add table links

Author: PatrickFarley

articles/ai-services/openai/concepts/content-filter-personal-information.md

@@ -10,7 +10,7 @@ ms.service: azure-ai-openai
 
 # Personally identifiable information (PII) filter
 
-Personally identifiable information (PII) refers to any information that can be used to identify a particular individual, such as a name, address, phone number, email address, social security number, driver's license number, passport number, or similar information. 
+Personally identifiable information (PII) refers to any information that can be used to identify a particular individual, such as a name, address, phone number, email address, social security number, driver's license number, passport number, or similar information.
 
 PII detection is used to prevent PII from being exposed or shared, protecting users from identity theft, financial fraud, or other types of privacy violations.
 

articles/ai-services/openai/concepts/content-filter.md

@@ -39,16 +39,16 @@ The following table summarizes the risk categories supported by Azure OpenAI's c
 
 |Category|Description|
 |--------|-----------|
-| Hate and Fairness      | Hate and fairness-related harms refer to any content that attacks or uses discriminatory language with reference to a person or Identity group based on certain differentiating attributes of these groups. <br><br>This includes, but is not limited to:<ul><li>Race, ethnicity, nationality</li><li>Gender identity groups and expression</li><li>Sexual orientation</li><li>Religion</li><li>Personal appearance and body size</li><li>Disability status</li><li>Harassment and bullying</li></ul> |
-| Sexual  | Sexual describes language related to anatomical organs and genitals, romantic relationships and sexual acts, acts portrayed in erotic or affectionate terms, including those portrayed as an assault or a forced sexual violent act against one’s will. <br><br> This includes but is not limited to:<ul><li>Vulgar content</li><li>Prostitution</li><li>Nudity and Pornography</li><li>Abuse</li><li>Child exploitation, child abuse, child grooming</li></ul>   |
-| Violence  | Violence describes language related to physical actions intended to hurt, injure, damage, or kill someone or something; describes weapons, guns and related entities. <br><br>This includes, but isn't limited to:  <ul><li>Weapons</li><li>Bullying and intimidation</li><li>Terrorist and violent extremism</li><li>Stalking</li></ul>  |
-| Self-Harm  | Self-harm describes language related to physical actions intended to purposely hurt, injure, damage one’s body or kill oneself. <br><br> This includes, but isn't limited to: <ul><li>Eating Disorders</li><li>Bullying and intimidation</li></ul>  |
-|User Prompt Attacks |User prompt attacks are User Prompts designed to provoke the Generative AI model into exhibiting behaviors it was trained to avoid or to break the rules set in the System Message. Such attacks can vary from intricate roleplay to subtle subversion of the safety objective. |
-|Indirect Attacks |Indirect Attacks, also referred to as Indirect Prompt Attacks or Cross-Domain Prompt Injection Attacks, are a potential vulnerability where third parties place malicious instructions inside of documents that the Generative AI system can access and process. Requires [document embedding and formatting](./content-filter-document-embedding.md). |
-| Groundedness<sup>2</sup> | Groundedness detection flags whether the text responses of large language models (LLMs) are grounded in the source materials provided by the users. Ungrounded material refers to instances where the LLMs produce information that is non-factual or inaccurate from what was present in the source materials. Requires [document embedding and formatting](./content-filter-document-embedding.md). |
-| Protected Material for Text<sup>1</sup> | Protected material text describes known text content (for example, song lyrics, articles, recipes, and selected web content) that can be outputted by large language models.|
-| Protected Material for Code | Protected material code describes source code that matches a set of source code from public repositories, which can be outputted by large language models without proper citation of source repositories.|
-| Personally identifiable information (PII) | Personally identifiable information (PII) refers to any information that can be used to identify a particular individual.PII detection involves analyzing text content in LLM completions and filtering any PII that was returned. |
+| [Hate and Fairness](/azure/ai-services/openai/concepts/content-filter-severity-levels)      | Hate and fairness-related harms refer to any content that attacks or uses discriminatory language with reference to a person or Identity group based on certain differentiating attributes of these groups. <br><br>This includes, but is not limited to:<ul><li>Race, ethnicity, nationality</li><li>Gender identity groups and expression</li><li>Sexual orientation</li><li>Religion</li><li>Personal appearance and body size</li><li>Disability status</li><li>Harassment and bullying</li></ul> |
+| [Sexual](/azure/ai-services/openai/concepts/content-filter-severity-levels)  | Sexual describes language related to anatomical organs and genitals, romantic relationships and sexual acts, acts portrayed in erotic or affectionate terms, including those portrayed as an assault or a forced sexual violent act against one’s will. <br><br> This includes but is not limited to:<ul><li>Vulgar content</li><li>Prostitution</li><li>Nudity and Pornography</li><li>Abuse</li><li>Child exploitation, child abuse, child grooming</li></ul>   |
+| [Violence](/azure/ai-services/openai/concepts/content-filter-severity-levels)  | Violence describes language related to physical actions intended to hurt, injure, damage, or kill someone or something; describes weapons, guns and related entities. <br><br>This includes, but isn't limited to:  <ul><li>Weapons</li><li>Bullying and intimidation</li><li>Terrorist and violent extremism</li><li>Stalking</li></ul>  |
+| [Self-Harm](/azure/ai-services/openai/concepts/content-filter-severity-levels)  | Self-harm describes language related to physical actions intended to purposely hurt, injure, damage one’s body or kill oneself. <br><br> This includes, but isn't limited to: <ul><li>Eating Disorders</li><li>Bullying and intimidation</li></ul>  |
+|[User Prompt Attacks](/azure/ai-services/openai/concepts/content-filter-prompt-shields) |User prompt attacks are User Prompts designed to provoke the Generative AI model into exhibiting behaviors it was trained to avoid or to break the rules set in the System Message. Such attacks can vary from intricate roleplay to subtle subversion of the safety objective. |
+|[Indirect Attacks](/azure/ai-services/openai/concepts/content-filter-prompt-shields) |Indirect Attacks, also referred to as Indirect Prompt Attacks or Cross-Domain Prompt Injection Attacks, are a potential vulnerability where third parties place malicious instructions inside of documents that the Generative AI system can access and process. Requires [document embedding and formatting](./content-filter-document-embedding.md). |
+| [Groundedness](/azure/ai-services/openai/concepts/content-filter-groundedness)<sup>2</sup> | Groundedness detection flags whether the text responses of large language models (LLMs) are grounded in the source materials provided by the users. Ungrounded material refers to instances where the LLMs produce information that is non-factual or inaccurate from what was present in the source materials. Requires [document embedding and formatting](./content-filter-document-embedding.md). |
+| [Protected Material for Text](/azure/ai-services/openai/concepts/content-filter-protected-material)<sup>1</sup> | Protected material text describes known text content (for example, song lyrics, articles, recipes, and selected web content) that can be outputted by large language models.|
+| [Protected Material for Code](/azure/ai-services/openai/concepts/content-filter-protected-material) | Protected material code describes source code that matches a set of source code from public repositories, which can be outputted by large language models without proper citation of source repositories.|
+| [Personally identifiable information (PII)](/azure/ai-services/openai/concepts/content-filter-personal-information) | Personally identifiable information (PII) refers to any information that can be used to identify a particular individual.PII detection involves analyzing text content in LLM completions and filtering any PII that was returned. |
 
 <sup>1</sup> If you're an owner of text material and want to submit text content for protection, [file a request](https://aka.ms/protectedmaterialsform).