Merge pull request #50191 from sherzyang/main

Update intro.

Author: JamesJBarnett

learn-pr/wwl-data-ai/use-prebuilt-form-recognizer-models/1-introduction.yml

@@ -1,16 +1,16 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.use-prebuilt-form-recognizer-models.introduction
-title: Introduction
-metadata:
-  title: Introduction
-  description: Introduction
-  author: ivorb
-  ms.author: berryivor
-  ms.date: 09/04/2024
-  ms.topic: unit
-  ms.collection:
-    - wwl-ai-copilot
-durationInMinutes: 3
-content: |
-  [!include[](includes/1-introduction.md)]
-
+### YamlMime:ModuleUnit
+uid: learn.wwl.use-prebuilt-form-recognizer-models.introduction
+title: Introduction
+metadata:
+  title: Introduction
+  description: Introduction
+  author: ivorb
+  ms.author: berryivor
+  ms.date: 04/28/2025
+  ms.topic: unit
+  ms.collection:
+    - wwl-ai-copilot
+durationInMinutes: 3
+content: |
+  [!include[](includes/1-introduction.md)]
+

learn-pr/wwl-data-ai/use-prebuilt-form-recognizer-models/2-understand-prebuilt-models.yml

@@ -1,18 +1,18 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.use-prebuilt-form-recognizer-models.understand-prebuilt-models
-title: Understand prebuilt models
-metadata:
-  title: Understand prebuilt models
-  description: Understand prebuilt models
-  author: ivorb
-  ms.author: berryivor
-  ms.date: 09/04/2024
-  ms.topic: unit
-  ms.collection:
-    - wwl-ai-copilot
-  ms.custom: devx-track-python
-  zone_pivot_groups: dev-lang-csharp-python
-durationInMinutes: 3
-content: |
-  [!include[](includes/2-understand-prebuilt-models.md)]
-
+### YamlMime:ModuleUnit
+uid: learn.wwl.use-prebuilt-form-recognizer-models.understand-prebuilt-models
+title: Understand prebuilt models
+metadata:
+  title: Understand prebuilt models
+  description: Understand prebuilt models
+  author: ivorb
+  ms.author: berryivor
+  ms.date: 04/28/2025
+  ms.topic: unit
+  ms.collection:
+    - wwl-ai-copilot
+  ms.custom: devx-track-python
+  zone_pivot_groups: dev-lang-csharp-python
+durationInMinutes: 3
+content: |
+  [!include[](includes/2-understand-prebuilt-models.md)]
+

learn-pr/wwl-data-ai/use-prebuilt-form-recognizer-models/3-use-general-document-read-layout-models.yml

@@ -1,16 +1,16 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.use-prebuilt-form-recognizer-models.use-general-document-read-layout-models
-title: Use the General Document, Read, and Layout models
-metadata:
-  title: Use the General Document, Read, and Layout models
-  description: Use the General Document, Read, and Layout models
-  author: ivorb
-  ms.author: berryivor
-  ms.date: 09/04/2024
-  ms.topic: unit
-  ms.collection:
-    - wwl-ai-copilot
-durationInMinutes: 3
-content: |
-  [!include[](includes/3-use-general-document-read-layout-models.md)]
-
+### YamlMime:ModuleUnit
+uid: learn.wwl.use-prebuilt-form-recognizer-models.use-general-document-read-layout-models
+title: Use the General Document, Read, and Layout models
+metadata:
+  title: Use the General Document, Read, and Layout models
+  description: Use the General Document, Read, and Layout models
+  author: ivorb
+  ms.author: berryivor
+  ms.date: 04/28/2025
+  ms.topic: unit
+  ms.collection:
+    - wwl-ai-copilot
+durationInMinutes: 3
+content: |
+  [!include[](includes/3-use-general-document-read-layout-models.md)]
+

learn-pr/wwl-data-ai/use-prebuilt-form-recognizer-models/4-use-financial-id-tax-models.yml

@@ -1,16 +1,16 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.use-prebuilt-form-recognizer-models.use-financial-id-tax-models
-title: Use financial, ID, and tax models
-metadata:
-  title: Use financial, ID, and tax models
-  description: Use financial, ID, and tax models
-  author: ivorb
-  ms.author: berryivor
-  ms.date: 09/04/2024
-  ms.topic: unit
-  ms.collection:
-    - wwl-ai-copilot
-durationInMinutes: 3
-content: |
-  [!include[](includes/4-use-financial-id-tax-models.md)]
-
+### YamlMime:ModuleUnit
+uid: learn.wwl.use-prebuilt-form-recognizer-models.use-financial-id-tax-models
+title: Use financial, ID, and tax models
+metadata:
+  title: Use financial, ID, and tax models
+  description: Use financial, ID, and tax models
+  author: ivorb
+  ms.author: berryivor
+  ms.date: 04/28/2025
+  ms.topic: unit
+  ms.collection:
+    - wwl-ai-copilot
+durationInMinutes: 3
+content: |
+  [!include[](includes/4-use-financial-id-tax-models.md)]
+

learn-pr/wwl-data-ai/use-prebuilt-form-recognizer-models/5-exercise-analyze-document-use-form-recognizer.yml

@@ -1,18 +1,18 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.use-prebuilt-form-recognizer-models.exercise-analyze-document-use-form-recognizer
-title: Exercise - Analyze a document using Azure AI Document Intelligence
-metadata:
-  title: Exercise - Analyze a document using Azure AI Document Intelligence
-  description: Exercise - Analyze a document using Azure AI Document Intelligence
-  author: ivorb
-  ms.author: berryivor
-  ms.date: 09/04/2024
-  ms.topic: unit
-  ms.collection:
-    - wwl-ai-copilot
-labId: 152395
-labModal: true
-durationInMinutes: 3
-content: |
-  [!include[](includes/5-exercise-analyze-document-use-form-recognizer.md)]
-
+### YamlMime:ModuleUnit
+uid: learn.wwl.use-prebuilt-form-recognizer-models.exercise-analyze-document-use-form-recognizer
+title: Exercise - Analyze a document using Azure AI Document Intelligence
+metadata:
+  title: Exercise - Analyze a document using Azure AI Document Intelligence
+  description: Exercise - Analyze a document using Azure AI Document Intelligence
+  author: ivorb
+  ms.author: berryivor
+  ms.date: 04/28/2025
+  ms.topic: unit
+  ms.collection:
+    - wwl-ai-copilot
+labId: 152395
+labModal: true
+durationInMinutes: 3
+content: |
+  [!include[](includes/5-exercise-analyze-document-use-form-recognizer.md)]
+

learn-pr/wwl-data-ai/use-prebuilt-form-recognizer-models/6-knowledge-check.yml

@@ -1,52 +1,52 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.use-prebuilt-form-recognizer-models.knowledge-check
-title: Module assessment
-metadata:
-  title: Module assessment
-  description: Knowledge check
-  author: ivorb
-  ms.author: berryivor
-  ms.date: 09/04/2024
-  ms.topic: unit
-  ms.collection:
-    - wwl-ai-copilot
-durationInMinutes: 3
-content: |
-  [!include[](includes/6-knowledge-check.md)]
-quiz:
-  title: "Check your knowledge"
-  questions:
-  - content: "You have a large set of documents with varying structures that contain customer name and address information. You want to extract entities for each customer. Which prebuilt model should you use?"
-    choices:
-    - content: "Read model."
-      isCorrect: false
-      explanation: "Incorrect. The read model can extract text and identify languages but doesn't support entity extraction."
-    - content: "General document model."
-      isCorrect: true
-      explanation: "Correct. The general document model is the only one that supports entity extraction."
-    - content: "ID document model."
-      isCorrect: false
-      explanation: "Incorrect. The ID document model extracts information from US drivers' licenses and international passports and doesn't support entities."
-  - content: "You are using the prebuilt layout model to analyze a document with many checkboxes. You want to find out whether each box is checked or empty. What object should you use in the returned JSON code?"
-    choices:
-    - content: "Selection marks."
-      isCorrect: true
-      explanation: "Correct. Selection marks record checkboxes and radio buttons and include whether they're selected or not."
-    - content: "Bounding boxes."
-      isCorrect: false
-      explanation: "Incorrect. Bounding boxes record the size and position of an element in the analyzed document."
-    - content: "Confidence indicators."
-      isCorrect: false
-      explanation: "Incorrect. Confidence indicators show how reliable an extracted value is."
-  - content: "You submit a Word document to the Azure AI Document Intelligence general document model for analysis but you receive an error. The file is A4 size, contains 1 MB of data, and is not password-protected. How should you resolve the error?"
-    choices:
-    - content: "Change from the free tier to the standard tier."
-      isCorrect: false
-      explanation: "Incorrect. The free tier supports documents up to 4 MB in size. This change would not resolve the error."
-    - content: "Submit the document one page at a time."
-      isCorrect: false
-      explanation: "Incorrect. It's possible but not necessary to submit multipage documents one page at a time. This change would not resolve the error."
-    - content: "Convert the document to PDF format."
-      isCorrect: true
-      explanation: "Correct. Word documents are not supported by Azure AI Document Intelligence but PDF documents are supported. Azure AI Document Intelligence is designed to analyze scanned and photographed paper documents, not documents that are already in a digital format so you should consider using another technology to extract the data in Word documents."
-
+### YamlMime:ModuleUnit
+uid: learn.wwl.use-prebuilt-form-recognizer-models.knowledge-check
+title: Module assessment
+metadata:
+  title: Module assessment
+  description: Knowledge check
+  author: ivorb
+  ms.author: berryivor
+  ms.date: 04/28/2025
+  ms.topic: unit
+  ms.collection:
+    - wwl-ai-copilot
+durationInMinutes: 3
+content: |
+  [!include[](includes/6-knowledge-check.md)]
+quiz:
+  title: "Check your knowledge"
+  questions:
+  - content: "You have a large set of documents with varying structures that contain customer name and address information. You want to extract entities for each customer. Which prebuilt model should you use?"
+    choices:
+    - content: "Read model."
+      isCorrect: false
+      explanation: "Incorrect. The read model can extract text and identify languages but doesn't support entity extraction."
+    - content: "General document model."
+      isCorrect: true
+      explanation: "Correct. The general document model is the only one that supports entity extraction."
+    - content: "ID document model."
+      isCorrect: false
+      explanation: "Incorrect. The ID document model extracts information from US drivers' licenses and international passports and doesn't support entities."
+  - content: "You are using the prebuilt layout model to analyze a document with many checkboxes. You want to find out whether each box is checked or empty. What object should you use in the returned JSON code?"
+    choices:
+    - content: "Selection marks."
+      isCorrect: true
+      explanation: "Correct. Selection marks record checkboxes and radio buttons and include whether they're selected or not."
+    - content: "Bounding boxes."
+      isCorrect: false
+      explanation: "Incorrect. Bounding boxes record the size and position of an element in the analyzed document."
+    - content: "Confidence indicators."
+      isCorrect: false
+      explanation: "Incorrect. Confidence indicators show how reliable an extracted value is."
+  - content: "You submit a Word document to the Azure AI Document Intelligence general document model for analysis but you receive an error. The file is A4 size, contains 1 MB of data, and is not password-protected. How should you resolve the error?"
+    choices:
+    - content: "Change from the free tier to the standard tier."
+      isCorrect: false
+      explanation: "Incorrect. The free tier supports documents up to 4 MB in size. This change would not resolve the error."
+    - content: "Submit the document one page at a time."
+      isCorrect: false
+      explanation: "Incorrect. It's possible but not necessary to submit multipage documents one page at a time. This change would not resolve the error."
+    - content: "Convert the document to PDF format."
+      isCorrect: true
+      explanation: "Correct. Word documents are not supported by Azure AI Document Intelligence but PDF documents are supported. Azure AI Document Intelligence is designed to analyze scanned and photographed paper documents, not documents that are already in a digital format so you should consider using another technology to extract the data in Word documents."
+

learn-pr/wwl-data-ai/use-prebuilt-form-recognizer-models/7-summary.yml

@@ -1,16 +1,16 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.use-prebuilt-form-recognizer-models.summary
-title: Summary
-metadata:
-  title: Summary
-  description: Summary
-  author: ivorb
-  ms.author: berryivor
-  ms.date: 09/04/2024
-  ms.topic: unit
-  ms.collection:
-    - wwl-ai-copilot
-durationInMinutes: 3
-content: |
-  [!include[](includes/7-summary.md)]
-
+### YamlMime:ModuleUnit
+uid: learn.wwl.use-prebuilt-form-recognizer-models.summary
+title: Summary
+metadata:
+  title: Summary
+  description: Summary
+  author: ivorb
+  ms.author: berryivor
+  ms.date: 04/28/2025
+  ms.topic: unit
+  ms.collection:
+    - wwl-ai-copilot
+durationInMinutes: 3
+content: |
+  [!include[](includes/7-summary.md)]
+

learn-pr/wwl-data-ai/use-prebuilt-form-recognizer-models/includes/1-introduction.md

@@ -1,6 +1,6 @@
-Many forms and documents that your business handles are common across disparate companies in different sectors. For example, most companies use invoices and receipts. Microsoft Azure AI Document Intelligence includes prebuilt models so you can handle common document types easily.
+Many forms and documents that businesses handle are common across disparate companies in different sectors. For example, most companies use invoices and receipts. Microsoft Azure AI Document Intelligence includes prebuilt models so you can handle common document types easily.
 
-You work for a company that conducts polls for private companies and political parties. Participants submit their responses as paper forms or as online PDFs. You've decided to deploy Azure AI Document Intelligence to streamline data entry and you need to know if you can use the prebuilt models to generate meaningful data from your forms.
+Imagine you conduct polls for private companies and political parties. Participants submit their responses as paper forms or as online PDFs. You've decided to deploy Azure AI Document Intelligence to streamline data entry. You want to know if you can use the prebuilt models to generate meaningful data from your forms.
 
 In this module, you'll learn about the capabilities of the prebuilt models in Azure AI Document Intelligence and how to use them.