into one of the other four categories. Custom entity types are assigned to this category. | |
| 5 | HR | These entity types identify information commonly found in documents for Human Resources such as
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| 6 | International Drivers License | These entity types use regular expression to identify driver’s license numbers for specific countries. | |
| 7 | Metadata | These entity types leverage file metadata to classify documents. | 3|
| 8 | PII | This entity type can identify personally identifiable information (PII) in a document. | |
| 9 | Privacy | This category is for any entity type pertaining to personally identifiable information (PII). Examples of this type of information include
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| 10 | Regulation | Regulation entity types rely on related keywords to find entity types in different areas such as
The built-in Document Type Classifier and Standardized Form Matcher also fall under this category. | 5identify information that is generally associated with regulatory agencies as
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| 11 | Technology | This category includes entity types related to the technology field such as domain names and IP addresses
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| 12 | US Drivers Licenses | These entity types identify driver’s license numbers for each state in the Unites States of America. |
Match Type
Match type is how the data is being detected. DryvIQ supports four match type methods.
Match Type | Description | ||||
|---|---|---|---|---|---|
| 1 | Regular expression is a pattern used to identify text. It allows you to have very fine-grained control over what content DryvIQ detects. | 2 | A block list allows matching on a given list of terms keywords within a piece of content. | ||
| 32 | This is a custom classification model that is plugged into the system. DryvIQ has four seven pre-installed classification entity types: Classifier, Classifier Module, , andStandardized Form Matcher. | 4 | Transformation | A transformation entity type allows for applying a custom metadata expression against any prior matches to generate new value. This option is available only through the DryvIQ API | |
| 3 | Regular expression is a pattern used to identify text. It allows you to have very fine-grained control over what content DryvIQ detects. |
Related Pages
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