Merge pull request #76192 from jborsecnik/text-an

Edit pass: Using C#

Author: ShawnJackson

articles/cognitive-services/text-analytics/quickstarts/csharp.md

@@ -1,7 +1,7 @@
 ---
-title: 'Quickstart: Using C# to call the Text Analytics API'
+title: 'Quickstart: Call the Text Analytics service by using the Azure SDK for .NET and C#'
 titleSuffix: Azure Cognitive Services
-description: Get information and code samples to help you quickly get started with using the Text Analytics API.
+description: Information and code samples to help you start using the Text Analytics service and C#.
 services: cognitive-services
 author: raymondl
 manager: nitinme
@@ -13,35 +13,38 @@ ms.date: 04/29/2019
 ms.author: assafi
 ---
 
-# Quickstart: Using C# to call the Text Analytics Cognitive Service
+# Quickstart: Use the .NET SDK and C# to call the Text Analytics service
 <a name="HOLTop"></a>
 
-Use this quickstart to begin analyzing language with the Text Analytics SDK for C#. While the [Text Analytics](//go.microsoft.com/fwlink/?LinkID=759711) REST API is compatible with most programming languages, the SDK provides an easy way to integrate the service into your applications. The source code for this sample can be found on [GitHub](https://github.com/Azure-Samples/cognitive-services-dotnet-sdk-samples/tree/master/samples/TextAnalytics).
+This quickstart helps you begin using the Azure SDK for .NET and C# to analyze language. Although the [Text Analytics](//go.microsoft.com/fwlink/?LinkID=759711) REST API is compatible with most programming languages, the SDK provides an easy way to integrate the service into your applications.
 
-Refer to the [API definitions](https://westus.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v2-1/operations/56f30ceeeda5650db055a3c7) for technical documentation for the APIs.
+> [!NOTE]
+> The source code for this sample is available on [GitHub](https://github.com/Azure-Samples/cognitive-services-dotnet-sdk-samples/tree/master/samples/TextAnalytics).
+
+For technical details, refer to the SDK for .NET [Text Analytics reference](https://docs.microsoft.com/dotnet/api/overview/azure/cognitiveservices/client/textanalytics?view=azure-dotnet).
 
 ## Prerequisites
 
 [!INCLUDE [cognitive-services-text-analytics-signup-requirements](../../../../includes/cognitive-services-text-analytics-signup-requirements.md)]
 
-You must also have the [endpoint and access key](../How-tos/text-analytics-how-to-access-key.md) that was generated for you during sign-up.
+You also need the [endpoint and access key](../How-tos/text-analytics-how-to-access-key.md) that was generated for you during sign-up.
 
 > [!Tip]
->  While you could call the [HTTP endpoints](https://westus.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v2-1/operations/56f30ceeeda5650db055a3c9) directly from C#, the Microsoft.Azure.CognitiveServices.Language SDK makes it much easier to call the service without having to worry about serializing and deserializing JSON.
+>  While you can call the [HTTP endpoints](https://westus.dev.cognitive.microsoft.com/docs/services/TextAnalytics-v2-1/operations/56f30ceeeda5650db055a3c9) directly from C#, the Microsoft.Azure.CognitiveServices.Language SDK makes it much easier to call the service without having to serialize and deserialize JSON.
 >
 > A few useful links:
-> - [SDK Nuget page](https://www.nuget.org/packages/Microsoft.Azure.CognitiveServices.Language.TextAnalytics)
+> - [SDK NuGet page](https://www.nuget.org/packages/Microsoft.Azure.CognitiveServices.Language.TextAnalytics)
 > - [SDK code](https://github.com/Azure/azure-sdk-for-net/tree/master/src/SDKs/CognitiveServices/dataPlane/Language/TextAnalytics)
 
 ## Create the Visual Studio solution and install the SDK
 
-1. Create a new Console App (.NET Core) project [Visual Studio](https://visualstudio.microsoft.com/vs/).
-1. Right click on the solution and click **Manage NuGet Packages for Solution**
-1. Select the **Browse** tab, and Search for **Microsoft.Azure.CognitiveServices.Language.TextAnalytics**
+1. Create a new console app (.NET Core) project. [Access Visual Studio](https://visualstudio.microsoft.com/vs/).
+1. Right-click the solution and select **Manage NuGet Packages for Solution**.
+1. Select the **Browse** tab. Search for **Microsoft.Azure.CognitiveServices.Language.TextAnalytics**.
 
 ## Authenticate your credentials
 
-1. Add the following `using` statements to the main class file (`Program.cs` by default).
+1. Add the following `using` statements to the main class file (which is Program.cs by default).
 
     ```csharp
     using System;
@@ -59,7 +62,7 @@ You must also have the [endpoint and access key](../How-tos/text-analytics-how-t
 
     ```csharp
     /// <summary>
-    /// Allows authentication to the API using a basic apiKey mechanism
+    /// Allows authentication to the API by using a basic apiKey mechanism
     /// </summary>
     class ApiKeyServiceClientCredentials : ServiceClientCredentials
     {
@@ -92,32 +95,32 @@ You must also have the [endpoint and access key](../How-tos/text-analytics-how-t
     }
     ```
 
-3. Update the `Program` class and add a constant member for your Text Analytics subscription key and another for the service endpoint. Remember to use the correct Azure region for your Text Analytics subscription.
+3. Update the `Program` class. Add a constant member for your Text Analytics subscription key, and another for the service endpoint. Remember to use the correct Azure region for your Text Analytics subscription.
 
     ```csharp
     private const string SubscriptionKey = "enter-your-key-here";
 
     private const string Endpoint = "enter-your-service-endpoint-here"; // For example: "https://westus.api.cognitive.microsoft.com";
     ```
 > [!Tip]
-> For secure deployment of secrets in production systems we recommend using [Azure Key Vault](https://docs.microsoft.com/azure/key-vault/quick-create-net)
+> To boost the security of secrets in production systems, we recommend that you use [Azure Key Vault](https://docs.microsoft.com/azure/key-vault/quick-create-net).
 >
 
 ## Create a Text Analytics client
 
-In the `Main` function of your project, call the sample method you would like to invoke and pass the `Endpoint` and `SubscriptionKey` parameters you defined.
+In the `Main` function of your project, call the sample method that you want to invoke. Pass the `Endpoint` and `SubscriptionKey` parameters that you defined.
 
 ```csharp
     public static void Main(string[] args)
     {
         var credentials = new ApiKeyServiceClientCredentials(SubscriptionKey);
         var client = new TextAnalyticsClient(credentials)
         {
-            //Replace 'westus' with the correct region for your Text Analytics subscription
+            //Replace 'westus' with the correct region for your Text Analytics subscription.
             Endpoint = "https://westus.api.cognitive.microsoft.com"
         };
 
-        // Change console encoding to display non-ASCII characters
+        // Change the console encoding to display non-ASCII characters.
         Console.OutputEncoding = System.Text.Encoding.UTF8;
         SentimentAnalysisExample(client).Wait();
         // DetectLanguageExample(client).Wait();
@@ -127,12 +130,12 @@ In the `Main` function of your project, call the sample method you would like to
     }
 ```
 
-Next sections describes how to call each of the API features.
+The following sections describe how to call each service feature.
 
-## Sentiment analysis
+## Perform sentiment analysis
 
-1. Create a new function called `SentimentAnalysisExample()` that takes the client created earlier.
-2. Generate a list of `MultiLanguageInput` objects, containing the documents you want to analyze.
+1. Create a new function `SentimentAnalysisExample()` that takes the client that you created earlier.
+2. Generate a list of `MultiLanguageInput` objects that contains the documents that you want to analyze.
 
     ```csharp
     public static async Task SentimentAnalysisExample(TextAnalyticsClient client)
@@ -150,7 +153,7 @@ Next sections describes how to call each of the API features.
     }
     ```
 
-3. In the same function, call `client.SentimentAsync()` and get the result. Then iterate through the results, and print each document's ID, and sentiment score. A score closer to 0 indicates a negative sentiment, while a score closer to 1 indicates a positive sentiment.
+3. In the same function, call `client.SentimentAsync()` and get the result. Then iterate through the results. Print each document's ID and sentiment score. A score that's close to 0 indicates a negative sentiment, while a score that's closer to 1 indicates a positive sentiment.
 
     ```csharp
     var result = await client.SentimentAsync(false, inputDocuments);
@@ -171,10 +174,10 @@ Document ID: 3 , Sentiment Score: 0.44
 Document ID: 4 , Sentiment Score: 1.00
 ```
 
-## Language detection
+## Perform language detection
 
-1. Create a new function called `DetectLanguageExample()` that takes the client created earlier.
-2. Generate a list of `LanguageInput` objects, containing your documents.
+1. Create a new function `DetectLanguageExample()` that takes the client that you created earlier.
+2. Generate a list of `LanguageInput` objects that contains your documents.
 
     ```csharp
     public static async Task DetectLanguageExample(TextAnalyticsClient client)
@@ -192,7 +195,7 @@ Document ID: 4 , Sentiment Score: 1.00
     }
     ```
 
-3. In the same function, call `client.DetectLanguageAsync()` and get the result. Then iterate through the results, and print each document's ID, and the first returned language.
+3. In the same function, call `client.DetectLanguageAsync()` and get the result. Then iterate through the results. Print each document's ID and the first returned language.
 
     ```csharp
     var langResults = await client.DetectLanguageAsync(false, inputDocuments);
@@ -213,10 +216,10 @@ Document ID: 2 , Language: Spanish
 Document ID: 3 , Language: Chinese_Simplified
 ```
 
-## Entity recognition
+## Perform entity recognition
 
-1. Create a new function called `RecognizeEntitiesExample()` that takes the client created earlier.
-2. Generate a list of `MultiLanguageBatchInput` objects, containing your documents.
+1. Create a new function `RecognizeEntitiesExample()` that takes the client that you created earlier.
+2. Generate a list of `MultiLanguageBatchInput` objects that contains your documents.
 
     ```csharp
     public static async Task RecognizeEntitiesExample(TextAnalyticsClient client)
@@ -233,7 +236,7 @@ Document ID: 3 , Language: Chinese_Simplified
     }
     ```
 
-3. In the same function, call `client.EntitiesAsync()` and get the result. Then iterate through the results, and print each document's ID. For each detected entity, print it's wikipedia name, the type and sub-types (if exists) as well as the locations in the original text.
+3. In the same function, call `client.EntitiesAsync()` and get the result. Then iterate through the results. Print each document's ID. For each detected entity, print its Wikipedia name and the type and subtypes (if they exist) as well as the locations in the original text.
 
     ```csharp
     var entitiesResult = await client.EntitiesAsync(false, inputDocuments);
@@ -286,10 +289,10 @@ Document ID: 2
                         Offset: 88,     Length: 7,      Score: 1.000
 ```
 
-## Key phrase extraction
+## Perform key phrase extraction
 
-1. Create a new function called `KeyPhraseExtractionExample()` that takes the client created earlier.
-2. Generate a list of `MultiLanguageBatchInput` objects, containing your documents.
+1. Create a new function `KeyPhraseExtractionExample()` that takes the client that you created earlier.
+2. Generate a list of `MultiLanguageBatchInput` objects that contains your documents.
 
     ```csharp
     public static async Task KeyPhraseExtractionExample(TextAnalyticsClient client)
@@ -306,7 +309,7 @@ Document ID: 2
     }
     ```
 
-3. In the same function, call `client.KeyPhrasesAsync()` and get the result. Then iterate through the results, and print each document's ID, and any detected key phrases.
+3. In the same function, call `client.KeyPhrasesAsync()` and get the result. Then iterate through the results. Print each document's ID and any detected key phrases.
 
     ```csharp
     var kpResults = await client.KeyPhrasesAsync(false, inputDocuments);
@@ -354,4 +357,3 @@ Document ID: 4
 
 * [Text Analytics overview](../overview.md)
 * [Frequently asked questions (FAQ)](../text-analytics-resource-faq.md)
-