Review fixes

Author: jboback

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

@@ -13,7 +13,7 @@ ms.custom: language-service-ner, ignite-fall-2021
 ---
 
 
-# How to use Named Entity Recognition(NER)
+# How to use Named Entity Recognition (NER)
 
 The NER feature can evaluate unstructured text, and extract named entities from text in several predefined categories, for example: person, location, event, product, and organization.  
 
@@ -87,7 +87,7 @@ The above examples would return entities falling under the `Location` entity typ
 
 ```
 
-This method returns all `Location` entities only falling under the `GPE` tag and ignore any other entity falling under the `Location` type that is tagged with any other entity tag such as `Structural` or `Geological` tagged `Location` entities. We could also further drill-down on our results by using the `excludeList` parameter. `GPE` tagged entities could be tagged with the following tags: `City`, `State`, `CountryRegion`, `Continent`. We could, for example, exclude `Continent` and `CountryRegion` tags for our example:
+This method returns all `Location` entities only falling under the `GPE` tag and ignore any other entity falling under the `Location` type that is tagged with any other entity tag such as `Structural` or `Geological` tagged `Location` entities. We could also further drill down on our results by using the `excludeList` parameter. `GPE` tagged entities could be tagged with the following tags: `City`, `State`, `CountryRegion`, `Continent`. We could, for example, exclude `Continent` and `CountryRegion` tags for our example:
 
 ```bash
 

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

@@ -50,7 +50,7 @@ CPU core and memory correspond to the `--cpus` and `--memory` settings, which ar
 
 The Named Entity Recognition container image can be found on the `mcr.microsoft.com` container registry syndicate. It resides within the `azure-cognitive-services/textanalytics/` repository and is named `ner`. The fully qualified container image name is, `mcr.microsoft.com/azure-cognitive-services/textanalytics/ner`
 
- To use the latest version of the container, you can use the `latest` tag, which is for english. You can also find a full list of containers for supported languages using the [tags on the MCR](https://mcr.microsoft.com/product/azure-cognitive-services/textanalytics/ner/tags).
+ To use the latest version of the container, you can use the `latest` tag, which is for English. You can also find a full list of containers for supported languages using the [tags on the MCR](https://mcr.microsoft.com/product/azure-cognitive-services/textanalytics/ner/tags).
 
 The latest Named Entity Recognition container is available in several languages. To download the container for the English container, use the command below. 
 
@@ -104,7 +104,7 @@ Use the host, `http://localhost:5000`, for container APIs.
 
 [!INCLUDE [Container's API documentation](../../../../../includes/cognitive-services-containers-api-documentation.md)]
 
-For information on how to call NER see [our guide](../how-to-call.md)
+For information on how to call NER see [our guide](../how-to-call.md).
 
 ## Run the container disconnected from the internet
 

articles/ai-services/language-service/summarization/how-to/conversation-summarization.md

@@ -175,8 +175,8 @@ curl -i -X POST https://<your-language-resource-endpoint>/language/analyze-conve
 ```
 
 2. Make the following changes in the command where needed:
-- Replace the value `your-value-language-key` with your key.
-- Replace the first part of the request URL `your-language-resource-endpoint` with your endpoint URL.
+    - Replace the value `your-value-language-key` with your key.
+    - Replace the first part of the request URL `your-language-resource-endpoint` with your endpoint URL.
 
 3. Open a command prompt window (for example: BASH).
 
@@ -361,8 +361,8 @@ curl -i -X POST https://<your-language-resource-endpoint>/language/analyze-conve
 ```
 
 2. Make the following changes in the command where needed:
-- Replace the value `your-language-resource-key` with your key.
-- Replace the first part of the request URL `your-language-resource-endpoint` with your endpoint URL.
+    - Replace the value `your-language-resource-key` with your key.
+    - Replace the first part of the request URL `your-language-resource-endpoint` with your endpoint URL.
 
 3. Open a command prompt window (for example: BASH).
 
@@ -521,8 +521,8 @@ curl -i -X POST https://<your-language-resource-endpoint>/language/analyze-conve
 ```
 
 2. Make the following changes in the command where needed:
-- Replace the value `your-language-resource-key` with your key.
-- Replace the first part of the request URL `your-language-resource-endpoint` with your endpoint URL.
+    - Replace the value `your-language-resource-key` with your key.
+    - Replace the first part of the request URL `your-language-resource-endpoint` with your endpoint URL.
 
 3. Open a command prompt window (for example: BASH).
 

articles/ai-services/language-service/summarization/how-to/document-summarization.md

@@ -125,8 +125,8 @@ curl -i -X POST https://<your-language-resource-endpoint>/language/analyze-text/
 If you don't specify `sentenceCount`, the model determines the summary length. Note that `sentenceCount` is the approximation of the sentence count of the output summary, range 1 to 20.
 
 2. Make the following changes in the command where needed:
-- Replace the value `your-language-resource-key` with your key.
-- Replace the first part of the request URL `your-language-resource-endpoint` with your endpoint URL.
+    - Replace the value `your-language-resource-key` with your key.
+    - Replace the first part of the request URL `your-language-resource-endpoint` with your endpoint URL.
 
 3. Open a command prompt window (for example: BASH).
 
@@ -279,8 +279,8 @@ curl -i -X POST https://<your-language-resource-endpoint>/language/analyze-text/
 ### Using the summaryParameter
 For the `summaryLength` parameter, three values are accepted:
 * short: Generates a summary of mostly 2-3 sentences, with around 120 tokens.
-* medium : Generates a summary of mostly 4-6 sentences, with around 170 tokens.
-* long : Generates a summary of mostly over 7 sentences, with around 210 tokens.
+* medium: Generates a summary of mostly 4-6 sentences, with around 170 tokens.
+* long: Generates a summary of mostly over 7 sentences, with around 210 tokens.
 
 ## Service and data limits
 

articles/ai-services/language-service/summarization/overview.md

@@ -1,5 +1,5 @@
 ---
-title: What is document and conversation summarization (preview)?
+title: What is document and conversation summarization?
 titleSuffix: Azure AI services
 description: Learn about summarizing text.
 services: cognitive-services