| Category | Microsoft Docs article | Related commit history on GitHub | Change details |
|---|---|---|---|
| admin | Feedback User Control | https://github.com/MicrosoftDocs/microsoft-365-docs/commits/public/microsoft-365/admin/misc/feedback-user-control.md | If you've enabled the corresponding policies, we may allow users to submit scree - Screenshots: Captures of the userΓÇÖs screen at the time they submitted feedback. Example: the screen including the dialog box from which the user is submitting feedback. - Attachments: Files the user can choose to attach to their feedback. Example: the file they were working on when they encountered a problem. - Content samples: Portions of content from the customerΓÇÖs document or interactions with Microsoft services. Example: the prompt the user sent to an AI service and the response the user received back from that AI service.-- Log files: Additional log files that aren't included in Overview of diagnostic log files for Office - Microsoft Support and that may include the userΓÇÖs name or contents of the userΓÇÖs files. Examples: logs that include the element of the customerΓÇÖs file that is preventing the file from saving.+- Log files: Additional log files that aren't included in [diagnostic log files for Office](https://support.microsoft.com/office/fba86aac-70dc-4858-ae1f-ec2034346cdf) and that may include the userΓÇÖs name or contents of the userΓÇÖs files. Examples: logs that include the element of the customerΓÇÖs file that is preventing the file from saving. > [!NOTE]-> For information about what feedback data is collected about Microsoft Copilot with Microsoft 365 apps, see [Providing feedback about Microsoft Copilot with Microsoft 365 apps](https://support.microsoft.com/topic/c481c26a-e01a-4be3-bdd0-aee0b0b2a423). +> - For information about what feedback data is collected about Microsoft Copilot with Microsoft 365 apps, see [Providing feedback about Microsoft Copilot with Microsoft 365 apps](https://support.microsoft.com/topic/c481c26a-e01a-4be3-bdd0-aee0b0b2a423). +> - For information about log files for Microsoft Teams, see [Configure log files for monitoring and troubleshooting in Teams](/microsoftteams/log-files). ## How can I see my user's feedback? |
| syntex | Prebuilt Model Sensitive Info | https://github.com/MicrosoftDocs/microsoft-365-docs/commits/public/microsoft-365/syntex/prebuilt-model-sensitive-info.md | description: Learn how to use a prebuilt sensitive information model in Microsof # Use a prebuilt model to detect sensitive information from documents in Microsoft Syntex -The prebuilt *sensitive information model* analyzes and detects key information from documents. The model recognizes documents in various formats and [detects sensitive information](/azure/ai-services/language-service/personally-identifiable-information/concepts/entity-categories#entity-categories), such as personal identification numbers, personal physical and email addresses, phone numbers, and personal financial or health information. This model can also extract key sensitive information when selected. +The prebuilt *sensitive information model* analyzes and detects key information from documents, and then optionally extracts the information. The model recognizes documents in various formats and [detects sensitive information](/azure/ai-services/language-service/personally-identifiable-information/concepts/entity-categories), such as personal identification numbers, personal physical and email addresses, phone numbers, and personal financial or health information. ## Set up a sensitive information model To create and configure a sensitive information model, follow these steps: 1. Follow the instructions in [Create a model in Syntex](create-syntex-model.md#set-up-a-prebuilt-model) to create a prebuilt sensitive information model. Then continue with the following steps to complete your model. > [!NOTE]- > You do not need to associate a content type for this prebuilt model. + > When you create a sensitive information model, you will notice that, unlike other models, you don't have the options to select a content type or to apply sensitivity or retention labels. If you need to associate a content type, you'll need to create a different model type. The ability to apply security labels will be provided in future releases. 2. On the **Models** page, in the **Add entities to detect** section, select **Add entities**. To create and configure a sensitive information model, follow these steps: - Select the language you want to use for this model. Only one language can be selected for each model. This model supports languages for both [handwritten text](/azure/ai-services/computer-vision/language-support#handwritten-text) and [print text](/azure/ai-services/computer-vision/language-support#print-text). - - Select the sensitive information entities you want to detect, and then select **Next**. + - From the list of supported entities, select the sensitive information entity or entities you want to detect, and then select **Next**.  -4. On the **Configure extraction** page, select the sensitive information entities you want to extract, and then select **Next**. +4. On the **Configure extraction** page, you see the list of sensitive information entities you chose to detect. Select the entities you want to extract into columns, and then select **Next**.  -5. On the **Test model** page, select **+Add files** to select sample files to test your model. +5. On the **Test model** page, you test the model to make sure it detects and extracts the entities you want. Select **+Add files** to select sample files to test your model.  > [!NOTE] > This model does not detect or extract information from encrypted files. -6. On the **Apply model** page, select **+Add library**, and choose the library you want to add this model to, and then select **Add**. +6. On the **Apply model** page, select **+Add library**, and choose the library you want to apply this model to, and then select **Add**.  -7. In the document library, entities that are detected are displayed in one column and entities that are selected for extraction are displayed in another column per entity. +7. In the document library, entities that are detected are displayed in the **Entities detected** column, and entities that are selected for extraction are displayed in their respective columns.  |