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.openpublishing.redirection.json

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{
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"redirections": [
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{
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"source_path": "articles/ai-studio/how-to/commitment-tier.md",
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"redirect_url": "/azure/ai-services/commitment-tier.md",
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"redirect_document_id": false
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},
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{
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"source_path": "articles/storage/files/files-samples-dotnet-v11.md",
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"redirect_url": "/previous-versions/azure/storage/files/files-samples-dotnet-v11",
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"source_path_from_root": "/articles/virtual-network/how-to-create-encryption-cli.md",
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"redirect_url": "/azure/virtual-network/how-to-create-encryption",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/virtual-network/tutorial-filter-network-traffic-powershell.md",
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"redirect_url": "/azure/virtual-network/tutorial-filter-network-traffic",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/virtual-network/tutorial-filter-network-traffic-cli.md",
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"redirect_url": "/azure/virtual-network/tutorial-filter-network-traffic",
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"redirect_document_id": false
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}
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]
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}

.openpublishing.redirection.sentinel.json

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{
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"redirections": [
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{
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"source_path": "articles/sentinel/notebooks-troubleshoot.md",
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"redirect_url": "/azure/sentinel/notebooks-hunt",
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"redirect_document_id": true
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},
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{
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"source_path": "articles/sentinel/detect-threats-built-in.md#use-analytics-rule-templates",
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"redirect_url": "/azure/sentinel/create-analytics-rule-from-template",

CODEOWNERS

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/articles/mariadb @tynevi @thomps23
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/articles/mysql @tynevi @thomps23
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/articles/managed-instance-apache-cassandra @tynevi @thomps23
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/articles/virtual-machines @jasonwhowell @thomps23
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/articles/virtual-machines-scale-sets @jasonwhowell @thomps23
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/articles/container-instances @jasonwhowell @thomps23
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/articles/service-fabric @jasonwhowell @thomps23

articles/ai-services/.openpublishing.redirection.ai-services.json

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"redirect_url": "/azure/ai-services/translator/document-translation/reference/rest-api-guide",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/ai-services/openai/how-to/monitoring.md",
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"redirect_url": "/azure/ai-services/openai/how-to/monitor-openai",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/ai-services/openai/how-to/prepare-dataset.md",
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"redirect_url": "/azure/ai-services/openai/concepts/fine-tuning-considerations",

articles/ai-services/computer-vision/how-to/specify-detection-model.md

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The different face detection models are optimized for different tasks. See the following table for an overview of the differences.
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| Model | Description | Performance notes | Attributes | Landmarks |
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|---------|------------|-------------------|-------------|--|
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|**detection_01** | Default choice for all face detection operations. | Not optimized for small, side-view, or blurry faces. | Returns main face attributes (head pose, glasses, and so on) if they're specified in the detect call. | Returns face landmarks if they're specified in the detect call. |
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|**detection_02** | Released in May 2019 and available optionally in all face detection operations. | Improved accuracy on small, side-view, and blurry faces. | Doesn't return face attributes. | Doesn't return face landmarks. |
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|**detection_03** | Released in February 2021 and available optionally in all face detection operations. | Further improved accuracy, including on smaller faces (64x64 pixels) and rotated face orientations. | Returns mask, blur, and head pose attributes if they're specified in the detect call. | Returns face landmarks if they're specified in the detect call. |
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| Model | Description | Performance notes | Landmarks |
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|-------|-------------|-------------------|-----------|
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|**detection_01** | Default choice for all face detection operations. | Not optimized for small, side-view, or blurry faces. | Returns face landmarks if they're specified in the detect call. |
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|**detection_02** | Released in May 2019 and available optionally in all face detection operations. | Improved accuracy on small, side-view, and blurry faces. | Doesn't return face landmarks. |
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|**detection_03** | Released in February 2021 and available optionally in all face detection operations. | Further improved accuracy, including on smaller faces (64x64 pixels) and rotated face orientations. | Returns face landmarks if they're specified in the detect call. |
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Attributes are a set of features that can optionally be detected if they're specified in the detect call:
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| Model | accessories | blur | exposure | glasses | headPose | mask | noise | occlusion | qualityForRecognition |
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|-------|:-----------:|:----:|:--------:|:-------:|:--------:|:----:|:-----:|:---------:|:---------------------:|
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|**detection_01** | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | | ✔️ | ✔️ | ✔️ (for recognition_03 or 04) |
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|**detection_02** | | | | | | | | | |
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|**detection_03** | | ✔️ | ✔️ | ✔️ | ✔️ | ✔️ | | ✔️ | ✔️ (for recognition_03 or 04) |
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The best way to compare the performances of the detection models is to use them on a sample dataset. We recommend calling the [Detect] API on a variety of images, especially images of many faces or of faces that are difficult to see, using each detection model. Pay attention to the number of faces that each model returns.
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articles/ai-services/computer-vision/whats-new.md

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Learn what's new in Azure AI Vision. Check this page to stay up to date with new features, enhancements, fixes, and documentation updates.
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## August 2024
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### New detectable Face attributes
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The glasses, occlusion, blur, and exposure attributes are available with the latest Detection 03 model. See [Specify a face detection model](./how-to/specify-detection-model.md) for more details.
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## May 2024
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### New Face SDK 1.0.0-beta.1 (breaking changes)
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The Face SDK was rewritten in version 1.0.0-beta.1 to better meet the guidelines and design principles of Azure SDKs. C#, Python, Java, and JavaScript are the supported languages. Follow the [QuickStart](./quickstarts-sdk/identity-client-library.md) to get started.
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## February 2024
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#### Multimodal embeddings GA: new multi-language model

articles/ai-services/content-safety/overview.md

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| France Central || | | || ||
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| West Europe |||| || ||
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| Japan East || | | || ||
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| Australia East|| | | ||||
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| Australia East|| | | ||||
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| USGov Arizona || | | | | | |
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| USGov Virginia || | | | | | |
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articles/ai-services/content-safety/quickstart-groundedness.md

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```Python
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import http.client
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import json
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conn = http.client.HTTPSConnection("<endpoint>/contentsafety/text:detectGroundedness?api-version=2024-02-15-preview")
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endpoint = "<your_custom_subdomain>.cognitiveservices.azure.com"
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conn = http.client.HTTPSConnection(endpoint)
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payload = json.dumps({
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"domain": "Generic",
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"task": "QnA",
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"groundingSources": [
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"I'm 21 years old and I need to make a decision about the next two years of my life. Within a week. I currently work for a bank that requires strict sales goals to meet. IF they aren't met three times (three months) you're canned. They pay me 10/hour and it's not unheard of to get a raise in 6ish months. The issue is, **I'm not a salesperson**. That's not my personality. I'm amazing at customer service, I have the most positive customer service \"reports\" done about me in the short time I've worked here. A coworker asked \"do you ask for people to fill these out? you have a ton\". That being said, I have a job opportunity at Chase Bank as a part time teller. What makes this decision so hard is that at my current job, I get 40 hours and Chase could only offer me 20 hours/week. Drive time to my current job is also 21 miles **one way** while Chase is literally 1.8 miles from my house, allowing me to go home for lunch. I do have an apartment and an awesome roommate that I know wont be late on his portion of rent, so paying bills with 20hours a week isn't the issue. It's the spending money and being broke all the time.\n\nI previously worked at Wal-Mart and took home just about 400 dollars every other week. So I know i can survive on this income. I just don't know whether I should go for Chase as I could definitely see myself having a career there. I'm a math major likely going to become an actuary, so Chase could provide excellent opportunities for me **eventually**."
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],
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"reasoning": false
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"reasoning": False
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})
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headers = {
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'Ocp-Apim-Subscription-Key': '<your_subscription_key>',

articles/ai-services/document-intelligence/concept-custom-generative.md

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* **Field Description**. Provide more contextual information in description to help clarify the field that needs to be extracted. Examples include location in the document, potential field labels it can be associated with, and ways to differentiate with other terms that could be ambiguous.
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* **Variation**. Custom generative models can generalize across different document templates of the same document type. As a best practice, create a single model for all variations of a document type. Ideally, include a visual template for each type, especially for ones that
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* **Variation**. Custom generative models can generalize across different document templates of the same document type. As a best practice, create a single model for all variations of a document type. Ideally, include a visual template for each type, especially for ones that involve distinct formatting or structural elements, to improve the model's accuracy and consistency in generating or processing documents.
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## Service guidance
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articles/ai-services/document-intelligence/concept-mortgage-documents.md

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**Supported document types:**
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* Uniform Residential Loan Application (Form 1003)
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* Uniform Residential Appraisal Report (Form 1004)
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* Verification of employment form (Form 1005)
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* Uniform Underwriting and Transmittal Summary (Form 1008)
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* Closing Disclosure form
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| Feature | Resources | Model ID |
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|----------|-------------|-----------|
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|**Mortgage model**|&bullet; [**Document Intelligence Studio**](https://formrecognizer.appliedai.azure.com)</br>&bullet; [**REST API**](/rest/api/aiservices/operation-groups?view=rest-aiservices-v4.0%20(2024-07-31-preview)&preserve-view=true)</br>&bullet; [**C# SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)</br>&bullet; [**Python SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)</br>&bullet; [**Java SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)</br>&bullet; [**JavaScript SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)|**&bullet; prebuilt-mortgage.us.1003</br>&bullet; prebuilt-mortgage.us.1008</br>&bullet; prebuilt-mortgage.us.closingDisclosure**|
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|**Mortgage model**|&bullet; [**Document Intelligence Studio**](https://formrecognizer.appliedai.azure.com)</br>&bullet; [**REST API**](/rest/api/aiservices/operation-groups?view=rest-aiservices-v4.0%20(2024-07-31-preview)&preserve-view=true)</br>&bullet; [**C# SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)</br>&bullet; [**Python SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)</br>&bullet; [**Java SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)</br>&bullet; [**JavaScript SDK**](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-4.0.0&preserve-view=true)|**&bullet; prebuilt-mortgage.us.1003</br>&bullet; prebuilt-mortgage.us.1004</br>&bullet; prebuilt-mortgage.us.1005</br>&bullet; prebuilt-mortgage.us.1008</br>&bullet; prebuilt-mortgage.us.closingDisclosure**|
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::: moniker-end
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## Input requirements
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|`Property.MixedUseProperty`|`selectionGroup`|Is the property a mixed-use property?|:selected: NO:unselected: YES|
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|`Property.ManufacturedHome`|`selectionGroup`|Is the property a manufactured home?|:selected: NO:unselected: YES|
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## [2024-02-29-preview](#tab/2024-02-29-preview)
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### Supported languages and locales
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| Supported Languages | Details |
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|:--------------------|:-------:|
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|English|United States (`en-US`)|
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### Supported document fields
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#### mortgage.us.1003
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| Field | Type | Description | Example |
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|:------|:-----|:------------|:--------|
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|`LenderLoanNumber`|`string`|Lender loan number or universal loan identifier|10Bx939c5543TqA1144M999143X38|
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|`AgencyCaseNumber`|`string`|Agency case number|115894|
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|`Borrower`|`object`|||
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|`Borrower.Name`|`string`|Borrower's full name as written on the form|Gwen Stacy|
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|`Borrower.SocialSecurityNumber`|`string`|Borrower's social security number|557-99-7283|
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|`Borrower.BirthDate`|`date`|Borrower's date of birth|11/07/1989|
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|`Borrower.CitizenshipType`|`selectionGroup`|Borrower's citizenship|:selected: U.S. Citizen<br>:unselected: Permanent Resident Alien<br>:unselected: Non-Permanent Resident Alien|
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|`Borrower.CreditApplicationType`|`selectionGroup`|Borrower's credit type|:selected: I'm applying for individual credit.<br>:unselected: I'm applying for joint credit.|
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|`Borrower.NumberOfBorrowers`|`integer`|Total number of borrowers|1|
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|`Borrower.MaritalStatus`|`selectionGroup`|Borrower's marital status|:selected: Married<br>:unselected: Separated<br>:unselected: Unmarried|
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|`Borrower.NumberOfDependents`|`integer`|Total number of borrower's dependents|2|
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|`Borrower.DependentsAges`|`string`|Age of borrower's dependents|10, 11|
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|`Borrower.HomePhoneNumber`|`phoneNumber`|Borrower's home phone number|(818) 246-8900|
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|`Borrower.CellPhoneNumber`|`phoneNumber`|Borrower's cell phone number|(831) 728-4766|
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|`Borrower.WorkPhoneNumber`|`phoneNumber`|Borrower's work phone number|(987) 213-5674|
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|`Borrower.CurrentAddress`|`address`|Borrower's current address|1634 W Glenoaks Blvd<br>Glendale CA 91201 United States|
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|`Borrower.YearsInCurrentAddress`|`integer`|Years in current address|1|
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|`Borrower.MonthsInCurrentAddress`|`integer`|Months in current address|1|
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|`Borrower.CurrentHousingExpenseType`|`selectionGroup`|Borrower's housing expense type|:unselected: No primary housing expense:selected: Own:unselected: Rent|
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|`Borrower.CurrentMonthlyRent`|`number`|Borrower's monthly rent|1,600.00|
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|`Borrower.SignedDate`|`date`|Borrower's signature date|03/16/2021|
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|`CoBorrower`|`object`|||
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|`CoBorrower.Names`|`string`|Coborrowers' names|Peter Parker<br>Mary Jane Watson|
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|`CoBorrower.SignedDate`|`date`|Coborrower's signature date|03/16/2021|
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|`CurrentEmployment`|`object`|||
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|`CurrentEmployment.DoesNotApply`|`boolean`|Checkbox state of 'Doesn't apply'|:selected:|
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|`CurrentEmployment.EmployerName`|`string`|Borrower's employer or business name|Spider Wb Corp.|
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|`CurrentEmployment.EmployerPhoneNumber`|`phoneNumber`|Borrower's employer phone number|(390) 353-2474|
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|`CurrentEmployment.EmployerAddress`|`address`|Borrower's employer address|3533 Band Ave<br>Glendale CA 92506 United States|
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|`CurrentEmployment.PositionOrTitle`|`string`|Borrower's position or title|Language Teacher|
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|`CurrentEmployment.StartDate`|`date`|Borrower's employment start date|01/08/2020|
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|`CurrentEmployment.GrossMonthlyIncomeTotal`|`number`|Borrower's gross monthly income total|4,254.00|
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|`Loan`|`object`|||
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|`Loan.Amount`|`number`|Loan amount|156,000.00|
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|`Loan.PurposeType`|`selectionGroup`|Loan purpose type|:unselected: Purchase:selected: Refinance:unselected: Other|
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|`Loan.OtherPurpose`|`string`|Other loan purpose type|Construction|
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|`Loan.RefinanceType`|`selectionGroup`|Loan refinance type|:selected: No Cash Out<br>:unselected: Limited Cash Out<br>:unselected: Cash Out|
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|`Loan.RefinanceProgramType`|`selectionGroup`|Loan refinance program type|:unselected: Full Documentation:selected: Interest Rate Reduction<br>:unselected: Streamlined without Appraisal<br>:unselected: Other|
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|`Loan.OtherRefinanceProgram`|`string`|Other loan refinance program type|Cash-out refinance|
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|`Property`|`object`|||
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|`Property.Address`|`address`|Property address|1634 W Glenoaks Blvd<br>Glendale CA 91201 Los Angeles|
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|`Property.NumberOfUnits`|`integer`|Number of units|1|
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|`Property.Value`|`number`|Property value|200,000.00|
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|`Property.OccupancyStatus`|`selectionGroup`|Property occupancy status|:selected: Primary Residence<br>:unselected: Second Home<br>:unselected: Investment Property|
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|`Property.IsFhaSecondaryResidence`|`boolean`|Checkbox state of '`FHA` Secondary Residence'|:unselected:|
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|`Property.MixedUseProperty`|`selectionGroup`|Is the property a mixed-use property?|:selected: NO:unselected: YES|
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|`Property.ManufacturedHome`|`selectionGroup`|Is the property a manufactured home?|:selected: NO:unselected: YES|
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The 1003 URLA key-value pairs and line items extracted are in the `documentResults` section of the JSON output.
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## Field extraction 1004 Uniform Residential Appraisal Report (URAR)
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The following are the fields extracted from a 1004 URAR form in the JSON output response.
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* Try processing your own forms and documents with the [Document Intelligence Studio](https://formrecognizer.appliedai.azure.com/studio).
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* Complete a [Document Intelligence quickstart](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true) and get started creating a document processing app in the development language of your choice.
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