Update csharp-sdk.md

Author: thediris

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

@@ -13,7 +13,7 @@ ms.reviewer: assafi
 
 <a name="HOLTop"></a>
 
-#### [Version 3.0-preview](#tab/version-3)
+#### [Version 3.0](#tab/version-3)
 
 [v3 Reference documentation](https://aka.ms/azsdk-net-textanalytics-ref-docs) | [v3 Library source code](https://github.com/Azure/azure-sdk-for-net/tree/master/sdk/textanalytics) | [v3 Package (NuGet)](https://www.nuget.org/packages/Azure.AI.TextAnalytics) | [v3 Samples](https://github.com/Azure/azure-sdk-for-net/tree/master/sdk/textanalytics/Azure.AI.TextAnalytics/samples)
 
@@ -37,9 +37,9 @@ ms.reviewer: assafi
 
 Using the Visual Studio IDE, create a new .NET Core console app. This will create a "Hello World" project with a single C# source file: *program.cs*.
 
-#### [Version 3.0-preview](#tab/version-3)
+#### [Version 3.0](#tab/version-3)
 
-Install the client library by right-clicking on the solution in the **Solution Explorer** and selecting **Manage NuGet Packages**. In the package manager that opens select **Browse**, check **Include prerelease**, and search for `Azure.AI.TextAnalytics`. Select version `1.0.0-preview.4`, and then **Install**. You can also use the [Package Manager Console](https://docs.microsoft.com/nuget/consume-packages/install-use-packages-powershell#find-and-install-a-package).
+Install the client library by right-clicking on the solution in the **Solution Explorer** and selecting **Manage NuGet Packages**. In the package manager that opens select **Browse**, check **Include prerelease**, and search for `Azure.AI.TextAnalytics`. Select version `1.0.0-preview.5`, and then **Install**. You can also use the [Package Manager Console](https://docs.microsoft.com/nuget/consume-packages/install-use-packages-powershell#find-and-install-a-package).
 
 > [!TIP]
 > Want to view the whole quickstart code file at once? You can find it [on GitHub](https://github.com/Azure-Samples/cognitive-services-quickstart-code/blob/master/dotnet/TextAnalytics/program.cs), which contains the code examples in this quickstart. 
@@ -53,7 +53,7 @@ Install the client library by right-clicking on the solution in the **Solution E
 
 ---
 
-#### [Version 3.0-preview](#tab/version-3)
+#### [Version 3.0](#tab/version-3)
 
 Open the *program.cs* file and add the following `using` directives:
 
@@ -116,7 +116,7 @@ Replace the application's `Main` method. You will define the methods called here
 
 The Text Analytics client is a `TextAnalyticsClient` object that authenticates to Azure using your key, and provides functions to accept text as single strings or as a batch. You can send text to the API synchronously, or asynchronously. The response object will contain the analysis information for each document you send. 
 
-If you're using version `3.0-preview` of the service, you can use an optional `TextAnalyticsClientOptions` instance to initialize the client with various default settings (for example default language or country/region hint). You can also authenticate using an Azure Active Directory token. 
+If you're using version `3.0` of the service, you can use an optional `TextAnalyticsClientOptions` instance to initialize the client with various default settings (for example default language or country/region hint). You can also authenticate using an Azure Active Directory token. 
 
 ## Code examples
 
@@ -128,7 +128,7 @@ If you're using version `3.0-preview` of the service, you can use an optional `T
 
 ## Authenticate the client
 
-#### [Version 3.0-preview](#tab/version-3)
+#### [Version 3.0](#tab/version-3)
 
 Make sure your main method from earlier creates a new client object with your endpoint and credentials.
 
@@ -150,7 +150,7 @@ Create a method to instantiate the [TextAnalyticsClient](https://docs.microsoft.
 
 ## Sentiment analysis
 
-#### [Version 3.0-preview](#tab/version-3)
+#### [Version 3.0](#tab/version-3)
 
 Create a new function called `SentimentAnalysisExample()` that takes the client that you created earlier, and call its `AnalyzeSentiment()` function. The returned `Response<DocumentSentiment>` object will contain the sentiment label and score of the entire input document, as well as a sentiment analysis for each sentence if successful. If there was an error, it will throw a `RequestFailedException`.
 
@@ -164,8 +164,7 @@ static void SentimentAnalysisExample(TextAnalyticsClient client)
     var si = new StringInfo(inputText);
     foreach (var sentence in documentSentiment.Sentences)
     {
-        Console.WriteLine($"\tSentence [length {sentence.GraphemeLength}]");
-        Console.WriteLine($"\tText: \"{si.SubstringByTextElements(sentence.GraphemeOffset, sentence.GraphemeLength)}\"");
+        Console.WriteLine($"\tText: \"{sentence.Text}\"");
         Console.WriteLine($"\tSentence sentiment: {sentence.Sentiment}");
         Console.WriteLine($"\tPositive score: {sentence.ConfidenceScores.Positive:0.00}");
         Console.WriteLine($"\tNegative score: {sentence.ConfidenceScores.Negative:0.00}");
@@ -179,14 +178,12 @@ static void SentimentAnalysisExample(TextAnalyticsClient client)
 ```console
 Document sentiment: Positive
 
-        Sentence [length 30]
         Text: "I had the best day of my life."
         Sentence sentiment: Positive
         Positive score: 1.00
         Negative score: 0.00
         Neutral score: 0.00
 
-        Sentence [length 30]
         Text: "I wish you were there with me."
         Sentence sentiment: Neutral
         Positive score: 0.21
@@ -210,7 +207,7 @@ Sentiment Score: 0.87
 
 ## Language detection
 
-#### [Version 3.0-preview](#tab/version-3)
+#### [Version 3.0](#tab/version-3)
 
 
 Create a new function called `LanguageDetectionExample()` that takes the client that you created earlier, and call its  `DetectLanguage()` function. The returned `Response<DetectedLanguage>` object will contain the detected language along with its name and ISO-6391 code. If there was an error, it will throw a `RequestFailedException`.
@@ -253,11 +250,11 @@ Language: English
 
 ## Named Entity Recognition (NER)
 
-#### [Version 3.0-preview](#tab/version-3)
+#### [Version 3.0](#tab/version-3)
 
 
 > [!NOTE]
-> New in version `3.0-preview`:
+> New in version `3.0`:
 > * Entity linking is now a separated from entity recognition.
 
 
@@ -271,7 +268,7 @@ static void EntityRecognitionExample(TextAnalyticsClient client)
     foreach (var entity in response.Value)
     {
         Console.WriteLine($"\tText: {entity.Text},\tCategory: {entity.Category},\tSub-Category: {entity.SubCategory}");
-        Console.WriteLine($"\t\tLength: {entity.GraphemeLength},\tScore: {entity.ConfidenceScore:F2}\n");
+        Console.WriteLine($"\t\tScore: {entity.ConfidenceScore:F2}\n");
     }
 }
 ```
@@ -280,11 +277,14 @@ static void EntityRecognitionExample(TextAnalyticsClient client)
 
 ```console
 Named Entities:
+        Text: trip,     Category: Event,        Sub-Category:
+                Score: 0.61
+
         Text: Seattle,  Category: Location,     Sub-Category: GPE
-                Length: 7,      Score: 0.92
+                Score: 0.82
 
         Text: last week,        Category: DateTime,     Sub-Category: DateRange
-                Length: 9,      Score: 0.80
+                Score: 0.80
 ```
 
 ## Entity linking
@@ -308,7 +308,7 @@ static void EntityLinkingExample(TextAnalyticsClient client)
         foreach (var match in entity.Matches)
         {
             Console.WriteLine($"\t\tText: {match.Text}");
-            Console.WriteLine($"\t\tLength: {match.GraphemeLength},\tScore: {match.ConfidenceScore:F2}\n");
+            Console.WriteLine($"\t\tScore: {match.ConfidenceScore:F2}\n");
         }
     }
 }
@@ -321,38 +321,38 @@ Linked Entities:
         Name: Altair 8800,      ID: Altair 8800,        URL: https://en.wikipedia.org/wiki/Altair_8800  Data Source: Wikipedia
         Matches:
                 Text: Altair 8800
-                Length: 11,     Score: 0.78
+                Score: 0.88
 
         Name: Bill Gates,       ID: Bill Gates, URL: https://en.wikipedia.org/wiki/Bill_Gates   Data Source: Wikipedia
         Matches:
                 Text: Bill Gates
-                Length: 10,     Score: 0.55
+                Score: 0.63
 
                 Text: Gates
-                Length: 5,      Score: 0.55
+                Score: 0.63
 
         Name: Paul Allen,       ID: Paul Allen, URL: https://en.wikipedia.org/wiki/Paul_Allen   Data Source: Wikipedia
         Matches:
                 Text: Paul Allen
-                Length: 10,     Score: 0.53
+                Score: 0.60
 
         Name: Microsoft,        ID: Microsoft,  URL: https://en.wikipedia.org/wiki/Microsoft    Data Source: Wikipedia
         Matches:
                 Text: Microsoft
-                Length: 9,      Score: 0.47
+                Score: 0.55
 
                 Text: Microsoft
-                Length: 9,      Score: 0.47
+                Score: 0.55
 
         Name: April 4,  ID: April 4,    URL: https://en.wikipedia.org/wiki/April_4      Data Source: Wikipedia
         Matches:
                 Text: April 4
-                Length: 7,      Score: 0.25
+                Score: 0.32
 
         Name: BASIC,    ID: BASIC,      URL: https://en.wikipedia.org/wiki/BASIC        Data Source: Wikipedia
         Matches:
                 Text: BASIC
-                Length: 5,      Score: 0.28
+                Score: 0.33
 ```
 
 #### [Version 2.1](#tab/version-2)
@@ -369,7 +369,7 @@ Create a new function called `RecognizeEntitiesExample()` that takes the client
 
 ## Key phrase extraction
 
-#### [Version 3.0-preview](#tab/version-3)
+#### [Version 3.0](#tab/version-3)
 
 Create a new function called `KeyPhraseExtractionExample()` that takes the client that you created earlier, and call its `ExtractKeyPhrases()` function. The returned `<Response<IReadOnlyCollection<string>>` object will contain the list of detected key phrases. If there was an error, it will throw a `RequestFailedException`.