revert

Author: jboback

articles/ai-services/language-service/named-entity-recognition/how-to-call.md

@@ -25,7 +25,7 @@ The NER feature can evaluate unstructured text, and extract named entities from
 
 ### Input languages
 
-When you submit input text to be processed, you can specify which of [the supported languages](language-support.md) they're written in. if you don't specify a language, named entity recognition defaults to English. The API may return offsets in the response to support different [multilingual and emoji encodings](../concepts/multilingual-emoji-support.md). 
+When you submit documents to be processed, you can specify which of [the supported languages](language-support.md) they're written in. if you don't specify a language, key phrase extraction defaults to English. The API may return offsets in the response to support different [multilingual and emoji encodings](../concepts/multilingual-emoji-support.md). 
 
 ## Submitting data
 
@@ -41,7 +41,7 @@ When you get results from NER, you can stream the results to an application or s
 
 ## Select which entities to be returned
 
-The API attempts to detect the [defined entity types and tags](concepts/named-entity-categories.md) for a given input text language. The entity types and tags replace the categories and subcategories structure the older models use to define entities for more flexibility. You can also specify which entities are detected and returned, use the optional `includeList` and `excludeList` parameters with the appropriate entity types. The following example would detect only `Location`. You can specify one or more [entity types](concepts/named-entity-categories.md) to be returned. Given the types and tags hierarchy introduced for this version, you have the flexibility to filter on different granularity levels as so:
+The API attempts to detect the [defined entity types and tags](concepts/named-entity-categories.md) for a given document language. The entity types and tags replace the categories and subcategories structure the older models use to define entities for more flexibility. You can also specify which entities are detected and returned, use the optional `includeList` and `excludeList` parameters with the appropriate entity types. The following example would detect only `Location`. You can specify one or more [entity types](concepts/named-entity-categories.md) to be returned. Given the types and tags hierarchy introduced for this version, you have the flexibility to filter on different granularity levels as so:
 
 **Input:**
 

articles/ai-services/language-service/named-entity-recognition/includes/development-options.md

@@ -13,5 +13,5 @@ To use named entity recognition, you submit raw unstructured text for analysis a
 
 |Development option  |Description  |
 |---------|---------|
-|Language studio     | Language Studio is a web-based platform that lets you try named entity recognition with text examples without an Azure account, and your own data when you sign up. For more information, see the [Language Studio website](https://language.cognitive.azure.com/tryout/namedEntities) or [language studio quickstart](../../language-studio.md).         |
+|Language studio     | Language Studio is a web-based platform that lets you try entity linking with text examples without an Azure account, and your own data when you sign up. For more information, see the [Language Studio website](https://language.cognitive.azure.com/tryout/namedEntities) or [language studio quickstart](../../language-studio.md).         |
 |REST API or Client library (Azure SDK)      | Integrate named entity recognition into your applications using the REST API, or the client library available in a variety of languages. For more information, see the [named entity recognition quickstart](../quickstart.md).        |

articles/ai-services/language-service/personally-identifiable-information/how-to-call.md

@@ -30,10 +30,10 @@ By default, this feature uses the latest available AI model on your text. You ca
 
 ### Input languages
 
-When you submit input text to be processed, you can specify which of [the supported languages](language-support.md) they're written in. If you don't specify a language, extraction defaults to English. The API may return offsets in the response to support different [multilingual and emoji encodings](../concepts/multilingual-emoji-support.md). 
+When you submit documents to be processed, you can specify which of [the supported languages](language-support.md) they're written in. If you don't specify a language, extraction defaults to English. The API may return offsets in the response to support different [multilingual and emoji encodings](../concepts/multilingual-emoji-support.md). 
 
 ### Redaction Policy (version 2024-11-5-preview only)
-In version `2024-11-5-preview`, you're able to define the `redactionPolicy` parameter to reflect the redaction policy to be used when redacting text. The policy field supports three policy types:
+In version 2024-11-5-preview, you're able to define the `redactionPolicy` parameter to reflect the redaction policy to be used when redacting text. The policy field supports three policy types:
 
 - `DoNotRedact` 
 - `MaskWithCharacter` (default) 
@@ -55,7 +55,7 @@ Analysis is performed upon receipt of the request. Using the PII detection featu
 
 ## Select which entities to be returned
 
-The API attempts to detect the [defined entity categories](concepts/entity-categories.md) for a given input text language. If you want to specify which entities are detected and returned, use the optional `piiCategories` parameter with the appropriate entity categories. This parameter can also let you detect entities that aren't enabled by default for your input text language. The following example would detect only `Person`. You can specify one or more [entity types](concepts/entity-categories.md) to be returned.
+The API attempts to detect the [defined entity categories](concepts/entity-categories.md) for a given document language. If you want to specify which entities are detected and returned, use the optional `piiCategories` parameter with the appropriate entity categories. This parameter can also let you detect entities that aren't enabled by default for your document language. The following example would detect only `Person`. You can specify one or more [entity types](concepts/entity-categories.md) to be returned.
 
 > [!TIP]
 > If you don't include `default` when specifying entity categories, The API only returns the entity categories you specify.

articles/ai-services/language-service/personally-identifiable-information/includes/development-options.md

@@ -13,5 +13,5 @@ To use PII detection, you submit text for analysis and handle the API output in
 
 |Development option  |Description  |
 |---------|---------|
-|Language studio     | Language Studio is a web-based platform that lets you try personally identifiable information detection with text examples without an Azure account, and your own data when you sign up. For more information, see the [Language Studio website](https://language.cognitive.azure.com/tryout/pii) or [language studio quickstart](../../language-studio.md).         |
+|Azure AI Foundry     | Azure AI Foundry is a web-based platform that lets you use entity linking with text examples with your own data when you sign up. For more information, see the [Azure AI Foundry website](https://ai.azure.com) or [Azure AI Foundry documentation](../../../../ai-studio/what-is-ai-studio.md).         |
 |REST API or Client library (Azure SDK)      | Integrate PII detection into your applications using the REST API, or the client library available in various languages. For more information, see the [PII detection quickstart](../quickstart.md).        |